Potential product reforms, such as raising the limit in the MIRon compensation for general damages.

IBC -llo..*..til~ May 31,2013 B jc A I Insuran~e Bureau of Canada ~{~ ~ Bureau d assurance du Canada William A. Adams Vice-President, Western & Pacific 10104-103 Avenue, Suite 2603, Edmonton, AS T5J OH8 780-423-22121 fax. 780-423-4796 510 Burrard Street Suite 901, Vancouver, BC V6C 3A8 604 684-3635 Ext. 2241 fax: 604-684-6235 Mr. Alfred Savage Chair Automobile Insurance Rate Board 2440 Canadian Western Bank Place 10303 Jasper Avenue Edmonton, AB TSJ 3N6 Dear Mr. Savage, Insurance Bureau of Canada (IBC) is pleased to respond to the Alberta Automobile Insurance Rate Board's (AIRS) request for input regarding the 2013 review of the required premium for basic coverage beginning November 1, 2013. Attached is the actuarial analysis prepared by IBC's consulting actuary, Dr. Ron Miller of Insurance Services. IBC has and continues to express the view to governments and regulators throughout the country that, while the regulation of rates provides a degree of comfort to some stakeholders, in a competitive market the cost of auto insurance claims is the major factor in determining the price of the product. For example, premiums in Ontario are the highest in Canada, despite the province employing one of the most strict rate regulation regimes. The reason for Ontario's high premiums is high claims costs, which are the result of many years of excessive utilization of an overly rich no-fault benefit package that is susceptible to abuse and outright fraud. Since 2004, the price of auto insurance in Alberta has fluctuated only modestly from year-to-year because of the relative stability of the product's cost structure. On many occasions, the government and the industry have collaborated to help maintain this cost stability and overcome threats to it, such as the constitutional challenge to the Minor Injury Regulation (MIR). The result is one of the most affordable auto insurance products in the country. In 2011, Albertans, on average, spent 2.8% of their disposable income on auto insurance, compared to 3.2% in Atlantic Canada and 5.3% in Ontario. 1 While the Facility Association's market in Alberta remains the largest among the provinces it serves, it has been declining steadily and now stands at 6.1 %. 2 Cost Environment There are three related factors we want to highlight for their potential to have an impact on the cost of delivering automobile insurance in Alberta. They are: Changes in injury claims patterns; Changes in property damage claims patterns; and Potential product reforms, such as raising the limit in the MIRon compensation for general damages. 1 IBC with data from GISA and Statistics Canada. 2 Facility Association (FARM and RSP). www.tbc.ca Reprcscutiug the ro111pcmics that insure your ho111c, your cnr. your lms~ucss. Reprcswtcwt /cs socictt;s qui assrm ut votn hnbitatiou, votrc autolllobrlc, 1 otrc eutrcpnse 1

Changes in Injury Claims Patterns In preparation for last year's IWA, IBC carried out a survey of fifteen insurance companies operating in Alberta in an effort to determine whether any impact on claiming behaviour has been seen following the January 2012 court decision in Sparrowhawk v. Zapoltinsky. As you know, the Alberta Court of Queen's Bench ruled that the temporomandibular joint disorder (TMD) suffered by the claimant in this case was not appropriate for treatment under the Diagnostic and Treatment Protocols Regulation (DTPR) and was not a minor injury. Most of the companies surveyed by IBC reported that the number of TMD claims was increasing. This development concerned us because TMD is associated with relatively high settlement costs. Indeed, a closed claims study that IBC sponsored for the Alberta constitutional challenge found that, as far back as 2004, claims with TMD diagnoses were responsible for 18.4% of bodily injury settlement dollars paid by insurance companies, while representing only 7.7% of these claims. 3 We repeated our survey this year and were informed that this pattern is continuing. We also found that, along with TMD, companies are experiencing more Section 8 claims for psychological impairment and chronic pain, both of which some stakeholders consider to be outside the MIR's application. These claims, which typically take longer to close, are beginning to appear earlier in the claims management process. Insurers also reported that there appears to be a positive correlation between an injured person having legal representation and that person pursuing a claim for TMD, psychological impairment and/or chronic pain. In our view, these developments suggest that more stakeholders may be beginning to use the Section 8 process to assert those types of injuries (TMD, chronic pain, depression) that can take their claim out of the minor injury class in order to build the case for more lucrative bodily injury general damages awards. According to some of the companies we surveyed, there is already beginning to be evidence that more people are pursuing claims for general damages, outside the MIR, based on TMD, psychological impairment and/or chronic pain. This was reflected in a statement that appeared in the 2012 annual report of one large carrier in describing recent Alberta injury claims developments: "Due to the age of older minor injury claims and the changing environment, plaintiff lawyers are aggressively working files in order to build the case for their clients". 4 Changes in Property Damage Claims Patterns A legal decision from December 2012 threatens to have negative effects for property damage liability costs. In Taylor v. Hrytsak, the judge at the Provincial Court of Alberta awarded the plaintiff $17,000 after finding that a vehicle involved in a collision had experienced "diminished value". Already, companies report receiving more claims for compensation for the perceived diminished value of a vehicle after it has been repaired following a collision. This development is not surprising because the size of the award in the case cited established an attractive windfall target even for individuals with no plans to sell their repaired vehicles. Thus, this court decision has created an opportunity for claimants that, coupled with the developments since the decision in Sparrowhawk v. Zapoltinsky, leaves the auto insurance product vulnerable to a rising number of more expensive liability claims. Changes to the Minor lnjurv Regulation (MIR) IBC understands that, at the urging of certain stakeholders, one of the changes the government is considering, in its review of the regulations related to the auto insurance product, is a one-time 3 Alberta Closed Claims Study, May 2006, prepared by Barb Addie, F. C.I.A., Insurance Services. 4 Intact Financial Corporation. Annual Report 2012. 2

increase in the award limit for general damages in the MIR. The current limit has been subject to annual inflation indexation since 2007. Governments in Atlantic Canada recently reviewed their limits on general damages that may be awarded for minor injuries. In 2010, the Nova Scotia government raised the limit from $2,500 to $7,500, and indexed it to changes in the Consumer Price Index (CPI). The New Brunswick government has just reformed its regulation, raising the limit to $7,500 effective July 1, 2013. While industry data is not mature enough to show the full impact of raising the limit in Nova Scotia, preliminary data indicates that, as between collisions that occurred in 2009 and those happening in 2011, the cost per car for bodily injury claims rose 9%, from $131.33 to $143.41. 5 We believe that this increase is, in part, simply the result of the higher non-pecuniary awards now available to those incurring minor injuries, but also that, to some extent, it may reflect an incentive effect that these higher awards have created. As we see in the actuarial analysis submitted with this letter, it appears that the statistical plan may already be reflecting cost pressures arising from the Sparrowhawk v. Zapoltinsky decision, as well as perhaps some measure of the typical erosion of the effectiveness of savings measures over time after a reform. In the case of the more recent Taylor v. Hrytsak decision, there is only anecdotal evidence to date from insurers that it may be changing the dynamics of property damage claims. Nonetheless, the fact that these new sources of cost pressure are clearly present suggests to us that, during this period in which the auto insurance market remains fairly stable, it would be highly prudent for the government to initiate an in-depth review of the claims cost environment in Alberta, and to work with stakeholders to develop solutions to the problems identified and ensure that the cost stability Albertans have come to expect continues into the future. IBC would welcome the opportunity to participate in these discussions. Commentary on the Industry-Wide Adjustment (IWA) On many occasions, we have expressed the view that a process reliant on competition is more appropriate than uniform adjustments for regulating the price of auto insurance. This view is based on several reasons: Uniform adjustments are more likely to disrupt the stability of the market. If a single company sets its premiums incorrectly in a competitive market, only that company feels the repercussions. But if an industry-wide indication is wrong, all companies and their consumers feel the effects. Experience in jurisdictions with rate regulation processes reliant on competition shows that premiums follow market conditions, and that competition tends to smooth out the impact that sudden changes in costs may have on prices. Strict regulation is costly. Last year, IBC conducted a Canada-wide study on the costs to the industry and its consumers that arise from funding the operations of the nearly 30 federal and provincial bodies having responsibilities for regulating insurance carriers and intermediaries. The results of the study showed that, in 2010, the direct cost that regulators charged to the industry was $80 million. It should be noted that this figure is, by no means, exclusive to auto insurance rate regulation, but rather covers the many governing bodies and types of regulation that the industry is subject to. Further, this estimate does not include the very substantial costs incurred by companies which need to use numerous expert personnel to carry out the activities required by regulators. In the case of auto insurance rate regulation, for example, depending upon the jurisdiction, 5 IBC with data from GISA. 3

companies can incur application fees, additional actuarial costs, and extensive staff time to comply with the different rate filing instructions used by different rate boards. As well, they incur the systems and human resources costs of reporting the additional data that rate regulators request, and the cost associated with the delay in getting indicated rates through the approval process and to the market. A more competitive rate-making environment encourages companies to differentiate themselves. This provides consumers with more choice through innovative product offerings and service models as companies compete more aggressively for the business of consumers. Last fall, IBC welcomed the opportunity to engage with the government and the AIRB in discussions on the Premiums Regulation. During that review, the industry proposed transitioning from an IWA process for basic coverage and a file-and-use process for optional coverage to a file-and-approve process for the entire product. The industry believes this model is more appropriate for a competitive market and will continue to provide a level of regulatory oversight that benefits consumers. Indication IBC does not endorse the assignment of a single rate adjustment indication for the entire industry. But because the IWA process calls for the provision of an indication, we retained Dr. Ron Miller of Insurance Services to conduct an actuarial analysis for this submission. On page 22 of Dr. Miller's enclosed report, the estimate given for the all-industry average of indicated required premium for basic coverage for November 1, 2013 is $670.82, while the projection of average street premium per car year, before annual adjustment, is stated as $591.00. These numbers imply that the indicated all-industry rate change is 13.5%. This indicated rate increase results largely from the confluence of two factors: the first factor is the influence of rising costs for bodily injury claims. Dr. Miller found that bodily injury claims from previous years are closing at a higher cost than was initially predicted. In reviewing past exhibits from GISA, we have found, that because of this development, the ultimate cost per car for Third Party Liability (TPL) claims for accident-years 2008 to 2011 has been adjusted upwards. The annual adjustments are set out in the table below. Changes to Ultimate Cost per Car for TPL Claims for Accident-Years (AY) 2008 to 2012 6 Exhibit Year 2008 2009 2010 2011 2012 AY 2008 AY 2009 AY 2010 AY 2011 AY 2012 378.55 370.76 406.04 379.79 379.86 399.71 ~34:o2' /;.... '.(1~:9z:~;'!Ifl!lff 1 ijli~'{4~:1 :~,~ ;.9/'i~;;,,.',;l:f?~;Ji'1.~$i Tt'!EX:cl :G~ 442f51 '. < The table also shows that the largest increases happened between the 2011 and 2012 GISA publications. In fact, between the publication of the 2011 and 2012 exhibits, the estimated ultimate cost per car for TPL claims for accident-years 2008, 2009, 2010 and 2011 increased by 6 IBC with data from GISA. 4

an average of 8.1%. By comparison, the increase between the 2010 and 2011 exhibits for accident-years 2008, 2009 and 2010 was an average of 2.8% and the change between the 2009 and 2010 exhibits for accident-years 2008 and 2009 was an average of 0.4%. The substantial adjustments between the 2011 and 2012 publications coincide with the court decision in Sparrowhawk v. Zapoltinsky. A second factor contributing to the magnitude of the indicated rate increase for 2013 is related to previous decisions of the AIRB regarding price adjustments. As noted above, Dr. Miller estimates that the average street premium for the basic auto insurance product as of November 1, 2013, prior to implementation of the IWA adjustment, will be $591.00. That the average street premium will be this low and the corresponding difference between street and indicated premium so wide, is in part a reflection of the Board's decision at last year's IWA. Thus, a year ago, the kinds of bodily injury cost pressures that are described in this letter and documented in the accompanying actuarial analysis were already very much in evidence. It was for this reason we understand that the Board's actuary, Oliver Wyman, identified an indicated adjustment for 2012 of +11.5%. However, the AIRB decided to permit an IWA of only +5% last year, leaving a sizable gap between the cost escalation trend, which was well under way, and the premium adjustment. Unfortunately, on an all-industry basis, the gap between average premium and costs has continued to grow over the past year. IBC is, of course, quite aware that not all companies have applied the +5% permitted adjustment. While companies have up to three years to apply the adjustment, we see the fact that some companies have not taken it as providing strong and positive evidence to support the industry's long-held position that a single, one-size-fits-all adjustment factor is not at all appropriate in a competitive market. It also shows that, even in a restrictive rate regulation context, companies' pricing decisions are based as much as they can be on each company's own book of business and market strategy. At the same time, however, we want to caution that individual company responses to past IWA directives should not take away from the requirements in the Premiums Regulation to decide on an all-industry adjustment that is reflective of industry-wide experience. Conclusion The principal messages we want to convey to the AIRB are summarized as follows: According to IBC's consulting actuary, the indicated rate adjustment for basic coverage, effective November 1, 2013 is 13.5%. We believe that the evidence, including Oliver Wyman's analysis and information from individual companies, will be sufficient to allow the AIRB to arrive at an adjustment decision that truly reflects the cost trends and projections that are put before it. In this regard, we believe that it will be particularly important that, on an all-industry basis, basic product rates are at or close to actuarial adequacy when the rate regulation system transitions to a more competitive process. There is little doubt that the pressures on bodily injury claims costs, as well as - albeit more recently - property damage tort claims, have become more pronounced. Consequently, we are urging the government to undertake an in-depth review of the factors affecting claims costs with a view to developing solutions that can protect the future stability of Alberta's automobile insurance market. Finally, we want to reiterate our support of the government moving forward with changes to the Premiums Regulation that permit competition to play a greater role in determining auto insurance premium levels. In our view, this will bring benefits to Alberta's driving public through lower premiums for good drivers, stronger incentives for safe driving, increasing product innovation, and more consumer choice. 5

We look forward to reviewing Oliver Wyman's analysis when it becomes available, and subsequently meeting with the AIRB on June 11, 2013. ~ William A. Adams Vice-President, Western & Pacific Enclosure (1) 6

Actuarial Analysis re Alberta Private Passenger Automobile Insurance Industry-Wide Rate Level Adjustment for Basic Coverage Effective November 1, 2013 submitted to Alberta Automobile Insurance Rate Board for its June 2013 Review prepared for Insurance Bureau of Canada by Insurance Services Inc. May 31, 2013

Table of Contents 1. Overview... 1 1.1 Introduction... 1 1.2 Scope... 1 1.3 My Approach... 2 1.4 Data Restatement... 3 1.5 Major Caveats... 4 2. Assumptions and Model Parameters in the Analysis... 8 2.1 Incurred Count and Incurred Amount Loss Development Factors... 8 2.2 Unallocated Loss Adjustment Expense Factors... 10 2.3 Trending Model... 12 2.3.1 Independent Variables in Trending Model... 12 Variable = Change in Level re the 2004 Reforms for TPL-BI... 13 Variable = Change in Level re the 2004 Reforms for Other Sub-Coverages... 13 Variable = Change in Trend re the 2004 Reforms for TPL-BI... 13 Variable = Change in Trend re the 2004 Reforms for Other Sub-Coverages... 13 Variable = Change in Level at 01/03/2007... 14 2.3.2 Acceptance or Rejection of Independent Variables... 14 2.3.3 Summary of Findings re 2004 Reforms for Major Sub-Coverages... 15 Variable = Change in Level re 2004 Reforms... 15 Variable = Change in Trend re 2004 Reforms... 15 2.3.4 Summary of Findings re Change in Level at 01/03/2007 for Major Sub-Coverages... 16 Variable = Change in Level at 01/03/2007... 16 2.3.5 Forward Projections... 16 2.4 Payment Pattern... 17 2.5 Fixed and Variable Expenses... 17 2.6 Alberta Health Levy... 19 2.7 Discounting for the Time Value of Money... 19 2.7.1 Forward New Money Pre-Tax Investment Rate re Cash Flow on Underwriting... 19 2.7.2 Discounting Process... 20 2.8 Profit and Contingency Margin... 20 2.9 Average Street Premium... 21 3. High Level Summary of Findings... 22 3.1 Required Rate Change... 22 Exhibit 1 - Required Premiums and Overall Rate Change for Basic Coverage... 23 Exhibit 2 - Trending Model and Forward Projections... 27 Exhibit 3 - Derived Accident Half-Year Payment Patterns... 37

1. Overview 1.1 Introduction Insurance Bureau of Canada (IBC) commissioned Insurance Services Inc. (EISI) to provide an actuarial analysis to the Alberta Automobile Insurance Rate Board (AIRB, or the Board) for its June 2013 Annual Review of Automobile Insurance Premiums for Basic Coverage (i.e.: Third Party Liability and Accident Benefits), which will culminate in an industry-wide rate adjustment to be effective November 1, 2013 for Private Passenger Automobile Insurance. The author of this report is as follows: Ronald R. Miller Insurance Services Inc. 30 Killdeer Crescent Toronto, ON M4G 2W8 Telephone: (416) 421-8930 Fax: (416) 421-9599 E-Mail: exactor@smpatico.ca The author is a Fellow of the Casualty Actuarial Society and a Fellow of the Canadian Institute of Actuaries. 1.2 Scope My report is based on analysis of the Basic Coverage data at the sub-coverage level as included in the all-industry Private Passenger (excluding Farmers) 2012-2 Loss Development Exhibit recently published by GISA. It includes the following: projection of reported-to-date claim experience to ultimate values including Unallocated Loss Adjustment Expense (ULAE), but excluding the Alberta Health Levy costs trending of ultimate claim frequency, claim severity, and claim cost per car year of experience to levels appropriate for the policy (rating) year starting November 1, 2013, based on a regression model which tests, amongst other things, for changes in level and changes in trend at the time of implementation of the 2004 product reforms projection of claim payment patterns based on paid-to-date claim amount development projection of fixed and variable expenses and Alberta Health Levy costs to levels appropriate for the policy (rating) year starting November 1, 2013 projection of average street premium per car to a level judged to be applicable to the policy (rating) year starting November 1, 2013, prior to any industry wide adjustment decision the AIRB may make this cycle 1

1.3 My Approach I have reviewed and analyzed the currently available data and have performed the following steps: projection of ultimate claim counts and amounts from the raw reported-to-date Private Passenger (excluding Farmers) Alberta all-industry Green Book 31/12/2012 Loss Development Exhibit experience incurred-to-date claim count and claim amount data by accident half year by application of Loss Development Factors selected by me, and the loading of the resulting claim amounts for ULAE by application of the ULAE factors to be published in the Green Book (with one exception - see Section 2.2 below) forward projection of car years of exposure and ultimate claim frequencies, claim severities, and claim costs per car year of exposure for the next few accident half years, from the resulting ultimate claim frequencies, claim severities, and claim costs per car year of exposure above, using a log linear regression model which, amongst other things, tests for a change in level and a change in trend at the time of implementation of the 2004 reforms (mostly at 01/10/2004, except for some earlier reforms to the tort bodily injury coverage which were effective 24/01/2004) derivation from these forward projections of corresponding values appropriate for the policy year starting 01/11/2013 by the application of appropriate overlapping exposure weights projection of cumulative paid amount Loss Development Factors from the raw paid-to-date Private Passenger (excluding Farmers) Alberta all-industry Green Book 31/12/2012 Loss Development Exhibit experience paid claim amount data by accident half year, and conversion of these into projected payout patterns appropriate to the policy year starting 01/11/2013 projection of fixed expense amount per car year and the variable expense margin appropriate to the policy year starting 01/11/2013 based on the IBC 2011 Calendar Year Automobile Expense Survey report data projection of Alberta Health Levy costs appropriate to the policy year starting 01/11/2013, based on the Health Cost Recovery Amounts up to 2012 as shown in the AIRB s 2012 Annual Report together with judgment projection of the forward interest rate applicable to cash flow on underwriting and appropriate to the policy year starting 01/11/2013, based on current and expected near term yields on Government of Canada bonds matched approximately to the average duration of the claim liabilities 2

forward projection of the average street premium per car year to the level judged to be applicable to the policy (rating) year starting 01/11/2013 (before consideration of any adjustment that the AIRB may mandate as the result of the current annual review, or of any interim individual company Section 6 rate changes that the AIRB may otherwise approve subsequent to those which are fully reflected in the currently available data, to 1 st Quarter 2013), but this cycle making a judgmental adjustment to impute an additional amount in recognition that the written premium data up to early 2013 reflects significantly less than a 100% uptake so far of the +5% 01/11/2012 IWA decision last year The final indicated rate change may be derived by the following additional steps: deriving discount factors (discounting to average date of writing a policy) appropriate to the policy year starting 01/11/2013, based on the forward interest rate together with the payment patterns discussed above converting the ultimate claim costs, Health Levy costs, and fixed expense amount per car year appropriate to the policy year starting 01/11/2013 discussed above to appropriate discounted amounts using these discount factors, loading for forgone investment income due to the estimated average lag interval between writing a policy and receiving the premium, and loading by the variable expense margin plus selected profit and contingency margin, to produce the indicated required premiums per car year appropriate to the policy year starting 01/11/2013 loading these indicated required premiums per car year were for fixed expenses by distributing the indicated required premium for fixed expenses proportionally to the remaining required premium items to arrive at final indicated required premiums per car year appropriate to the policy year starting 01/11/2013 deriving the indicated required overall rate change appropriate to the policy year starting 01/11/2013 as the ratio of the total Basic Coverage indicated required premium per car year to the projected average street premium per car year, less one 1.4 Data Restatement The analysis underlying this report uses the data from the recently released GISA Alberta Private Passenger (ex. Farmers) 31/12/2012 Loss Development Exhibit. This is the second cycle where this exhibit has been produced from the new exhibit system implemented by GISA. As part of my analysis, I compared the TPL and AB data in this exhibit against its analogue from the 31/12/2011 exhibit which was also produced from the new exhibit system. For exposure and premiums, this comparison revealed only minor changes in overlapping data points, generally less than 0.5% in magnitude and in the most recent periods. For incurred claim counts, and paid and incurred claim amounts, this comparison also revealed only minor changes in overlapping data points, all less than 0.5% and generally in the most recent periods. Such changes are expected as some insurers refile data. This situation contrasts with the situation last cycle, when the exhibit system had changed, which showed somewhat larger and unusual data swing patterns. 3

1.5 Major Caveats There are many caveats which are applicable to my report. Principal amongst these are the following: all projections of average future claim costs are uncertain, the more so for the longer tail sub-coverages where claims do not settle for a substantial period of time because of significant product reform under Bill 53 and related initiatives, the subsequent Charter Challenge, and the inevitable erosion of the effectiveness of the Minor Injury Cap over time, this level of uncertainty in average future claim costs is higher than would otherwise be the case especially for the most recent years even though the Charter Challenge was ultimately defeated and the MIR was determined to be constitutional, the evolution of this challenge and recent court decisions likely lead to ultimate claim costs and development patterns which are different from what they would have been in their absence. Chronological highlights here are: 02/2008 decision of the lower court striking down the MIR ab initio 06/2009 Court of Appeal decision reversing the lower court s decision 12/2009 denial of leave to appeal by the Supreme Court of Canada 01/2012 Decision of the Alberta Court of Queen s Bench in Sparrowhawk v. Zapoltinsky regarding whether TMD is a minor injury This makes the projections of future development patterns and future costs here more uncertain because of possible disturbances to development patterns for recent periods, stemming from a number of sources, including the following: insurers generally increased their unpaid claim liability by year end 2008 after the lower court decision, often only through a change in bulk reserves (not reported under ASP), but in some cases, by increasing TPL-BI claim case reserves, and such increases in total reserves generally reflected an expectation of ultimate claim costs as a probability-weighting of values appropriate if the MIR remained struck down and if it were ultimately restored on appeal insurers continued to settle claims, including MIR claims, after the lower court decision, but closure rates declined insurers generally decreased their unpaid claim liability in this connection by year end 2009 after the Court of Appeal decision reversing the lower court decision and just after the denial of leave to appeal by the Supreme Court of Canada, often only through a change in bulk reserves (not reported under ASP), but in some cases, by decreasing TPL-BI claim case reserves 4

because of the timing of the denial of leave to appeal by the Supreme Court of Canada, a few insurers may not have had time to fully reduce their case reserves in this connection by 31/12/2009 as of 31/12/2009, there may be more incurred but unreported TPL-BI claims than usual, if some claimants in recent accidents may have been waiting to hear what the Supreme Court of Canada would say and delayed filing proof of loss until after the 17/12/2009 refusal of the Supreme Court of Canada to grant leave to appeal during the 2012 calendar year, there may be increases in case incurred claim severities for recent prior period claims asserting a TMD injury, and a corresponding increase in severity for new claims asserting such an injury claim count and claim amount development patterns for the 2004-2 and subsequent accident periods along future calendar period diagonals may in the fullness of time prove to differ from each other for the Third Party Liability - Bodily Injury sub-coverage the last several calendar half year diagonals in the incurred claim amount data development triangles for TPL-BI show development factors since the 2004 reforms at each development level often to be generally increasing for the latest several accident half years, with especially significant increases on the latest two such diagonals - this is likely a reflection of the inevitable erosion over time of the proportion of injuries falling under the Minor Injury Threshold, as claimants and their counsel seek ways to bypass the threshold, and the 01/2012 Sparrowhawk decision may be one of the factors underlying this changes along the latest two diagonals Alberta gasoline prices at the pump have been quite volatile in recent years, except for a fairly stable stretch in 2009 and 2010, and including a very volatile stretch in 2008 - periods of higher gasoline prices may lead to a reduction in road exposure and therefore fewer claims, while periods of lower gasoline prices may have the opposite effect - no account of these fluctuations in gasoline prices has been taken into account in the analysis here all projections of future average street premium amounts are uncertain, but some more recent data, not part of the regular GISA 31/12/2012 Green Book exhibits, sheds some useful light on this issue (see Section 3.9 below) - for the purposes of this analysis I have assumed no net effect on average rates based on interim individual company Section 6 rate changes to compulsory coverage which the Board may approve subsequent to those fully reflected in this additional data, except that I have added an adjustment (that might or might not come to pass) to impute an additional amount recognition that the written premium data up to early 2013 reflects significantly less than a 100% uptake so far of the +5% 01/11/2012 IWA decision last year 5

all results in this report apply to all-industry averages and do not apply to and may not be appropriate for any particular individual company, especially given that each individual company had its compulsory insurance rates frozen as of 30/10/2003 at levels then in force (for new business) and at levels in force over the preceding year (for renewal business) - as with any competitive market, at that particular point in time, different insurers had different relative rate adequacy levels, but each was frozen at its own particular level just the same, and this issue continues to some degree going forward, although there has been some amelioration of this situation in recent years through Section 6 rate filings the underlying experience data analyzed in this report is for the all-industry Private Passenger Automobile (excluding Farmers, but including Fleets rated on a per car basis, and Trailers but with their exposure suppressed) class of business, but the indicated industry-wide rate level adjustment is meant to and does in fact apply to the Private Passenger Automobile (including Farmers, but excluding Fleets) class of business - the Farmers Private Passenger book of business accounts for a relatively small approximately 3% adjustment which should be added to the number of cars, with average premium levels for Basic Coverage at roughly half that of that for Private Passenger (excluding Farmers), but is expected to be subject to percentage changes in premiums and presumably in claim costs on account of the reforms similar to those of Private Passenger (excluding Farmers), and the Private Passenger Fleets on a per car basis book accounts for a relatively small approximately 0.7% adjustment which should be subtracted from the number of cars, with average premium levels (including premiums but not exposure for trailers) for compulsory coverage at roughly 60% to 70% above that of Private Passenger (excluding Farmers) - as such, the indicated compulsory insurance required premiums and projected street premiums per car in my report, which do reflect the inclusion of Fleets on a per car basis and Trailers with their exposure suppressed, but do not reflect the inclusion of Private Passenger Farmers business, may both be slightly overstated for the Private Passenger (including Farmers, but excluding Fleets and Trailers) class of business, but the indicated percentage rate change based on these is not expected to be materially affected all results in this report apply to all-industry all classification cell averages and do not apply to and may not be appropriate for any particular territory or other classification cell, even at the all-industry level, let alone at the individual company level - this may be a particular issue for any individual company whose distribution of business is significantly different from that of all-industry at the territorial level, or along other classification dimensions Effective 01/07/2006, the GST rate was reduced from 7% to 6%, and effective 01/01/2008, it was further reduced from 6% to 5% - to the extent that some components of claim and other expense costs are subject to the GST, these changes are expected to reduce such costs slightly, and this issue has not been addressed explicitly in my analysis, but for expenses, it is implicitly accounted for by starting from expense data from 2008, and for claims, it is implicitly accounted for to some degree by the regression methodology used for trending 6

the historical payment patterns estimated in this report are based on the analysis of the underlying raw paid-to-date Green Book development data which in part relates to the product as it was prior to the Bill 53 and related reforms, in part relates to the product as was after the reforms but before the lower court decision, in part relates to the product as it is after the 02/2008 strikedown of the MIR but before the reversal of this decision by the Court of Appeal, in part relates to the product as it is after the 06/2009 reversal of the lower court decision by the Court of Appeal but before the denial of leave to appeal by the Supreme Court of Canada, in part relates to the product as it is after the denial of leave to appeal by the Supreme Court of Canada, and in part relates to the environment as it is after the Sparrowhawk decision - some shift in the payment patterns on account of the reforms and on account of this situation, especially for the Third Party Liability - Bodily Injury (TPL- BI) sub-coverage should be expected, and I have made an adjustment to the pattern I might otherwise have selected for this latter sub-coverage, based on judgment Orders-in-Council 520/2006 to 522/2006 revised certain regulations under the Insurance Act - in particular, by: increasing, effective 01/03/2007, certain caps on accident benefits under the Accident Benefits Regulation, including the cap on the funeral benefits ($2,000 up to $5,000) and weekly disability income indemnity cap ($300 to $400 for employed, $100 to $135 for others - this reform is expected to increase claim costs slightly and is explicitly addressed in my analysis by the introduction of an additional level variable in my trend analysis indexing the Minor Injury Amount (cap on non-pecuniary damages in cases of minor injury) based on a calculated change in the Alberta CPI, effective 01/01/2007 and each subsequent January 1 - for 2007, the $4,000 amount increased by 3.6% to $4,144, for 2008 by 4.7% to $4,339, for 2009 by 3.8% to $4,504, for 2010 by 0.3% to $4,518, and for 2011 by 0.9% to $4,559 - this reform is expected to increase claim costs slightly and is not explicitly addressed in my analysis Effective 01/06/2013, rates in the fee schedules for Chiropractic and Physical Therapy services are increasing modestly, which may lead to a modest increase in AB-MR claim costs, but no account of this change has been taken here In recent previous cycles, the ULAE factor, Private Passenger Commission loading, and general expense loading for the latest year (now 2012 this cycle) were taken from the values published by IBC in its Automobile Expense Survey (AES) report for the latest year, but unfortunately, this survey was discontinued after the last cycle, and no new data is available The new exhibit system has produced overlapping loss development data which differs somewhat from the analogous data from the old system for older accident periods 7

2. Assumptions and Model Parameters in the Analysis My analysis of the 2012-2 Loss Development Exhibit and other data incorporates a number of assumptions and selection of model parameters, the most important of these are discussed in the following sub-sections. 2.1 Incurred Count and Incurred Amount Loss Development Factors I selected incurred count and incurred amount loss development factors by sub-coverage and accident half year based on analysis of the recently released GISA Alberta Private Passenger (ex. Farmers) 31/12/2012 Loss Development exhibit. As a default, the selected factors were taken as the average of the latest four such factors, except for the first, which was taken as the average of the latest two such factors for the same half year (because of seasonality). I then made a number of adjustments to these default factors, by judgment at the sub-coverage level, as follows: TPL-BI: because of the generally high incurred age-to-age claim amount development factors observed on the latest two calendar half year diagonals (see table below) and uncertainty as to whether such higher values are likely to continue in the future (or perhaps rather decrease or perhaps even increase further), this cycle, instead of adopting the default factors, I selected factors for both incurred counts and amounts as the average of the latest six such factors, except for the first, which was taken as the average of the latest three such factors for the same half year (because of seasonality), except that the 17 th factor for amounts was increased by about 0.4% to account for an expected lag in development post reform - had I adopted the default factors (with adjustment) instead (which are similar to the factors adopted by GISA s actuary for Green Book purposes), the resulting projection of the ultimate claim cost for the policy year starting 01/11/2013 would have been about 6.5% higher Alberta PPAxF TPL-BI Historical Incurred Amount Age-to-Age Development Factors Based on Analysis of GISA PPAxF Loss Development Data as of 31/12/2012 Accident Age / Age (Months) Half Year 12/06 18/12 24/18 30/24 36/30 42/36 48/42 54/48 60/54 66/60 72/66 78/72 84/78 90/84 96/90 20051 1.100 1.004 1.017 1.013 1.028 1.048 1.032 1.023 1.001 1.008 1.013 1.019 1.021 1.009 1.005 20052 1.171 0.978 1.017 1.010 1.062 1.054 1.042 1.010 1.002 1.009 1.015 1.019 1.020 1.009 20061 1.070 0.970 0.997 1.055 1.040 1.042 1.003 1.024 1.031 1.019 1.015 1.024 1.018 20062 1.190 0.916 1.015 1.080 1.053 1.032 1.019 1.044 1.009 1.017 1.024 1.018 20071 1.138 0.997 1.050 1.085 1.042 1.035 1.018 1.041 1.038 1.031 1.043 20072 1.207 1.038 1.050 1.044 1.042 1.068 1.036 1.021 1.031 1.031 20081 1.169 1.005 1.007 1.052 1.071 1.083 1.051 1.069 1.048 20082 1.221 0.985 1.042 1.095 1.077 1.047 1.067 1.053 20091 1.047 0.972 1.034 1.088 1.058 1.100 1.090 20092 1.123 1.007 1.077 1.043 1.089 1.084 20101 1.085 0.978 1.048 1.075 1.084 20102 1.111 0.997 1.059 1.071 20111 1.065 1.000 1.046 20112 1.147 1.047 20121 1.206 8

The paid amount develop factors selected as discussed in Section 2.4 below may be used to produce another and different set of estimates of the ultimate claims amounts here, and the following table provides a comparison of these two sets of estimates for accident half years 2005-1 and subsequent: Alberta PPAxF TPL-BI Ultimate Claim Cost per Car (excluding ULAE) Comparison of Incurred vs Paid Projections Based on Analysis of GISA PPAxF Loss Development Data as of 31/12/2012 Accident Half Year Incurred (I) Projection Paid (P) Projection Difference P Less I % Difference P / I 2005-1 $212.50 $206.65 ($5.85) -2.8% 2005-2 $227.98 $220.41 ($7.57) -3.3% 2006-1 $201.30 $194.92 ($6.37) -3.2% 2006-2 $243.70 $232.84 ($10.86) -4.5% 2007-1 $195.48 $180.93 ($14.56) -7.4% 2007-2 $236.68 $230.42 ($6.26) -2.6% 2008-1 $211.82 $196.21 ($15.62) -7.4% 2008-2 $242.82 $223.65 ($19.17) -7.9% 2009-1 $190.66 $181.08 ($9.58) -5.0% 2009-2 $234.02 $220.16 ($13.85) -5.9% 2010-1 $179.37 $189.34 $9.97 5.6% 2010-2 $238.52 $241.10 $2.59 1.1% 2011-1 $185.83 $200.07 $14.23 7.7% 2011-2 $239.03 $241.78 $2.74 1.1% 2012-1 $216.28 $233.34 $17.06 7.9% 2012-2 $214.03 $215.75 $1.71 0.8% Average $216.88 $213.04 ($3.84) -1.8% Because of the significantly larger age-to-age development factors for Paid versus Incurred, the Paid projection meteorology is much less stable than the Incurred projection methodology. Nevertheless, the above table shows that for the 2005-1 and subsequent accident periods, the two sets of projections are on average quite close, and that for the last six periods (i.e. those in 2010, 2011, and 2012), the Paid projections are higher than the Incurred projections, which suggests that it is unlikely that the Incurred projections here are being overstated because of possible current overly conservative case reserves. 9

AB-FB: for both incurred counts and amounts, the factors were taken as the weighted average factors, except for the 1 st, which was taken as the weighted average of such factors for the same half year AB-DB: for both incurred counts and amounts, the factors were taken as the weighted average factors, except for the 1 st, which was taken as the weighted average of such factors for the same half year AB-DI: for incurred amounts, the 6 th factor was taken as the weighted average factor AB-SB: for both incurred counts and amounts, the factors were replaced by factors selected by judgment AB-UM: for both incurred counts and amounts, the factors were taken as weighted average factors, except for the first, taken as the weighted average such factors for the same half year In many cases, apparently spurious factors in the tail were ignored. Detailed supporting exhibits are not included in this report. In my view, especially because of observed generally higher incurred claim amount age-to-age development along the latest two calendar half year diagonals for TPL-BI, which may reflect erosion of the threshold from the 01/2012 Sparrowhawk decision amongst other causes, significant uncertainty remains at this time as to the values of the eventual ultimate claim amounts for TPL-BI for recent accident periods, and development patterns for these may in the fullness of time prove to differ from their analogues from the recent past and from each other, the more so for the more recent periods. These factors were applied by sub-coverage and accident half year to the reported-to-date incurred counts and amounts in the 2012-2 PPA LDE data to project ultimate counts and amounts, the amounts being before inclusion of Unallocated Loss Adjustment Expenses. 2.2 Unallocated Loss Adjustment Expense Factors Claim data reported under the Automobile Statistical Plan (ASP) includes Pure Loss (indemnity) and Allocated Loss Adjustment Expenses (ALAE), but not Unallocated Loss Adjustment Expenses (ULAE). It is therefore necessary to adjust such claim amounts to include ULAE in order to get a proper picture of total claim costs. I selected ULAE factors as those published by GISA in the introductory pages of the 2012 PPA ALR for the most recent years, except that the factors for 2008 and 2009 were replaced by their average (see footnote below table following). The 2012 factor was taken as the same as the 2011 factor, since the old IBC Automobile Expense Survey (AES) was discontinued after the last cycle, and no new data is available - it is my understanding that a similar approach for 2012 is being taken for production of the GISA Green Book exhibits. For earlier years, I selected the factors as those previously published by GISA and/or IBC. These factors were applied uniformly by sub-coverage and accident half year to the ultimate claim amounts projected in section 3.1 above. 10

The selected ULAE factors are as follows for accident years 1994 and subsequent: Alberta Private Passenger (Excluding Farmers) Automobile Insurance Green Book Unallocated Loss Adjustment Expense Factors (except 2008 and 2009) Accident Year ULAE Factor 1996 1.083 1997 1.085 1998 1.101 1999 1.112 2000 1.101 2001 1.076 2002 1.089 2003 1.093 2004 1.103 2005 1.097 2006 1.087 2007 1.089 2008 1.095* 2009 1.095* 2010 1.102 2011 1.095 2012 1.095** * because of a distortion caused by the way these factors are derived from calendar year data and the fact that insurers increased total reserves materially during 2008 on account of the lower court decision striking down the MIR and reduced them materially during 2009 on account of the appeal court decision and Supreme Court denial of leave to appeal, both in the Green Book and here, the factors for both 2008 and 2009 are taken as the average of those indicated by the Automobile Expense Survey data (1.084 for 2008 and 1.105 for 2009) ** because the Automobile Expense Survey was discontinued, no new data is available here, and the 2011 factor has been adopted for 2012 These factors were applied to the ultimate claim amounts (before ULAE) projected in section 3.1 above. For 2004 and prior, the factors are derived from aggregate data submitted under the old IBC Expense Allocation Program, and for 2005 and subsequent, they are derived from aggregate data submitted under the new IBC Automobile Expense Survey. 11

2.3 Trending Model I used a log linear regression trending model applied at the accident half year and sub-coverage level (see Exhibit 2). The input to this model is the historical earned exposure and premium data and projected ultimate claim counts and amounts (from sections 3.1 and 3.2 above), all derived from the 2012-2 PPA LDE data, for the 1996-1 and subsequent accident half years - this provides a balance between the number of years included which were before and which were after the year of the reforms (2004). Because the trending model is a linear regression on the logarithms of the dependent variables of claim frequency, claim severity, and claim cost per car year, it provides a consistent treatment of these three dependent variables (i.e. the tautology claim frequency x claim severity = claim cost per car year is preserved in all fitted and projected values). This is not necessarily the case with other trending models. 2.3.1 Independent Variables in Trending Model This model tests for the significance of, and potentially fits, parameters related to up to 7 independent variables, as follows: Overall Level Change in Level re the 2004 Reforms Change in Level at 01/03/2007 Change in Level for 2 nd half years compared to 1 st half years (i.e. Seasonality re 2 nd half years) Change in Level for half years with Weather related Catastrophe Occurrences Overall Trend Change in Trend re the 2004 Reforms For the Third Party Liability - Bodily Injury (TPL-BI) sub-coverage, in the last cycle, I made adjustments to the values (which would otherwise have been appropriate) of the independent variables relating to Change in Level re the 2004 Reforms and to Change in Trend re the 2004 Reforms. 12

In the last cycle, for the Change in Level variable, a further adjustment was made in recognition of a pattern in the data which then appeared to indicate that the effect on TPL-BI loss costs after the 2004 Reforms did not occur suddenly, but rather phased itself in over an extended period of time, but with some disruption to this pattern on account of the 02/2008 lower court decision striking down the MIR, the subsequent 06/2009 decision of the Court of Appeal, and the 12/2009 denial of leave to appeal by the Supreme Court of Canada. However, since the last cycle, the projections of post reform ultimate claims cost per car no longer show this anomalous pattern, many of them having undergone significant development in the last year, and so I have dropped the phase in approach. For both the Change in Level and Change in Trend variables, these adjustments were made in recognition of the fact that part of the reforms here (i.e. gross to net income loss and offset of collateral source amounts) became effective at 24/01/2004, before the 01/10/2004 date when most of the reforms were implemented, and I have continued this approach this cycle. My adjustments for the earliest periods are based on KPMG s a priori estimate that 30% of the total savings for TPL-BI would be due to the part of the reforms which ended up being implemented earlier (see page 20 of KPMG s 13/12/2004 report to Alberta Finance Report I Costing Analysis of 2004 Auto Reform : 80 / (80 + 189) = 30%), and on judgment, and are as follows: Variable = Change in Level re the 2004 Reforms for TPL-BI: Time 0 = 01/01/2004 Value for 2004-1 = 30% of (1.00-23 / 181) =.262 Value for 2004-2 = 30% of 1.00 + 70% of.50 =.650 Value for 2005-1 and subsequent = 1.000 Variable = Change in Level re the 2004 Reforms for Other Sub-Coverages: Time 0 = 01/01/2004 Value for 2004-2 =.500 Value for 2005-1 and subsequent = 1.000 Variable = Change in Trend re the 2004 Reforms for TPL-BI: Time 0 = 24/01/2004 for parts implemented early, and 01/10/2004 for rest Value for 2004-1 = 30% of (.25 -.50 x 23 / 365) =.066 Value for 2004-2 = 30% of (.75-23 / 365) + 70% of.125 =.294 Value for 2005-1 = 30% of (1.75-23 / 365) + 70% of.500 =.706 Value for 2005-2 and subsequent = prior +.500 Variable = Change in Trend re the 2004 Reforms for Other Sub-Coverages: Time 0 = 01/10/2004 Value for 2004-2 =.125 Value for 2005-1 =.500 Value for 2005-2 and subsequent = prior +.500 13

Variable = Change in Level at 01/03/2007: Time 0 = 01/03/2007 Value for 2007-1 =.667 Value for 2007-2 and subsequent = 1.000 2.3.2 Acceptance or Rejection of Independent Variables For each sub-coverage, I ran the general model based on tentative acceptance of various combinations of the independent variables (with rejection of the rest) until I found what I believe to be the optimal set of independent variables which should be accepted as being statistically significant. Recalling that the model treats claim frequency, claim severity, and claim cost per car year consistently, then I judge that if a dependent variable tests as being significant for any one of these three dependent variables, then it should be retained in the optimal set. Retention of an independent variable in the optimal set was generally governed by the following: retain the variable if a two-sided t-test indicates that it is statistically significant at the 5% level (i.e. 1 chance in 20 that the test would find the variable to be significant when it was in reality not) for at least one of claim frequency, claim severity, and claim cost per car year reject the variable if a two-sided t-test indicates that it is not statistically significant at the 10% level (i.e. 1 chance in 10 that the test would find the variable to be significant when it was in reality not) for all of claim frequency, claim severity, and claim cost per car year retain or reject the variable based on a judgment call if a two-sided t-test indicates that it is statistically significant at the 10% level (i.e. 1 chance in 10 that the test would find the variable to be significant when it was in reality not), but not at the 5% level (i.e. 1 chance in 20 that the test would find the variable to be significant when it was in reality not), for at least one of claim frequency, claim severity, and claim cost per car year 14

2.3.3 Summary of Findings re 2004 Reforms for Major Sub-Coverages Based on the criteria for acceptance or rejection in section 3.3.2 above, I find (see Exhibit 2) fitted values as follows for the two independent variables of most interest, for the major sub-coverages: Variable = Change in Level re 2004 Reforms: Change in Level re 2004 Reforms Sub-Coverage Decision Minimum* t-test % Frequency Change Severity Change Claim Cost Change TPL-BI Accept 0.000% -10.8% -33.5% -41.7% TPL-PD Reject N/A N/A N/A N/A AB-MR Accept 0.000% 32.2% -33.1% -11.5% AB-DI Accept 1.712% -15.0% -1.7% -16.5% * Minimum over claim frequency, claim severity, and claim cost per car year Variable = Change in Trend re 2004 Reforms: Change in Trend re 2004 Reforms Derived Forward Trend Sub-Coverage Decision Minimum* t-test % Frequency Trend Severity Trend Claim Cost Trend TPL-BI Reject N/A -3.8% 4.7% 0.7% TPL-PD Accept 0.170% 2.0% -0.3% 1.7% AB-MR Reject N/A -3.2% 5.3% 1.9% AB-DI Reject N/A -3.6% 1.4% -2.3% * Minimum over claim frequency, claim severity, and claim cost per car year In the above table, for coverages where this variable is rejected, the forward trends are based on the values of the remaining fitted trend variables only. 15

2.3.4 Summary of Findings re Change in Level at 01/03/2007 for Major Sub-Coverages Based on the criteria for acceptance or rejection in section 3.3.2 above, I find (see Exhibit 1) fitted values as follows for the Change in Level at 01/03/2007, for the major sub-coverages: Variable = Change in Level at 01/03/2007: Change in Level at 01/03/2007 Sub-Coverage Decision Minimum* t-test % Frequency Change Severity Change Claim Cost Change TPL-BI Reject N/A N/A N/A N/A TPL-PD Accept 0.000% 12.7% 11.4% 25.5% AB-MR Reject N/A N/A N/A N/A AB-DI Accept 0.000% -15.5% 37.8% 16.5% * Minimum over claim frequency, claim severity, and claim cost per car year 2.3.5 Forward Projections For each sub-coverage, based on the fitted parameters for the independent variables retained in the optimal set of independent variables, I projected claim frequency, claim severity, and claim cost per car year forward for each of the next 6 accident half years after the current one (2012-2), and I also used a similar process to trend the aggregate earned exposure forward to the same periods (see Exhibit 2). Values appropriate for the policy year starting 01/11/2013 were estimated by weighting these projections for the next 6 accident half years by weights proportional to the overlap of the earning pattern of this policy year with each of these accident half years, based on the assumption of 12 month policy terms. The accident half year weights in 1 / 72s used to get the policy year projections are as follows: Accident Half Year Weight for Policy Year starting 01/11/2013 2013-1 0 / 72 2013-2 2 / 72 2014-1 30 / 72 2014-2 62 / 72 2015-1 42 / 72 2015-2 8 / 72 Total 144 / 72 = 2 16

2.4 Payment Pattern I analyzed the paid claim amount experience included in the 2012-2 PPA LDE and selected age-toage paid claim amount development factors. As a default, the selected factors were taken as the average of the latest four such factors, except for the first, which was taken as the average of the latest two such factors for the same half year (because of seasonality). I then made a number of adjustments to these default factors, by judgment at the sub-coverage level, as follows: TPL-BI: in keeping with the approach taken for the incurred amount development factors, this cycle, instead of adopting the default factors, I selected factors here as the average of the latest six such factors, except for the first, which was taken as the average of the latest three such factors for the same half year (because of seasonality), and except that the 17 th factor for amounts was increased by about 2.3% to account for an expected lag in development post reform AB-DI: the 14 th factor was taken as the weighted average factor AB-SB: the factors were replaced by factors selected by judgment AB-UM: the factors were taken as weighted average factors, except for the first, taken as the weighted average such factors for the same half year In many cases, apparently spurious factors in the tail were ignored. Detailed supporting exhibits are not included in this report. I then converted the cumulative age-to-ultimate factors into corresponding payment patterns. Please see Exhibit 3 for a summary. 2.5 Fixed and Variable Expenses As noted above, the IBC Automobile Expense Survey was discontinued after the last cycle, and no new data is available. This cycle, I selected expense margins for the policy year starting 01/11/2013 as follows: Premium Tax Margin: 3.0% = statutory margin ( = weighted average value from 2011 AES) Commission (including Profit Commission) Margin: 12.4% = weighted average value for Private Passenger from 2011 AES = value used last cycle Fixed Expense Margin: 9.0% = weighted average of fixed expenses expressed as a percentage of earned premium from 2011 AES = value used last cycle, applied to the 2011 Accident Year earned premium and trended forward. 17

I therefore took the variable expense margin for required premiums for the policy year starting 01/11/2013 as 15.4% = sum of the margins for Premium Tax and Commission. I converted the 9.0% margin above into a basic coverage only $ amount per car year appropriate for the 2011 Calendar Year as follows, using 2011 premium and exposure numbers taken from the 2013 PPA LDE: 9.0% of the $560.26 Basic Coverage average earned premium for 2011 = $1,292,893,911 (2011 Basic Coverage Earned Premium) / 2,307,682 (2011 Earned Exposure for TPL) = 9.0% of $560.26 = $50.42 for the 2011 Calendar Year for basic coverage only I then trended the basic coverage 2011 calendar year $50.42 per vehicle amount forward by for 2 years and 10 months (average date-of-writing 01/07/2011 to average date-of-writing of 01/05/2014) at 2% per annum (estimate of Alberta CPI inflation) to a level appropriate to the policy year starting 01/11/2013 as follows: (34 / 12) $50.42 x 1.020 = $53.33 for the Policy Year starting 01/11/2013 for basic coverage only By using the all coverages 9.0% factor in my analysis above, I am implicitly splitting the total fixed amount expense per car pro rata between Basic Coverage (i.e. TPL and Accident Benefits), which is compulsory (at least up to the $200,000 minimum limit for TPL) and Optional Coverages (all the rest), which is a rather conservative approach - given that Fixed Expenses relate mainly to general overhead in connection with underwriting and issuing policies (and not to commission, premium tax, or claim adjustment expense costs, all of which are accounted for elsewhere), it may reasonably be argued that it is therefore appropriate to ascribe the lion s share of total fixed expenses to Basic Coverage, since the policy only has to be underwritten and issued once, regardless of whether or not it provides Basic Coverage only, with only a small residual portion of such expenses being ascribed to Optional Coverages, to the extent of additional marginal costs associated with underwriting these other coverages. 18

2.6 Alberta Health Levy I projected the $ amount of the Alberta Health Levy per car year appropriate to the Policy Year starting 01/11/2013, as follows: I selected a target amount for the levy for the 2014 calendar year of $105 million based on the recent history for the levy as shown in the 2012 AIRB Annual Report and elsewhere ($80, $85, $90, $90, $95, $100, and $100 million for 2007 to 2013 respectively) I converted this to an amount per car: $100,000,000 (2013 target) x 2/12 + $105,000,000 (2014 target) x 10/12 x 77% ( % PPAxF/ Total for TPL Prem) / [ ( 2,441,247 (2012 written exposure per LDE) x 1.035 (22 / 12) (PPAxF TPL exposure trend factor, trended for 22 months) ] = $30.85 I assume that on average the Health Levy is paid 8.5 months after the date of writing a policy. 2.7 Discounting for the Time Value of Money The time value of money is recognized by discounting my projected ultimate claim and other costs for the Policy Year starting 01/11/2013, based on the selected forward new money pre-tax investment rate re cash flow on underwriting coupled with my projected payment patterns. 2.7.1 Forward New Money Pre-Tax Investment Rate re Cash Flow on Underwriting In my opinion, an appropriate expected return on investment for cash flow from underwriting should not be greater than (and perhaps somewhat less than, since insurers need to retain some level of cash float) that which would be expected by investing cash flow from underwriting after front end expenses (i.e. the provision in the premium for claim costs) at current rates in risk-free Government of Canada bonds reasonably matched by duration to the claim liabilities. Since, for the compulsory coverages in total, the average time to claim payout (including the Health Levy) from time of writing the policy projected for the upcoming policy year is about 2.60 years, in my opinion, an appropriate value would be something like the weighted expected yield on 2 and 3 year Government of Canada Bonds in the near future. Although some insurers may choose to invest at least some of this cash flow in assets with higher expected yields and higher risk (either through higher expected default rates or duration mismatch), I do not believe that it is appropriate to make such alternative assumptions for the purposes of this review - in my view, if insurers choose to take on higher risk in their investments here, then they should reap the additional benefits when things go well, but should suffer the consequences negative consequences when things go poorly. 19

I therefore selected an investment rate for discounting purposes of 1.05%, which is slightly greater than the 40:60 weighting of the approximate current rate for 2 year (1.00%) and 3 year (1.05%) Government of Canada bonds. 2.7.2 Discounting Process All projected ultimate costs should be discounted to the average date of writing of policy for the Policy Year starting 01/11/2013. For claim costs by sub-coverage, discounting is accomplished by using the payment patterns in Exhibit 3 and the interest rate in section 3.7.1 above, assuming that payments occur on average at the mid point of each half year calendar period. For the Health Levy cost, I assume that amounts relating to a given calendar year are payable on March 15 of the subsequent calendar year, which leads to an average lag of 8.5 months to payment from date of writing. For the Fixed Expense cost, I assume that such amounts would on average be payable at the date of writing of the policy. Such discounted costs need then to be loaded for the estimated average lag between writing a policy and receiving the premium, assumed to be approximately 0.2 years. 2.8 Profit and Contingency Margin The Board s 10/04/2012 Notice to All Stakeholders announcing this year s annual adjustment process states in part: The profit provision will remain at 7% of premium for the 2013 industry-wide adjustment. Based on the above, for the purposes of this review process, I have adopted a 7.0% profit and contingency provision. 20

2.9 Average Street Premium The following table was derived from the data provided in the special ad hoc exhibit Alberta 2013 Ter FINAL.xls (2013 PEM) of exposure and premium data for recent policy effective months, which was prepared by IBC from accepted files of premium and exposure data submitted under the ASP up until late April 2013, and which was distributed to interested parties on 29/04/2013. Policy Effective Month TPL exposure re Principal Operators (car years) TPL+AB premium for both Principal Operators and Occasional Operators Average TPL + AB premium per car year 201201 165,729 91,421,500 551.63 201202 163,431 90,567,023 554.16 201203 203,586 112,685,231 553.50 201204 227,506 124,940,000 549.17 201205 227,886 126,656,563 555.79 201206 218,281 122,151,229 559.61 Sub-Total 1,206,419 668,421,546 554.05 201207 210,626 118,367,913 561.98 201208 218,119 125,266,672 574.31 201209 217,963 124,949,724 573.26 201210 224,841 127,648,620 567.73 201211 202,861 117,394,293 578.69 201212 162,513 94,572,496 581.94 Sub-Total 1,236,922 708,199,718 572.55 201301 174,194 101,338,268 581.76 201302 172,791 100,810,695 583.43 201303 196,995 111,484,968 565.93 Sub-Total 543,979 313,633,931 576.56 Review of the monthly average premiums (which reflect the effects of any shifts in proportion of business by grid versus non-grid, by insurer, by territory, and by other classification cells) in this table revealed the following: Average premiums were fairly stable over the first six months of 2012, at about $555, consistent with no significant rate change activity implemented in that time frame 21

Average premiums for November 2012 and subsequent generally show a modest increase over the corresponding values from the prior year, but not enough to reflect the full effect of the mandated +5.0% change in premium rates (which may be phased in over time) based on the Board s decision following last year s annual review, and this is consistent with the proportion of the industry which has so far implemented the increase in whole or in part - in this connection I also note a slight decrease in the proportion of vehicles on the grid in early 2013 compared to the prior year Based on the above, and noting a slight downward premium development (estimated at 1.0%) over the subsequent year in the data for the first three months of the year, and a slight seasonality factor for average premium over the year compared to average premium for the first 3 months (estimated at 1.2% in the absence of IWA rate changes), I selected my $591 estimate of the average street premium per car which should be expected to apply to the Policy Year starting 01/11/2013, before consideration of any changes which the Board may mandate to be effective at 01/11/2013, or any changes the Board may approve based on Section 6 filings to individual company rates subsequent to those fully reflected in the data at hand, as follows: $576.56 x.990 x 1.015 x 1.02 = ~ $591 where the 1.02 factor above reflects my assumption that there will be a further increase of some 2% by 01/11/2013, as most of the market which has not already taken the full 5% increase from last year s IWA chooses to do so in the light of deteriorating experience Based on review of the TPL versus AB data in the 2012 PEM exhibit, I further assessed the split of this $591 between TPL and AB as TPL = $546, and AB = $55. 3. High Level Summary of Findings 3.1 Required Rate Change Based on the analysis in this report (see Exhibit 1, Page 1 for more details), including the AIRB s mandated assumption of a 7% Profit Margin in the premium, we find as follows for Basic Coverage (i.e. Third Party Liability plus Accident Benefits) for the Alberta Private Passenger (excluding Farmers) all-industry class of business for the policy (rating) year starting November 1, 2013: Alberta Private Passenger (excluding Farmers) Automobile Insurance Basic Coverage = Third Party Liability + Accident Benefits Policy Year starting 01/11/2013 7.0% Profit Margin Indicated Required Average Premium per Car Year $670.82 Average Street Premium per Car Year (before annual adjustment and any interim individual company rate changes) $591.00 Indicated Required Rate Change 13.5% 22

Exhibit 1 - Required Premiums and Overall Rate Change for Basic Coverage 23

All-Industry Alberta Private Passenger (excluding Farmers) Automobile Insurance for Policy (Rating) Year 01/11/2012 to 31/10/2013 [Data valued at 31/12/2012] and Analysis at 1.05% per Annum Forward Insurance Operations Return on Investment Rate and AIRB 7.0% Profit and Contingency Margin Summary of Estimated Costs and Required Direct Premiums for the Bill 53 Product Exhibit 1 - Alberta PPAxF Projected Experience under Current Product - Page 1 Projected Estimated Resulting Estimated Estimated Required Required $ Required Projected Indicated Adequate 1.05%/annum Discounted Premium Variable Profit & Adequate Premium with Actual % Increase in $ Pure Discount $ Pure Delay Expense Contingency $ Direct Fixed Expense $ Earned $ Average Coverage Sub-Coverage Premium Factor Premium Factor % Margin % Margin Premium Redistributed Premium Premium [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] Bodily Injury 247.18 0.9538 235.76 1.0021 15.4 7.0 304.45 339.28 Health Levy 30.85 0.9926 30.62 1.0021 15.4 7.0 39.54 44.06 Property Damage 162.39 0.9901 160.78 1.0021 15.4 7.0 207.63 231.39 TPL Total 440.42 0.9699 427.16 1.0021 15.4 7.0 551.62 614.73 536.00 14.7 Funeral Benefit 0.55 0.9898 0.54 1.0021 15.4 7.0 0.70 0.78 Death Benefit 1.27 0.9887 1.26 1.0021 15.4 7.0 1.63 1.82 Medical/Rehab 27.97 0.9879 27.63 1.0021 15.4 7.0 35.68 39.76 Disablty Income 9.23 0.9855 9.10 1.0021 15.4 7.0 11.75 13.09 Supp Benefits 0.9872 1.0021 15.4 7.0 Uninsd Motorist 0.47 0.9389 0.44 1.0021 15.4 7.0 0.57 0.64 AB Total 39.49 0.9868 38.97 1.0021 15.4 7.0 50.33 56.09 55.00 2.0 Package Compulsory 479.91 0.9713 466.13 1.0021 15.4 7.0 601.95 670.82 591.00 13.5 Fixed Expense Total 53.33 1.0000 53.33 1.0021 15.4 7.0 68.87 Note: 1) Compulsory Package = TPL (average limits) + AB 2) Earned Premiums are Based on Estimates documented elsewhere Time: 11:14:17 a.m. May 28, 2013 25

Exhibit 2 - Trending Model and Forward Projections 27

Exhibit 2 - All-Industry Alberta PPAxF Accident Half Year Trend Analysis (Selected Model) - Page 1 Alberta Private Passenger Automobile (excluding Farmers) Valuation Date: 20121231 Data Basis: Direct All-Industry Calendar/Accident Year Data (incl. Facility Association) Coverage/KoL: Third Party Liability - Bodily Injury (KoL 01,02) Data Source: AIX All-Industry Loss Development Exhibit Item: Projected Experience for Policy Year starting 01/11/2013 Description: Historical Estimated and Future Projected All-Industry Ultimate Accident Half-Year Experience (excluding Health Levy but including ULAE), under various Products Historical Estimated Ultimate Statistics & Future Projected Ultimate Statistics Fitted Regression Estimates Independent Variables for Regression Acc. Car-Years Pro Rata # $ % $ $/Car $/Car % Car-Years % $ $/Car OldP/ 04-2P/ 07-1P/ 2nd Wthr OldP/ 04-2P/ Half Earned $ Earned Claim Claim Claim Claim Loss Earned Loss Earned Claim Claim Loss Prior Prior Prior Hlf Yr Cat Prior Prior Year Exposure Premium Count Amount Freqcy Severity Cost Premium Ratio Exposure Freqcy Severity Cost Level Level Level Level Level Trend Trend 19961 700,304 292,090,217 7,345 211,846,776 1.049 28,842 302.51 417.09 72.5 680,432 1.154 29,472 340.14 1.000 0.000 0.000 0.000 0.000 0.250 0.000 19962 714,960 307,261,819 8,304 243,267,545 1.161 29,295 340.25 429.76 79.2 705,793 1.202 32,217 387.39 1.000 0.000 0.000 1.000 1.000 0.750 0.000 19971 707,357 311,310,719 7,694 233,301,578 1.088 30,323 329.82 440.10 74.9 704,158 1.110 30,869 342.65 1.000 0.000 0.000 0.000 0.000 1.250 0.000 19972 729,706 335,984,422 8,275 263,817,173 1.134 31,881 361.54 460.44 78.5 730,403 1.156 33,744 390.25 1.000 0.000 0.000 1.000 0.000 1.750 0.000 19981 744,075 350,977,586 8,055 255,993,545 1.083 31,781 344.04 471.70 72.9 728,712 1.068 32,332 345.18 1.000 0.000 0.000 0.000 0.000 2.250 0.000 19982 753,632 362,001,433 9,073 306,851,098 1.204 33,820 407.16 480.34 84.8 755,872 1.112 35,344 393.13 1.000 0.000 0.000 1.000 1.000 2.750 0.000 19991 744,746 363,719,519 8,242 284,229,483 1.107 34,485 381.65 488.38 78.1 754,121 1.027 33,865 347.73 1.000 0.000 0.000 0.000 0.000 3.250 0.000 19992 761,320 371,319,221 8,729 321,026,589 1.147 36,777 421.67 487.73 86.5 782,228 1.070 37,019 396.03 1.000 0.000 0.000 1.000 0.000 3.750 0.000 20001 782,580 378,631,146 8,443 291,581,806 1.079 34,535 372.59 483.82 77.0 780,417 0.988 35,470 350.30 1.000 0.000 0.000 0.000 0.000 4.250 0.000 20002 810,796 394,102,785 8,863 331,786,518 1.093 37,435 409.21 486.07 84.2 809,504 1.029 38,774 398.96 1.000 0.000 0.000 1.000 1.000 4.750 0.000 20011 830,225 406,418,747 7,690 298,770,661 0.926 38,852 359.87 489.53 73.5 807,629 0.950 37,151 352.89 1.000 0.000 0.000 0.000 0.000 5.250 0.000 20012 851,902 444,723,539 8,396 350,914,397 0.986 41,795 411.92 522.04 78.9 837,731 0.990 40,612 401.90 1.000 0.000 0.000 1.000 0.000 5.750 0.000 20021 834,467 464,568,776 7,959 330,796,480 0.954 41,563 396.42 556.73 71.2 835,791 0.914 38,912 355.49 1.000 0.000 0.000 0.000 0.000 6.250 0.000 20022 869,888 524,948,434 7,986 363,078,244 0.918 45,464 417.39 603.47 69.2 866,942 0.952 42,537 404.87 1.000 0.000 0.000 1.000 0.000 6.750 0.000 20031 853,493 558,295,267 7,490 311,595,365 0.878 41,602 365.08 654.13 55.8 864,934 0.879 40,757 358.12 1.000 0.000 0.000 0.000 0.000 7.250 0.000 20032 874,538 622,600,141 7,082 319,190,575 0.810 45,071 364.98 711.92 51.3 897,172 0.915 44,554 407.86 1.000 0.000 0.000 1.000 0.000 7.750 0.000 20041 861,326 623,957,245 6,607 269,567,170 0.767 40,800 312.97 724.41 43.2 895,094 0.820 38,368 314.66 1.000 0.262 0.000 0.000 0.000 8.250 0.066 20042 888,616 598,607,462 6,853 259,451,079 0.771 37,859 291.97 673.64 43.3 928,455 0.817 35,811 292.69 1.000 0.650 0.000 1.000 1.000 8.750 0.294 20051 884,450 535,846,536 6,475 206,175,095 0.732 31,842 233.11 605.85 38.5 926,305 0.725 29,754 215.68 1.000 1.000 0.000 0.000 1.000 9.250 0.706 20052 939,957 557,631,312 7,482 235,073,710 0.796 31,419 250.09 593.25 42.2 960,830 0.755 32,525 245.63 1.000 1.000 0.000 1.000 0.000 9.750 1.206 20061 945,708 540,150,919 6,904 206,928,931 0.730 29,972 218.81 571.16 38.3 958,605 0.697 31,164 217.27 1.000 1.000 0.000 0.000 0.000 10.250 1.706 20062 1,001,688 561,384,498 7,702 265,344,395 0.769 34,451 264.90 560.44 47.3 994,333 0.726 34,067 247.45 1.000 1.000 0.000 1.000 1.000 10.750 2.206 20071 1,002,209 556,078,696 6,711 213,350,280 0.670 31,791 212.88 554.85 38.4 992,031 0.671 32,641 218.87 1.000 1.000 0.670 0.000 1.000 11.250 2.706 20072 1,056,654 579,792,317 7,080 272,342,835 0.670 38,467 257.74 548.71 47.0 1,029,005 0.699 35,682 249.27 1.000 1.000 1.000 1.000 1.000 11.750 3.206 20081 1,052,732 575,847,669 6,512 244,177,902 0.619 37,497 231.95 547.00 42.4 1,026,622 0.645 34,189 220.49 1.000 1.000 1.000 0.000 0.000 12.250 3.706 20082 1,097,641 596,639,947 6,810 291,853,473 0.620 42,857 265.89 543.57 48.9 1,064,885 0.672 37,373 251.11 1.000 1.000 1.000 1.000 1.000 12.750 4.206 20091 1,080,349 592,169,771 6,211 225,545,042 0.575 36,314 208.77 548.13 38.1 1,062,419 0.620 35,809 222.12 1.000 1.000 1.000 0.000 0.000 13.250 4.706 20092 1,119,600 619,378,776 7,025 286,894,891 0.627 40,839 256.25 553.21 46.3 1,102,017 0.646 39,145 252.97 1.000 1.000 1.000 1.000 1.000 13.750 5.206 20101 1,100,444 597,372,837 6,172 217,525,436 0.561 35,244 197.67 542.85 36.4 1,099,465 0.597 37,507 223.76 1.000 1.000 1.000 0.000 0.000 14.250 5.706 20102 1,147,413 606,683,872 7,454 301,592,867 0.650 40,461 262.85 528.74 49.7 1,140,444 0.622 41,001 254.84 1.000 1.000 1.000 1.000 1.000 14.750 6.206 20111 1,128,929 580,649,354 6,944 229,719,703 0.615 33,082 203.48 514.34 39.6 1,137,803 0.574 39,285 225.41 1.000 1.000 1.000 0.000 0.000 15.250 6.706 20112 1,178,753 592,645,006 7,152 308,527,679 0.607 43,139 261.74 502.77 52.1 1,180,210 0.598 42,944 256.72 1.000 1.000 1.000 1.000 1.000 15.750 7.206 20121 1,172,761 588,791,971 6,765 277,746,645 0.577 41,056 236.83 502.06 47.2 1,177,477 0.552 41,147 227.07 1.000 1.000 1.000 0.000 0.000 16.250 7.706 20122 1,224,852 620,144,884 7,393 287,066,250 0.604 38,829 234.37 506.30 46.3 1,221,363 0.575 44,980 258.61 1.000 1.000 1.000 1.000 1.000 16.750 8.206 20131 1,218,535 6,468 278,738,815 0.531 43,097 228.75 1,218,535 0.531 43,097 228.75 1.000 1.000 1.000 0.000 0.000 17.250 8.706 20132 1,263,951 6,990 329,289,191 0.553 47,112 260.52 1,263,951 0.553 47,112 260.52 1.000 1.000 1.000 1.000 0.650 17.750 9.206 20141 1,261,024 6,437 290,588,139 0.510 45,140 230.44 1,261,024 0.510 45,140 230.44 1.000 1.000 1.000 0.000 0.000 18.250 9.706 20142 1,308,024 6,957 343,287,436 0.532 49,345 262.45 1,308,024 0.532 49,345 262.45 1.000 1.000 1.000 1.000 0.650 18.750 10.206 20151 1,304,995 6,407 302,941,183 0.491 47,280 232.14 1,304,995 0.491 47,280 232.14 1.000 1.000 1.000 0.000 0.000 19.250 10.706 20152 1,353,634 6,924 357,880,754 0.512 51,684 264.39 1,353,634 0.512 51,684 264.39 1.000 1.000 1.000 1.000 0.650 19.750 11.206 PYWtd 2,598,541 13,374 642,314,157 0.515 48,027 247.18 Earned Car-Years of Exposure Beta Hat Parameter Estimates: 13.422 N/A N/A 0.019 N/A 0.034 N/A Ultimate Claim Frequency Beta Hat Parameter Estimates: 0.153-0.115 N/A 0.060 N/A -0.039 N/A Ultimate Claim Severity Beta Hat Parameter Estimates: 10.280-0.407 N/A 0.066 N/A 0.046 N/A Ultimate Claim Cost/Car-Year Beta Hat Parameter Estimates: 5.828-0.522 N/A 0.126 N/A 0.007 N/A Earned Car-Years of Exposure R*2 Statistic = 98.6%; T-Test Statistics on 31 Degrees of Freedom: 1,704.123 N/A N/A 2.713 N/A 46.883 N/A Ultimate Claim Frequency R*2 Statistic = 95.0%; T-Test Statistics on 30 Degrees of Freedom: 6.134-2.527 N/A 2.959 N/A -8.643 N/A Ultimate Claim Severity R*2 Statistic = 76.0%; T-Test Statistics on 30 Degrees of Freedom: 365.152-7.969 N/A 2.859 N/A 9.110 N/A Ultimate Claim Cost/Car-Year R*2 Statistic = 92.6%; T-Test Statistics on 30 Degrees of Freedom: 200.283-9.878 N/A 5.304 N/A 1.400 N/A Earned Car-Years of Exposure Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 1.080 N/A 0.000 N/A Ultimate Claim Frequency Two-Sided T-Test Tail Probability %: 0.000 1.701 N/A 0.598 N/A 0.000 N/A Ultimate Claim Severity Two-Sided T-Test Tail Probability %: 0.000 0.000 N/A 0.766 N/A 0.000 N/A Ultimate Claim Cost/Car-Year Two-Sided T-Test Tail Probability %: 0.000 0.000 N/A 0.001 N/A 17.177 N/A Earned Car-Years of Exposure Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 674,626.486 1.000 1.000 1.020 1.000 1.035 1.035 Ultimate Claim Frequency Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 1.165 0.892 1.000 1.062 1.000 0.962 0.962 Ultimate Claim Severity Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 29,132.398 0.665 1.000 1.068 1.000 1.047 1.047 Ultimate Claim Cost/Car-Year Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 339.516 0.593 1.000 1.135 1.000 1.007 1.007 Note: 1. Earned Exposure, Frequency, Severity, and Loss Cost are projected by Linear Regression on their Natural Logarithms 2. Regression Equation is: Ln Y = X x Beta + Epsilon, where X is matrix of independent variables, and Epsilon is distributed Normal (0, I x Sigma*2) 3. Independent Variables with Beta Hat and T Statistic and T Tail Probability = N/A have been judgmentally omitted from the Regression Time: 9:48:09 a.m. May 15, 2013 29

Exhibit 2 - All-Industry Alberta PPAxF Accident Half Year Trend Analysis (Selected Model) - Page 2 Alberta Private Passenger Automobile (excluding Farmers) Valuation Date: 20121231 Data Basis: Direct All-Industry Calendar/Accident Year Data (incl. Facility Association) Coverage/KoL: Third Party Liability - Property Damage (KoL 09) Data Source: AIX All-Industry Loss Development Exhibit Item: Projected Experience for Policy Year starting 01/11/2013 Description: Historical Estimated and Future Projected All-Industry Ultimate Accident Half-Year Experience (excluding Health Levy but including ULAE), under various Products Historical Estimated Ultimate Statistics & Future Projected Ultimate Statistics Fitted Regression Estimates Independent Variables for Regression Acc. Car-Years Pro Rata # $ % $ $/Car $/Car % Car-Years % $ $/Car OldP/ 04-2P/ 07-1P/ 2nd Wthr OldP/ 04-2P/ Half Earned $ Earned Claim Claim Claim Claim Loss Earned Loss Earned Claim Claim Loss Prior Prior Prior Hlf Yr Cat Prior Prior Year Exposure Premium Count Amount Freqcy Severity Cost Premium Ratio Exposure Freqcy Severity Cost Level Level Level Level Level Trend Trend 19961 700,304 292,090,217 23,398 55,826,286 3.341 2,386 79.72 417.09 19.1 680,432 3.269 2,427 79.33 1.000 0.000 0.000 0.000 0.000 0.250 0.000 19962 714,960 307,261,819 24,145 65,120,229 3.377 2,697 91.08 429.76 21.2 705,793 3.285 2,645 86.89 1.000 0.000 0.000 1.000 1.000 0.750 0.000 19971 707,357 311,310,719 22,772 60,660,373 3.219 2,664 85.76 440.10 19.5 704,158 3.173 2,585 82.03 1.000 0.000 0.000 0.000 0.000 1.250 0.000 19972 729,706 335,984,422 21,506 62,412,624 2.947 2,902 85.53 460.44 18.6 730,403 3.188 2,818 89.85 1.000 0.000 0.000 1.000 0.000 1.750 0.000 19981 744,075 350,977,586 23,054 61,895,118 3.098 2,685 83.18 471.70 17.6 728,712 3.080 2,754 84.82 1.000 0.000 0.000 0.000 0.000 2.250 0.000 19982 753,632 362,001,433 24,256 70,873,721 3.219 2,922 94.04 480.34 19.6 755,872 3.095 3,002 92.91 1.000 0.000 0.000 1.000 1.000 2.750 0.000 19991 744,746 363,719,519 21,755 62,976,744 2.921 2,895 84.56 488.38 17.3 754,121 2.989 2,934 87.71 1.000 0.000 0.000 0.000 0.000 3.250 0.000 19992 761,320 371,319,221 22,875 70,649,923 3.005 3,089 92.80 487.73 19.0 782,228 3.004 3,199 96.07 1.000 0.000 0.000 1.000 0.000 3.750 0.000 20001 782,580 378,631,146 23,818 72,952,735 3.044 3,063 93.22 483.82 19.3 780,417 2.901 3,126 90.70 1.000 0.000 0.000 0.000 0.000 4.250 0.000 20002 810,796 394,102,785 24,730 82,608,377 3.050 3,340 101.89 486.07 21.0 809,504 2.915 3,408 99.35 1.000 0.000 0.000 1.000 1.000 4.750 0.000 20011 830,225 406,418,747 21,967 71,344,721 2.646 3,248 85.93 489.53 17.6 807,629 2.816 3,330 93.79 1.000 0.000 0.000 0.000 0.000 5.250 0.000 20012 851,902 444,723,539 23,891 86,504,120 2.804 3,621 101.54 522.04 19.5 837,731 2.830 3,630 102.73 1.000 0.000 0.000 1.000 0.000 5.750 0.000 20021 834,467 464,568,776 24,233 90,695,215 2.904 3,743 108.69 556.73 19.5 835,791 2.733 3,548 96.99 1.000 0.000 0.000 0.000 0.000 6.250 0.000 20022 869,888 524,948,434 22,314 92,340,750 2.565 4,138 106.15 603.47 17.6 866,942 2.747 3,868 106.23 1.000 0.000 0.000 1.000 0.000 6.750 0.000 20031 853,493 558,295,267 21,592 87,316,973 2.530 4,044 102.31 654.13 15.6 864,934 2.653 3,780 100.29 1.000 0.000 0.000 0.000 0.000 7.250 0.000 20032 874,538 622,600,141 19,750 85,537,903 2.258 4,331 97.81 711.92 13.7 897,172 2.666 4,120 109.85 1.000 0.000 0.000 1.000 0.000 7.750 0.000 20041 861,326 623,957,245 20,362 80,898,238 2.364 3,973 93.92 724.41 13.0 895,094 2.575 4,027 103.71 1.000 0.000 0.000 0.000 0.000 8.250 0.000 20042 888,616 598,607,462 22,514 93,426,839 2.534 4,150 105.14 673.64 15.6 928,455 2.604 4,353 113.35 1.000 0.500 0.000 1.000 1.000 8.750 0.125 20051 884,450 535,846,536 22,504 91,145,169 2.544 4,050 103.05 605.85 17.0 926,305 2.562 4,151 106.33 1.000 1.000 0.000 0.000 1.000 9.250 0.500 20052 939,957 557,631,312 25,855 109,700,171 2.751 4,243 116.71 593.25 19.7 960,830 2.638 4,377 115.48 1.000 1.000 0.000 1.000 0.000 9.750 1.000 20061 945,708 540,150,919 26,431 106,755,105 2.795 4,039 112.88 571.16 19.8 958,605 2.612 4,139 108.10 1.000 1.000 0.000 0.000 0.000 10.250 1.500 20062 1,001,688 561,384,498 32,329 142,026,249 3.227 4,393 141.79 560.44 25.3 994,333 2.690 4,365 117.40 1.000 1.000 0.000 1.000 1.000 10.750 2.000 20071 1,002,209 556,078,696 30,657 137,851,712 3.059 4,497 137.55 554.85 24.8 992,031 2.884 4,437 127.96 1.000 1.000 0.670 0.000 1.000 11.250 2.500 20072 1,056,654 579,792,317 33,117 163,882,093 3.134 4,949 155.10 548.71 28.3 1,029,005 3.090 4,848 149.79 1.000 1.000 1.000 1.000 1.000 11.750 3.000 20081 1,052,732 575,847,669 32,880 154,100,510 3.123 4,687 146.38 547.00 26.8 1,026,622 3.059 4,584 140.22 1.000 1.000 1.000 0.000 0.000 12.250 3.500 20082 1,097,641 596,639,947 35,324 171,608,445 3.218 4,858 156.34 543.57 28.8 1,064,885 3.150 4,835 152.28 1.000 1.000 1.000 1.000 1.000 12.750 4.000 20091 1,080,349 592,169,771 34,426 153,588,738 3.187 4,461 142.17 548.13 25.9 1,062,419 3.118 4,571 142.55 1.000 1.000 1.000 0.000 0.000 13.250 4.500 20092 1,119,600 619,378,776 37,496 174,022,656 3.349 4,641 155.43 553.21 28.1 1,102,017 3.211 4,821 154.81 1.000 1.000 1.000 1.000 1.000 13.750 5.000 20101 1,100,444 597,372,837 32,679 146,053,226 2.970 4,469 132.72 542.85 24.4 1,099,465 3.179 4,558 144.91 1.000 1.000 1.000 0.000 0.000 14.250 5.500 20102 1,147,413 606,683,872 39,332 179,536,945 3.428 4,565 156.47 528.74 29.6 1,140,444 3.274 4,807 157.39 1.000 1.000 1.000 1.000 1.000 14.750 6.000 20111 1,128,929 580,649,354 40,082 178,572,834 3.550 4,455 158.18 514.34 30.8 1,137,803 3.241 4,546 147.32 1.000 1.000 1.000 0.000 0.000 15.250 6.500 20112 1,178,753 592,645,006 34,875 172,115,480 2.959 4,935 146.01 502.77 29.0 1,180,210 3.338 4,794 160.00 1.000 1.000 1.000 1.000 1.000 15.750 7.000 20121 1,172,761 588,791,971 34,445 162,823,598 2.937 4,727 138.84 502.06 27.7 1,177,477 3.304 4,533 149.77 1.000 1.000 1.000 0.000 0.000 16.250 7.500 20122 1,224,852 620,144,884 42,078 206,537,425 3.435 4,908 168.62 506.30 33.3 1,221,363 3.403 4,780 162.66 1.000 1.000 1.000 1.000 1.000 16.750 8.000 20131 1,218,535 41,050 185,533,177 3.369 4,520 152.26 1,218,535 3.369 4,520 152.26 1.000 1.000 1.000 0.000 0.000 17.250 8.500 20132 1,263,951 43,850 209,009,357 3.469 4,766 165.36 1,263,951 3.469 4,766 165.36 1.000 1.000 1.000 1.000 0.650 17.750 9.000 20141 1,261,024 43,310 195,193,043 3.434 4,507 154.79 1,261,024 3.434 4,507 154.79 1.000 1.000 1.000 0.000 0.000 18.250 9.500 20142 1,308,024 46,265 219,891,520 3.537 4,753 168.11 1,308,024 3.537 4,753 168.11 1.000 1.000 1.000 1.000 0.650 18.750 10.000 20151 1,304,995 45,694 205,355,854 3.501 4,494 157.36 1,304,995 3.501 4,494 157.36 1.000 1.000 1.000 0.000 0.000 19.250 10.500 20152 1,353,634 48,812 231,340,268 3.606 4,739 170.90 1,353,634 3.606 4,739 170.90 1.000 1.000 1.000 1.000 0.650 19.750 11.000 PYWtd 2,598,541 91,181 421,982,671 3.509 4,628 162.39 Earned Car-Years of Exposure Beta Hat Parameter Estimates: 13.422 N/A N/A 0.019 N/A 0.034 N/A Ultimate Claim Frequency Beta Hat Parameter Estimates: 1.192 N/A 0.119 0.020 N/A -0.030 0.049 Ultimate Claim Severity Beta Hat Parameter Estimates: 7.779 N/A 0.108 0.055 N/A 0.063-0.066 Ultimate Claim Cost/Car-Year Beta Hat Parameter Estimates: 4.365 N/A 0.227 0.074 N/A 0.033-0.017 Earned Car-Years of Exposure R*2 Statistic = 98.6%; T-Test Statistics on 31 Degrees of Freedom: 1,704.123 N/A N/A 2.713 N/A 46.883 N/A Ultimate Claim Frequency R*2 Statistic = 62.4%; T-Test Statistics on 29 Degrees of Freedom: 34.359 N/A 1.711 0.787 N/A -5.373 3.336 Ultimate Claim Severity R*2 Statistic = 97.7%; T-Test Statistics on 29 Degrees of Freedom: 465.672 N/A 3.217 4.516 N/A 23.699-9.327 Ultimate Claim Cost/Car-Year R*2 Statistic = 92.5%; T-Test Statistics on 29 Degrees of Freedom: 133.510 N/A 3.459 3.142 N/A 6.407-1.226 Earned Car-Years of Exposure Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 1.080 N/A 0.000 N/A Ultimate Claim Frequency Two-Sided T-Test Tail Probability %: 0.000 N/A 9.773 43.765 N/A 0.001 0.234 Ultimate Claim Severity Two-Sided T-Test Tail Probability %: 0.000 N/A 0.318 0.010 N/A 0.000 0.000 Ultimate Claim Cost/Car-Year Two-Sided T-Test Tail Probability %: 0.000 N/A 0.170 0.384 N/A 0.000 23.009 Earned Car-Years of Exposure Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 674,626.486 1.000 1.000 1.020 1.000 1.035 1.035 Ultimate Claim Frequency Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 3.293 1.000 1.127 1.020 1.000 0.971 1.020 Ultimate Claim Severity Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 2,388.745 1.000 1.114 1.056 1.000 1.065 0.997 Ultimate Claim Cost/Car-Year Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 78.665 1.000 1.255 1.077 1.000 1.034 1.017 Note: 1. Earned Exposure, Frequency, Severity, and Loss Cost are projected by Linear Regression on their Natural Logarithms 2. Regression Equation is: Ln Y = X x Beta + Epsilon, where X is matrix of independent variables, and Epsilon is distributed Normal (0, I x Sigma*2) 3. Independent Variables with Beta Hat and T Statistic and T Tail Probability = N/A have been judgmentally omitted from the Regression Time: 9:48:09 a.m. May 15, 2013 30

Exhibit 2 - All-Industry Alberta PPAxF Accident Half Year Trend Analysis (Selected Model) - Page 3 Alberta Private Passenger Automobile (excluding Farmers) Valuation Date: 20121231 Data Basis: Direct All-Industry Calendar/Accident Year Data (incl. Facility Association) Coverage/KoL: Accident Benefits - Funeral Benefit (KoL 30) Data Source: AIX All-Industry Loss Development Exhibit Item: Projected Experience for Policy Year starting 01/11/2013 Description: Historical Estimated and Future Projected All-Industry Ultimate Accident Half-Year Experience (excluding Health Levy but including ULAE), under various Products Historical Estimated Ultimate Statistics & Future Projected Ultimate Statistics Fitted Regression Estimates Independent Variables for Regression Acc. Car-Years Pro Rata # $ % $ $/Car $/Car % Car-Years % $ $/Car OldP/ 04-2P/ 07-1P/ 2nd Wthr OldP/ 04-2P/ Half Earned $ Earned Claim Claim Claim Claim Loss Earned Loss Earned Claim Claim Loss Prior Prior Prior Hlf Yr Cat Prior Prior Year Exposure Premium Count Amount Freqcy Severity Cost Premium Ratio Exposure Freqcy Severity Cost Level Level Level Level Level Trend Trend 19961 702,438 23,454,310 64 177,991 0.009 2,781 0.25 33.39 0.8 679,569 0.010 2,932 0.29 1.000 0.000 0.000 0.000 0.000 0.250 0.000 19962 716,995 28,781,304 110 323,476 0.015 2,941 0.45 40.14 1.1 705,434 0.013 2,982 0.38 1.000 0.000 0.000 1.000 1.000 0.750 0.000 19971 709,388 30,569,244 88 229,591 0.012 2,609 0.32 43.09 0.8 703,313 0.010 2,932 0.29 1.000 0.000 0.000 0.000 0.000 1.250 0.000 19972 732,097 33,698,955 107 297,902 0.015 2,784 0.41 46.03 0.9 730,081 0.013 2,982 0.38 1.000 0.000 0.000 1.000 0.000 1.750 0.000 19981 745,435 35,593,233 84 229,603 0.011 2,733 0.31 47.75 0.6 727,887 0.010 2,932 0.29 1.000 0.000 0.000 0.000 0.000 2.250 0.000 19982 753,625 36,570,499 98 268,463 0.013 2,739 0.36 48.53 0.7 755,590 0.013 2,982 0.38 1.000 0.000 0.000 1.000 1.000 2.750 0.000 19991 743,979 36,929,834 69 187,858 0.009 2,723 0.25 49.64 0.5 753,319 0.010 2,932 0.29 1.000 0.000 0.000 0.000 0.000 3.250 0.000 19992 760,146 37,546,087 75 223,154 0.010 2,975 0.29 49.39 0.6 781,990 0.013 2,982 0.38 1.000 0.000 0.000 1.000 0.000 3.750 0.000 20001 780,439 38,654,226 76 206,273 0.010 2,714 0.26 49.53 0.5 779,639 0.010 2,932 0.29 1.000 0.000 0.000 0.000 0.000 4.250 0.000 20002 807,484 40,543,620 115 353,305 0.014 3,072 0.44 50.21 0.9 809,313 0.013 2,982 0.38 1.000 0.000 0.000 1.000 1.000 4.750 0.000 20011 812,443 41,479,104 94 281,538 0.012 2,995 0.35 51.05 0.7 806,880 0.010 2,932 0.29 1.000 0.000 0.000 0.000 0.000 5.250 0.000 20012 844,102 44,727,646 93 288,507 0.011 3,102 0.34 52.99 0.6 837,590 0.013 2,982 0.38 1.000 0.000 0.000 1.000 0.000 5.750 0.000 20021 832,380 46,097,890 80 252,774 0.010 3,160 0.30 55.38 0.5 835,072 0.010 2,932 0.29 1.000 0.000 0.000 0.000 0.000 6.250 0.000 20022 869,522 49,952,888 85 271,671 0.010 3,196 0.31 57.45 0.5 866,855 0.013 2,982 0.38 1.000 0.000 0.000 1.000 0.000 6.750 0.000 20031 853,159 50,517,919 60 222,007 0.007 3,700 0.26 59.21 0.4 864,249 0.010 2,932 0.29 1.000 0.000 0.000 0.000 0.000 7.250 0.000 20032 875,870 54,589,148 128 615,472 0.015 4,808 0.70 62.33 1.1 897,143 0.013 2,982 0.38 1.000 0.000 0.000 1.000 0.000 7.750 0.000 20041 864,301 54,928,139 78 227,784 0.009 2,920 0.26 63.55 0.4 894,445 0.010 2,932 0.29 1.000 0.000 0.000 0.000 0.000 8.250 0.000 20042 893,636 55,456,343 115 300,414 0.013 2,612 0.34 62.06 0.5 928,488 0.013 2,982 0.38 1.000 0.500 0.000 1.000 1.000 8.750 0.125 20051 888,577 52,506,871 95 286,543 0.011 3,016 0.32 59.09 0.5 925,697 0.010 2,932 0.29 1.000 1.000 0.000 0.000 1.000 9.250 0.500 20052 941,650 53,913,225 129 393,110 0.014 3,047 0.42 57.25 0.7 960,929 0.013 2,982 0.38 1.000 1.000 0.000 1.000 0.000 9.750 1.000 20061 945,397 52,001,984 110 272,648 0.012 2,479 0.29 55.01 0.5 958,041 0.010 2,932 0.29 1.000 1.000 0.000 0.000 0.000 10.250 1.500 20062 1,000,816 54,290,492 117 312,820 0.012 2,674 0.31 54.25 0.6 994,504 0.013 2,982 0.38 1.000 1.000 0.000 1.000 1.000 10.750 2.000 20071 1,001,481 54,239,291 93 434,251 0.009 4,669 0.43 54.16 0.8 991,514 0.008 4,954 0.41 1.000 1.000 0.670 0.000 1.000 11.250 2.500 20072 1,056,479 56,744,348 130 698,210 0.012 5,371 0.66 53.71 1.2 1,029,252 0.010 6,523 0.63 1.000 1.000 1.000 1.000 1.000 11.750 3.000 20081 1,053,298 56,211,621 98 512,210 0.009 5,227 0.49 53.37 0.9 1,026,157 0.007 6,414 0.48 1.000 1.000 1.000 0.000 0.000 12.250 3.500 20082 1,098,212 58,435,948 122 807,911 0.011 6,622 0.74 53.21 1.4 1,065,213 0.010 6,523 0.63 1.000 1.000 1.000 1.000 1.000 12.750 4.000 20091 1,080,743 58,722,935 83 543,212 0.008 6,545 0.50 54.34 0.9 1,062,011 0.007 6,414 0.48 1.000 1.000 1.000 0.000 0.000 13.250 4.500 20092 1,119,991 61,978,670 99 625,370 0.009 6,317 0.56 55.34 1.0 1,102,431 0.010 6,523 0.63 1.000 1.000 1.000 1.000 1.000 13.750 5.000 20101 1,100,667 60,035,766 75 726,497 0.007 9,687 0.66 54.54 1.2 1,099,117 0.007 6,414 0.48 1.000 1.000 1.000 0.000 0.000 14.250 5.500 20102 1,147,571 61,221,644 116 788,420 0.010 6,797 0.69 53.35 1.3 1,140,950 0.010 6,523 0.63 1.000 1.000 1.000 1.000 1.000 14.750 6.000 20111 1,128,672 58,812,870 59 353,650 0.005 5,994 0.31 52.11 0.6 1,137,520 0.007 6,414 0.48 1.000 1.000 1.000 0.000 0.000 15.250 6.500 20112 1,178,746 60,786,682 106 689,417 0.009 6,504 0.58 51.57 1.1 1,180,814 0.010 6,523 0.63 1.000 1.000 1.000 1.000 1.000 15.750 7.000 20121 1,173,155 60,478,972 90 642,502 0.008 7,139 0.55 51.55 1.1 1,177,264 0.007 6,414 0.48 1.000 1.000 1.000 0.000 0.000 16.250 7.500 20122 1,225,881 64,557,619 98 605,600 0.008 6,180 0.49 52.66 0.9 1,222,072 0.010 6,523 0.63 1.000 1.000 1.000 1.000 1.000 16.750 8.000 20131 1,218,398 91 585,239 0.007 6,414 0.48 1,218,398 0.007 6,414 0.48 1.000 1.000 1.000 0.000 0.000 17.250 8.500 20132 1,264,770 122 793,169 0.010 6,523 0.63 1,264,770 0.010 6,523 0.63 1.000 1.000 1.000 1.000 0.650 17.750 9.000 20141 1,260,968 94 605,687 0.007 6,414 0.48 1,260,968 0.007 6,414 0.48 1.000 1.000 1.000 0.000 0.000 18.250 9.500 20142 1,308,961 126 820,882 0.010 6,523 0.63 1,308,961 0.010 6,523 0.63 1.000 1.000 1.000 1.000 0.650 18.750 10.000 20151 1,305,026 98 626,849 0.007 6,414 0.48 1,305,026 0.007 6,414 0.48 1.000 1.000 1.000 0.000 0.000 19.250 10.500 20152 1,354,696 130 849,563 0.010 6,523 0.63 1,354,696 0.010 6,523 0.63 1.000 1.000 1.000 1.000 0.650 19.750 11.000 PYWtd 2,599,483 223 1,441,331 0.009 6,476 0.55 Earned Car-Years of Exposure Beta Hat Parameter Estimates: 13.421 N/A N/A 0.020 N/A 0.034 N/A Ultimate Claim Frequency Beta Hat Parameter Estimates: -4.610 N/A -0.284 0.250 N/A N/A N/A Ultimate Claim Severity Beta Hat Parameter Estimates: 7.984 N/A 0.783 0.017 N/A N/A N/A Ultimate Claim Cost/Car-Year Beta Hat Parameter Estimates: -1.232 N/A 0.499 0.267 N/A N/A N/A Earned Car-Years of Exposure R*2 Statistic = 98.8%; T-Test Statistics on 31 Degrees of Freedom: 1,819.175 N/A N/A 3.004 N/A 50.152 N/A Ultimate Claim Frequency R*2 Statistic = 56.7%; T-Test Statistics on 31 Degrees of Freedom: -102.698 N/A -4.689 4.407 N/A N/A N/A Ultimate Claim Severity R*2 Statistic = 87.1%; T-Test Statistics on 31 Degrees of Freedom: 199.185 N/A 14.468 0.331 N/A N/A N/A Ultimate Claim Cost/Car-Year R*2 Statistic = 68.3%; T-Test Statistics on 31 Degrees of Freedom: -23.432 N/A 7.026 4.016 N/A N/A N/A Earned Car-Years of Exposure Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 0.523 N/A 0.000 N/A Ultimate Claim Frequency Two-Sided T-Test Tail Probability %: 0.000 N/A 0.005 0.012 N/A N/A N/A Ultimate Claim Severity Two-Sided T-Test Tail Probability %: 0.000 N/A 0.000 74.294 N/A N/A N/A Ultimate Claim Cost/Car-Year Two-Sided T-Test Tail Probability %: 0.000 N/A 0.000 0.035 N/A N/A N/A Earned Car-Years of Exposure Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 673,759.549 1.000 1.000 1.020 1.000 1.035 1.035 Ultimate Claim Frequency Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 0.010 1.000 0.753 1.284 1.000 1.000 1.000 Ultimate Claim Severity Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 2,932.426 1.000 2.187 1.017 1.000 1.000 1.000 Ultimate Claim Cost/Car-Year Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 0.292 1.000 1.646 1.306 1.000 1.000 1.000 Note: 1. Earned Exposure, Frequency, Severity, and Loss Cost are projected by Linear Regression on their Natural Logarithms 2. Regression Equation is: Ln Y = X x Beta + Epsilon, where X is matrix of independent variables, and Epsilon is distributed Normal (0, I x Sigma*2) 3. Independent Variables with Beta Hat and T Statistic and T Tail Probability = N/A have been judgmentally omitted from the Regression Time: 9:48:09 a.m. May 15, 2013 31

Exhibit 2 - All-Industry Alberta PPAxF Accident Half Year Trend Analysis (Selected Model) - Page 4 Alberta Private Passenger Automobile (excluding Farmers) Valuation Date: 20121231 Data Basis: Direct All-Industry Calendar/Accident Year Data (incl. Facility Association) Coverage/KoL: Accident Benefits - Death Benefit (KoL 32) Data Source: AIX All-Industry Loss Development Exhibit Item: Projected Experience for Policy Year starting 01/11/2013 Description: Historical Estimated and Future Projected All-Industry Ultimate Accident Half-Year Experience (excluding Health Levy but including ULAE), under various Products Historical Estimated Ultimate Statistics & Future Projected Ultimate Statistics Fitted Regression Estimates Independent Variables for Regression Acc. Car-Years Pro Rata # $ % $ $/Car $/Car % Car-Years % $ $/Car OldP/ 04-2P/ 07-1P/ 2nd Wthr OldP/ 04-2P/ Half Earned $ Earned Claim Claim Claim Claim Loss Earned Loss Earned Claim Claim Loss Prior Prior Prior Hlf Yr Cat Prior Prior Year Exposure Premium Count Amount Freqcy Severity Cost Premium Ratio Exposure Freqcy Severity Cost Level Level Level Level Level Trend Trend 19961 702,438 23,454,310 43 1,041,946 0.006 24,231 1.48 33.39 4.4 679,569 0.008 19,092 1.59 1.000 0.000 0.000 0.000 0.000 0.250 0.000 19962 716,995 28,781,304 65 1,417,805 0.009 21,812 1.98 40.14 4.9 705,434 0.011 20,028 2.12 1.000 0.000 0.000 1.000 1.000 0.750 0.000 19971 709,388 30,569,244 49 943,377 0.007 19,253 1.33 43.09 3.1 703,313 0.008 19,488 1.56 1.000 0.000 0.000 0.000 0.000 1.250 0.000 19972 732,097 33,698,955 82 1,588,430 0.011 19,371 2.17 46.03 4.7 730,081 0.010 20,443 2.07 1.000 0.000 0.000 1.000 0.000 1.750 0.000 19981 745,435 35,593,233 58 994,892 0.008 17,153 1.33 47.75 2.8 727,887 0.008 19,892 1.53 1.000 0.000 0.000 0.000 0.000 2.250 0.000 19982 753,625 36,570,499 73 1,449,694 0.010 19,859 1.92 48.53 4.0 755,590 0.010 20,867 2.03 1.000 0.000 0.000 1.000 1.000 2.750 0.000 19991 743,979 36,929,834 53 891,417 0.007 16,819 1.20 49.64 2.4 753,319 0.007 20,304 1.50 1.000 0.000 0.000 0.000 0.000 3.250 0.000 19992 760,146 37,546,087 59 1,410,397 0.008 23,905 1.86 49.39 3.8 781,990 0.009 21,300 1.99 1.000 0.000 0.000 1.000 0.000 3.750 0.000 20001 780,439 38,654,226 55 1,333,799 0.007 24,251 1.71 49.53 3.5 779,639 0.007 20,725 1.47 1.000 0.000 0.000 0.000 0.000 4.250 0.000 20002 807,484 40,543,620 85 2,118,608 0.011 24,925 2.62 50.21 5.2 809,313 0.009 21,741 1.95 1.000 0.000 0.000 1.000 1.000 4.750 0.000 20011 812,443 41,479,104 61 1,814,233 0.008 29,742 2.23 51.05 4.4 806,880 0.007 21,154 1.44 1.000 0.000 0.000 0.000 0.000 5.250 0.000 20012 844,102 44,727,646 74 1,115,464 0.009 15,074 1.32 52.99 2.5 837,590 0.009 22,192 1.91 1.000 0.000 0.000 1.000 0.000 5.750 0.000 20021 832,380 46,097,890 66 1,308,826 0.008 19,831 1.57 55.38 2.8 835,072 0.007 21,593 1.41 1.000 0.000 0.000 0.000 0.000 6.250 0.000 20022 869,522 49,952,888 64 1,550,099 0.007 24,220 1.78 57.45 3.1 866,855 0.008 22,652 1.87 1.000 0.000 0.000 1.000 0.000 6.750 0.000 20031 853,159 50,517,919 61 1,193,887 0.007 19,572 1.40 59.21 2.4 864,249 0.006 22,041 1.38 1.000 0.000 0.000 0.000 0.000 7.250 0.000 20032 875,870 54,589,148 81 1,576,440 0.009 19,462 1.80 62.33 2.9 897,143 0.008 23,121 1.83 1.000 0.000 0.000 1.000 0.000 7.750 0.000 20041 864,301 54,928,139 51 1,017,063 0.006 19,942 1.18 63.55 1.9 894,445 0.006 22,497 1.35 1.000 0.000 0.000 0.000 0.000 8.250 0.000 20042 893,636 55,456,343 71 2,063,308 0.008 29,061 2.31 62.06 3.7 928,488 0.008 23,601 1.79 1.000 0.500 0.000 1.000 1.000 8.750 0.125 20051 888,577 52,506,871 64 1,424,913 0.007 22,264 1.60 59.09 2.7 925,697 0.006 22,964 1.32 1.000 1.000 0.000 0.000 1.000 9.250 0.500 20052 941,650 53,913,225 77 2,327,182 0.008 30,223 2.47 57.25 4.3 960,929 0.007 24,090 1.75 1.000 1.000 0.000 1.000 0.000 9.750 1.000 20061 945,397 52,001,984 62 1,780,749 0.007 28,722 1.88 55.01 3.4 958,041 0.006 23,440 1.29 1.000 1.000 0.000 0.000 0.000 10.250 1.500 20062 1,000,816 54,290,492 72 1,261,635 0.007 17,523 1.26 54.25 2.3 994,504 0.007 24,589 1.72 1.000 1.000 0.000 1.000 1.000 10.750 2.000 20071 1,001,481 54,239,291 62 1,114,864 0.006 17,982 1.11 54.16 2.1 991,514 0.005 23,926 1.27 1.000 1.000 0.670 0.000 1.000 11.250 2.500 20072 1,056,479 56,744,348 83 1,741,965 0.008 20,988 1.65 53.71 3.1 1,029,252 0.007 25,099 1.68 1.000 1.000 1.000 1.000 1.000 11.750 3.000 20081 1,053,298 56,211,621 57 1,328,464 0.005 23,306 1.26 53.37 2.4 1,026,157 0.005 24,422 1.24 1.000 1.000 1.000 0.000 0.000 12.250 3.500 20082 1,098,212 58,435,948 79 2,016,833 0.007 25,530 1.84 53.21 3.5 1,065,213 0.006 25,619 1.65 1.000 1.000 1.000 1.000 1.000 12.750 4.000 20091 1,080,743 58,722,935 46 923,742 0.004 20,081 0.85 54.34 1.6 1,062,011 0.005 24,928 1.22 1.000 1.000 1.000 0.000 0.000 13.250 4.500 20092 1,119,991 61,978,670 57 2,099,889 0.005 36,840 1.87 55.34 3.4 1,102,431 0.006 26,150 1.62 1.000 1.000 1.000 1.000 1.000 13.750 5.000 20101 1,100,667 60,035,766 39 964,278 0.004 24,725 0.88 54.54 1.6 1,099,117 0.005 25,445 1.19 1.000 1.000 1.000 0.000 0.000 14.250 5.500 20102 1,147,571 61,221,644 72 1,696,908 0.006 23,568 1.48 53.35 2.8 1,140,950 0.006 26,693 1.58 1.000 1.000 1.000 1.000 1.000 14.750 6.000 20111 1,128,672 58,812,870 34 1,503,682 0.003 44,226 1.33 52.11 2.6 1,137,520 0.004 25,972 1.17 1.000 1.000 1.000 0.000 0.000 15.250 6.500 20112 1,178,746 60,786,682 60 1,583,716 0.005 26,395 1.34 51.57 2.6 1,180,814 0.006 27,246 1.55 1.000 1.000 1.000 1.000 1.000 15.750 7.000 20121 1,173,155 60,478,972 66 1,446,141 0.006 21,911 1.23 51.55 2.4 1,177,264 0.004 26,510 1.14 1.000 1.000 1.000 0.000 0.000 16.250 7.500 20122 1,225,881 64,557,619 55 1,791,277 0.004 32,569 1.46 52.66 2.8 1,222,072 0.005 27,811 1.52 1.000 1.000 1.000 1.000 1.000 16.750 8.000 20131 1,218,398 50 1,363,826 0.004 27,060 1.12 1,218,398 0.004 27,060 1.12 1.000 1.000 1.000 0.000 0.000 17.250 8.500 20132 1,264,770 66 1,880,064 0.005 28,387 1.49 1,264,770 0.005 28,387 1.49 1.000 1.000 1.000 1.000 0.650 17.750 9.000 20141 1,260,968 50 1,382,497 0.004 27,621 1.10 1,260,968 0.004 27,621 1.10 1.000 1.000 1.000 0.000 0.000 18.250 9.500 20142 1,308,961 66 1,905,802 0.005 28,976 1.46 1,308,961 0.005 28,976 1.46 1.000 1.000 1.000 1.000 0.650 18.750 10.000 20151 1,305,026 50 1,401,422 0.004 28,194 1.07 1,305,026 0.004 28,194 1.07 1.000 1.000 1.000 0.000 0.000 19.250 10.500 20152 1,354,696 65 1,931,891 0.005 29,576 1.43 1,354,696 0.005 29,576 1.43 1.000 1.000 1.000 1.000 0.650 19.750 11.000 PYWtd 2,599,483 116 3,301,522 0.004 28,563 1.27 Earned Car-Years of Exposure Beta Hat Parameter Estimates: 13.421 N/A N/A 0.020 N/A 0.034 N/A Ultimate Claim Frequency Beta Hat Parameter Estimates: -4.776 N/A N/A 0.256 N/A -0.041 N/A Ultimate Claim Severity Beta Hat Parameter Estimates: 9.852 N/A N/A 0.038 N/A 0.021 N/A Ultimate Claim Cost/Car-Year Beta Hat Parameter Estimates: 0.471 N/A N/A 0.294 N/A -0.021 N/A Earned Car-Years of Exposure R*2 Statistic = 98.8%; T-Test Statistics on 31 Degrees of Freedom: 1,819.175 N/A N/A 3.004 N/A 50.152 N/A Ultimate Claim Frequency R*2 Statistic = 67.5%; T-Test Statistics on 31 Degrees of Freedom: -74.441 N/A N/A 4.389 N/A -6.929 N/A Ultimate Claim Severity R*2 Statistic = 20.4%; T-Test Statistics on 31 Degrees of Freedom: 122.354 N/A N/A 0.513 N/A 2.745 N/A Ultimate Claim Cost/Car-Year R*2 Statistic = 43.1%; T-Test Statistics on 31 Degrees of Freedom: 5.948 N/A N/A 4.081 N/A -2.825 N/A Earned Car-Years of Exposure Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 0.523 N/A 0.000 N/A Ultimate Claim Frequency Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 0.012 N/A 0.000 N/A Ultimate Claim Severity Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 61.155 N/A 0.997 N/A Ultimate Claim Cost/Car-Year Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 0.029 N/A 0.820 N/A Earned Car-Years of Exposure Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 673,759.549 1.000 1.000 1.020 1.000 1.035 1.035 Ultimate Claim Frequency Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 0.008 1.000 1.000 1.292 1.000 0.960 0.960 Ultimate Claim Severity Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 18,994.174 1.000 1.000 1.038 1.000 1.021 1.021 Ultimate Claim Cost/Car-Year Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 1.601 1.000 1.000 1.342 1.000 0.979 0.979 Note: 1. Earned Exposure, Frequency, Severity, and Loss Cost are projected by Linear Regression on their Natural Logarithms 2. Regression Equation is: Ln Y = X x Beta + Epsilon, where X is matrix of independent variables, and Epsilon is distributed Normal (0, I x Sigma*2) 3. Independent Variables with Beta Hat and T Statistic and T Tail Probability = N/A have been judgmentally omitted from the Regression Time: 9:48:09 a.m. May 15, 2013 32

Exhibit 2 - All-Industry Alberta PPAxF Accident Half Year Trend Analysis (Selected Model) - Page 5 Alberta Private Passenger Automobile (excluding Farmers) Valuation Date: 20121231 Data Basis: Direct All-Industry Calendar/Accident Year Data (incl. Facility Association) Coverage/KoL: Accident Benefits - Medical/Rehabilitation (KoL 31) Data Source: AIX All-Industry Loss Development Exhibit Item: Projected Experience for Policy Year starting 01/11/2013 Description: Historical Estimated and Future Projected All-Industry Ultimate Accident Half-Year Experience (excluding Health Levy but including ULAE), under various Products Historical Estimated Ultimate Statistics & Future Projected Ultimate Statistics Fitted Regression Estimates Independent Variables for Regression Acc. Car-Years Pro Rata # $ % $ $/Car $/Car % Car-Years % $ $/Car OldP/ 04-2P/ 07-1P/ 2nd Wthr OldP/ 04-2P/ Half Earned $ Earned Claim Claim Claim Claim Loss Earned Loss Earned Claim Claim Loss Prior Prior Prior Hlf Yr Cat Prior Prior Year Exposure Premium Count Amount Freqcy Severity Cost Premium Ratio Exposure Freqcy Severity Cost Level Level Level Level Level Trend Trend 19961 702,438 23,454,310 6,806 12,941,116 0.969 1,901 18.42 33.39 55.2 679,569 1.086 1,919 20.84 1.000 0.000 0.000 0.000 0.000 0.250 0.000 19962 716,995 28,781,304 7,790 17,758,684 1.086 2,280 24.77 40.14 61.7 705,434 1.142 2,093 23.90 1.000 0.000 0.000 1.000 1.000 0.750 0.000 19971 709,388 30,569,244 7,431 15,261,943 1.048 2,054 21.51 43.09 49.9 703,313 1.051 2,021 21.24 1.000 0.000 0.000 0.000 0.000 1.250 0.000 19972 732,097 33,698,955 7,920 16,313,752 1.082 2,060 22.28 46.03 48.4 730,081 1.105 2,204 24.36 1.000 0.000 0.000 1.000 0.000 1.750 0.000 19981 745,435 35,593,233 7,678 15,358,268 1.030 2,000 20.60 47.75 43.1 727,887 1.017 2,128 21.64 1.000 0.000 0.000 0.000 0.000 2.250 0.000 19982 753,625 36,570,499 8,774 17,717,136 1.164 2,019 23.51 48.53 48.4 755,590 1.069 2,321 24.82 1.000 0.000 0.000 1.000 1.000 2.750 0.000 19991 743,979 36,929,834 7,925 17,113,997 1.065 2,159 23.00 49.64 46.3 753,319 0.984 2,241 22.05 1.000 0.000 0.000 0.000 0.000 3.250 0.000 19992 760,146 37,546,087 8,606 19,560,187 1.132 2,273 25.73 49.39 52.1 781,990 1.035 2,445 25.29 1.000 0.000 0.000 1.000 0.000 3.750 0.000 20001 780,439 38,654,226 8,046 19,003,666 1.031 2,362 24.35 49.53 49.2 779,639 0.952 2,360 22.47 1.000 0.000 0.000 0.000 0.000 4.250 0.000 20002 807,484 40,543,620 8,426 22,151,272 1.043 2,629 27.43 50.21 54.6 809,313 1.001 2,574 25.77 1.000 0.000 0.000 1.000 1.000 4.750 0.000 20011 812,443 41,479,104 7,545 18,964,744 0.929 2,514 23.34 51.05 45.7 806,880 0.921 2,485 22.90 1.000 0.000 0.000 0.000 0.000 5.250 0.000 20012 844,102 44,727,646 8,614 23,737,719 1.020 2,756 28.12 52.99 53.1 837,590 0.969 2,711 26.26 1.000 0.000 0.000 1.000 0.000 5.750 0.000 20021 832,380 46,097,890 8,204 22,390,144 0.986 2,729 26.90 55.38 48.6 835,072 0.892 2,617 23.33 1.000 0.000 0.000 0.000 0.000 6.250 0.000 20022 869,522 49,952,888 7,909 24,654,689 0.910 3,117 28.35 57.45 49.4 866,855 0.938 2,855 26.76 1.000 0.000 0.000 1.000 0.000 6.750 0.000 20031 853,159 50,517,919 6,908 20,852,036 0.810 3,019 24.44 59.21 41.3 864,249 0.863 2,756 23.78 1.000 0.000 0.000 0.000 0.000 7.250 0.000 20032 875,870 54,589,148 6,869 21,166,129 0.784 3,081 24.17 62.33 38.8 897,143 0.907 3,006 27.27 1.000 0.000 0.000 1.000 0.000 7.750 0.000 20041 864,301 54,928,139 6,659 18,656,545 0.770 2,802 21.59 63.55 34.0 894,445 0.835 2,902 24.23 1.000 0.000 0.000 0.000 0.000 8.250 0.000 20042 893,636 55,456,343 8,322 22,736,141 0.931 2,732 25.44 62.06 41.0 928,488 1.009 2,590 26.14 1.000 0.500 0.000 1.000 1.000 8.750 0.125 20051 888,577 52,506,871 8,940 21,318,556 1.006 2,385 23.99 59.09 40.6 925,697 1.068 2,045 21.84 1.000 1.000 0.000 0.000 1.000 9.250 0.500 20052 941,650 53,913,225 10,453 24,373,413 1.110 2,332 25.88 57.25 45.2 960,929 1.123 2,231 25.05 1.000 1.000 0.000 1.000 0.000 9.750 1.000 20061 945,397 52,001,984 10,177 20,139,831 1.076 1,979 21.30 55.01 38.7 958,041 1.033 2,154 22.26 1.000 1.000 0.000 0.000 0.000 10.250 1.500 20062 1,000,816 54,290,492 11,496 26,681,760 1.149 2,321 26.66 54.25 49.1 994,504 1.086 2,350 25.53 1.000 1.000 0.000 1.000 1.000 10.750 2.000 20071 1,001,481 54,239,291 10,467 22,102,708 1.045 2,112 22.07 54.16 40.8 991,514 1.000 2,268 22.68 1.000 1.000 0.670 0.000 1.000 11.250 2.500 20072 1,056,479 56,744,348 11,328 26,416,850 1.072 2,332 25.00 53.71 46.6 1,029,252 1.051 2,474 26.01 1.000 1.000 1.000 1.000 1.000 11.750 3.000 20081 1,053,298 56,211,621 10,157 23,767,690 0.964 2,340 22.57 53.37 42.3 1,026,157 0.968 2,389 23.11 1.000 1.000 1.000 0.000 0.000 12.250 3.500 20082 1,098,212 58,435,948 10,422 29,936,966 0.949 2,872 27.26 53.21 51.2 1,065,213 1.017 2,606 26.51 1.000 1.000 1.000 1.000 1.000 12.750 4.000 20091 1,080,743 58,722,935 9,442 24,603,947 0.874 2,606 22.77 54.34 41.9 1,062,011 0.936 2,515 23.55 1.000 1.000 1.000 0.000 0.000 13.250 4.500 20092 1,119,991 61,978,670 10,693 30,673,103 0.955 2,869 27.39 55.34 49.5 1,102,431 0.984 2,744 27.01 1.000 1.000 1.000 1.000 1.000 13.750 5.000 20101 1,100,667 60,035,766 9,259 26,086,373 0.841 2,817 23.70 54.54 43.5 1,099,117 0.906 2,649 24.00 1.000 1.000 1.000 0.000 0.000 14.250 5.500 20102 1,147,571 61,221,644 11,171 31,970,378 0.973 2,862 27.86 53.35 52.2 1,140,950 0.953 2,889 27.53 1.000 1.000 1.000 1.000 1.000 14.750 6.000 20111 1,128,672 58,812,870 10,759 28,718,407 0.953 2,669 25.44 52.11 48.8 1,137,520 0.877 2,789 24.46 1.000 1.000 1.000 0.000 0.000 15.250 6.500 20112 1,178,746 60,786,682 10,682 32,333,345 0.906 3,027 27.43 51.57 53.2 1,180,814 0.922 3,043 28.05 1.000 1.000 1.000 1.000 1.000 15.750 7.000 20121 1,173,155 60,478,972 10,144 28,412,030 0.865 2,801 24.22 51.55 47.0 1,177,264 0.848 2,937 24.92 1.000 1.000 1.000 0.000 0.000 16.250 7.500 20122 1,225,881 64,557,619 11,966 34,396,075 0.976 2,874 28.06 52.66 53.3 1,222,072 0.892 3,204 28.58 1.000 1.000 1.000 1.000 1.000 16.750 8.000 20131 1,218,398 10,002 30,941,113 0.821 3,093 25.39 1,218,398 0.821 3,093 25.39 1.000 1.000 1.000 0.000 0.000 17.250 8.500 20132 1,264,770 10,917 36,838,079 0.863 3,374 29.13 1,264,770 0.863 3,374 29.13 1.000 1.000 1.000 1.000 0.650 17.750 9.000 20141 1,260,968 10,017 32,631,459 0.794 3,258 25.88 1,260,968 0.794 3,258 25.88 1.000 1.000 1.000 0.000 0.000 18.250 9.500 20142 1,308,961 10,933 38,850,582 0.835 3,553 29.68 1,308,961 0.835 3,553 29.68 1.000 1.000 1.000 1.000 0.650 18.750 10.000 20151 1,305,026 10,032 34,414,150 0.769 3,430 26.37 1,305,026 0.769 3,430 26.37 1.000 1.000 1.000 0.000 0.000 19.250 10.500 20152 1,354,696 10,950 40,973,031 0.808 3,742 30.25 1,354,696 0.808 3,742 30.25 1.000 1.000 1.000 1.000 0.650 19.750 11.000 PYWtd 2,599,483 20,961 72,701,869 0.806 3,468 27.97 Earned Car-Years of Exposure Beta Hat Parameter Estimates: 13.421 N/A N/A 0.020 N/A 0.034 N/A Ultimate Claim Frequency Beta Hat Parameter Estimates: 0.091 0.279 N/A 0.067 N/A -0.033 N/A Ultimate Claim Severity Beta Hat Parameter Estimates: 7.547-0.402 N/A 0.061 N/A 0.052 N/A Ultimate Claim Cost/Car-Year Beta Hat Parameter Estimates: 3.032-0.123 N/A 0.128 N/A 0.019 N/A Earned Car-Years of Exposure R*2 Statistic = 98.8%; T-Test Statistics on 31 Degrees of Freedom: 1,819.175 N/A N/A 3.004 N/A 50.152 N/A Ultimate Claim Frequency R*2 Statistic = 62.1%; T-Test Statistics on 30 Degrees of Freedom: 3.143 5.585 N/A 2.829 N/A -6.551 N/A Ultimate Claim Severity R*2 Statistic = 80.2%; T-Test Statistics on 30 Degrees of Freedom: 262.245-8.065 N/A 2.602 N/A 10.337 N/A Ultimate Claim Cost/Car-Year R*2 Statistic = 65.5%; T-Test Statistics on 30 Degrees of Freedom: 112.608-2.634 N/A 5.812 N/A 4.027 N/A Earned Car-Years of Exposure Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 0.523 N/A 0.000 N/A Ultimate Claim Frequency Two-Sided T-Test Tail Probability %: 0.375 0.000 N/A 0.825 N/A 0.000 N/A Ultimate Claim Severity Two-Sided T-Test Tail Probability %: 0.000 0.000 N/A 1.426 N/A 0.000 N/A Ultimate Claim Cost/Car-Year Two-Sided T-Test Tail Probability %: 0.000 1.322 N/A 0.000 N/A 0.035 N/A Earned Car-Years of Exposure Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 673,759.549 1.000 1.000 1.020 1.000 1.035 1.035 Ultimate Claim Frequency Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 1.095 1.322 1.000 1.069 1.000 0.968 0.968 Ultimate Claim Severity Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 1,894.332 0.669 1.000 1.063 1.000 1.053 1.053 Ultimate Claim Cost/Car-Year Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 20.742 0.885 1.000 1.136 1.000 1.019 1.019 Note: 1. Earned Exposure, Frequency, Severity, and Loss Cost are projected by Linear Regression on their Natural Logarithms 2. Regression Equation is: Ln Y = X x Beta + Epsilon, where X is matrix of independent variables, and Epsilon is distributed Normal (0, I x Sigma*2) 3. Independent Variables with Beta Hat and T Statistic and T Tail Probability = N/A have been judgmentally omitted from the Regression Time: 9:48:09 a.m. May 15, 2013 33

Exhibit 2 - All-Industry Alberta PPAxF Accident Half Year Trend Analysis (Selected Model) - Page 6 Alberta Private Passenger Automobile (excluding Farmers) Valuation Date: 20121231 Data Basis: Direct All-Industry Calendar/Accident Year Data (incl. Facility Association) Coverage/KoL: Accident Benefits - Disability Income (KoL 34) Data Source: AIX All-Industry Loss Development Exhibit Item: Projected Experience for Policy Year starting 01/11/2013 Description: Historical Estimated and Future Projected All-Industry Ultimate Accident Half-Year Experience (excluding Health Levy but including ULAE), under various Products Historical Estimated Ultimate Statistics & Future Projected Ultimate Statistics Fitted Regression Estimates Independent Variables for Regression Acc. Car-Years Pro Rata # $ % $ $/Car $/Car % Car-Years % $ $/Car OldP/ 04-2P/ 07-1P/ 2nd Wthr OldP/ 04-2P/ Half Earned $ Earned Claim Claim Claim Claim Loss Earned Loss Earned Claim Claim Loss Prior Prior Prior Hlf Yr Cat Prior Prior Year Exposure Premium Count Amount Freqcy Severity Cost Premium Ratio Exposure Freqcy Severity Cost Level Level Level Level Level Trend Trend 19961 702,438 23,454,310 1,549 8,064,657 0.221 5,206 11.48 33.39 34.4 679,569 0.265 4,971 13.17 1.000 0.000 0.000 0.000 0.000 0.250 0.000 19962 716,995 28,781,304 1,845 10,296,175 0.257 5,581 14.36 40.14 35.8 705,434 0.291 5,488 15.98 1.000 0.000 0.000 1.000 1.000 0.750 0.000 19971 709,388 30,569,244 1,598 8,175,132 0.225 5,116 11.52 43.09 26.7 703,313 0.255 5,039 12.86 1.000 0.000 0.000 0.000 0.000 1.250 0.000 19972 732,097 33,698,955 1,986 10,959,815 0.271 5,519 14.97 46.03 32.5 730,081 0.281 5,562 15.60 1.000 0.000 0.000 1.000 0.000 1.750 0.000 19981 745,435 35,593,233 1,868 9,807,624 0.251 5,250 13.16 47.75 27.6 727,887 0.246 5,107 12.56 1.000 0.000 0.000 0.000 0.000 2.250 0.000 19982 753,625 36,570,499 2,125 10,496,021 0.282 4,939 13.93 48.53 28.7 755,590 0.270 5,638 15.24 1.000 0.000 0.000 1.000 1.000 2.750 0.000 19991 743,979 36,929,834 1,862 9,947,599 0.250 5,342 13.37 49.64 26.9 753,319 0.237 5,177 12.27 1.000 0.000 0.000 0.000 0.000 3.250 0.000 19992 760,146 37,546,087 2,169 12,305,215 0.285 5,673 16.19 49.39 32.8 781,990 0.260 5,715 14.89 1.000 0.000 0.000 1.000 0.000 3.750 0.000 20001 780,439 38,654,226 2,063 9,932,971 0.264 4,815 12.73 49.53 25.7 779,639 0.228 5,248 11.99 1.000 0.000 0.000 0.000 0.000 4.250 0.000 20002 807,484 40,543,620 2,271 13,869,174 0.281 6,107 17.18 50.21 34.2 809,313 0.251 5,793 14.54 1.000 0.000 0.000 1.000 1.000 4.750 0.000 20011 812,443 41,479,104 1,874 9,852,806 0.231 5,258 12.13 51.05 23.8 806,880 0.220 5,319 11.71 1.000 0.000 0.000 0.000 0.000 5.250 0.000 20012 844,102 44,727,646 2,192 12,865,108 0.260 5,869 15.24 52.99 28.8 837,590 0.242 5,872 14.20 1.000 0.000 0.000 1.000 0.000 5.750 0.000 20021 832,380 46,097,890 2,055 12,071,010 0.247 5,874 14.50 55.38 26.2 835,072 0.212 5,392 11.43 1.000 0.000 0.000 0.000 0.000 6.250 0.000 20022 869,522 49,952,888 2,120 12,699,943 0.244 5,991 14.61 57.45 25.4 866,855 0.233 5,952 13.87 1.000 0.000 0.000 1.000 0.000 6.750 0.000 20031 853,159 50,517,919 1,663 9,122,688 0.195 5,486 10.69 59.21 18.1 864,249 0.204 5,465 11.17 1.000 0.000 0.000 0.000 0.000 7.250 0.000 20032 875,870 54,589,148 1,694 10,100,606 0.193 5,963 11.53 62.33 18.5 897,143 0.225 6,034 13.55 1.000 0.000 0.000 1.000 0.000 7.750 0.000 20041 864,301 54,928,139 1,611 8,295,977 0.186 5,150 9.60 63.55 15.1 894,445 0.197 5,540 10.91 1.000 0.000 0.000 0.000 0.000 8.250 0.000 20042 893,636 55,456,343 1,566 10,390,686 0.175 6,635 11.63 62.06 18.7 928,488 0.199 6,064 12.10 1.000 0.500 0.000 1.000 1.000 8.750 0.125 20051 888,577 52,506,871 1,440 8,174,932 0.162 5,677 9.20 59.09 15.6 925,697 0.161 5,520 8.90 1.000 1.000 0.000 0.000 1.000 9.250 0.500 20052 941,650 53,913,225 1,743 10,037,677 0.185 5,759 10.66 57.25 18.6 960,929 0.177 6,094 10.80 1.000 1.000 0.000 1.000 0.000 9.750 1.000 20061 945,397 52,001,984 1,444 8,117,072 0.153 5,621 8.59 55.01 15.6 958,041 0.155 5,595 8.69 1.000 1.000 0.000 0.000 0.000 10.250 1.500 20062 1,000,816 54,290,492 1,703 10,518,681 0.170 6,177 10.51 54.25 19.4 994,504 0.171 6,177 10.55 1.000 1.000 0.000 1.000 1.000 10.750 2.000 20071 1,001,481 54,239,291 1,495 9,863,264 0.149 6,598 9.85 54.16 18.2 991,514 0.134 7,031 9.40 1.000 1.000 0.670 0.000 1.000 11.250 2.500 20072 1,056,479 56,744,348 1,642 12,993,126 0.155 7,913 12.30 53.71 22.9 1,029,252 0.139 8,628 12.00 1.000 1.000 1.000 1.000 1.000 11.750 3.000 20081 1,053,298 56,211,621 1,440 10,452,039 0.137 7,258 9.92 53.37 18.6 1,026,157 0.122 7,922 9.66 1.000 1.000 1.000 0.000 0.000 12.250 3.500 20082 1,098,212 58,435,948 1,537 14,460,315 0.140 9,408 13.17 53.21 24.7 1,065,213 0.134 8,745 11.72 1.000 1.000 1.000 1.000 1.000 12.750 4.000 20091 1,080,743 58,722,935 1,246 11,253,099 0.115 9,031 10.41 54.34 19.2 1,062,011 0.118 8,030 9.44 1.000 1.000 1.000 0.000 0.000 13.250 4.500 20092 1,119,991 61,978,670 1,434 13,302,387 0.128 9,276 11.88 55.34 21.5 1,102,431 0.129 8,865 11.45 1.000 1.000 1.000 1.000 1.000 13.750 5.000 20101 1,100,667 60,035,766 1,119 8,927,683 0.102 7,978 8.11 54.54 14.9 1,099,117 0.113 8,140 9.22 1.000 1.000 1.000 0.000 0.000 14.250 5.500 20102 1,147,571 61,221,644 1,332 12,940,328 0.116 9,715 11.28 53.35 21.1 1,140,950 0.124 8,986 11.18 1.000 1.000 1.000 1.000 1.000 14.750 6.000 20111 1,128,672 58,812,870 1,172 9,217,469 0.104 7,865 8.17 52.11 15.7 1,137,520 0.109 8,251 9.00 1.000 1.000 1.000 0.000 0.000 15.250 6.500 20112 1,178,746 60,786,682 1,318 12,126,290 0.112 9,201 10.29 51.57 19.9 1,180,814 0.120 9,108 10.92 1.000 1.000 1.000 1.000 1.000 15.750 7.000 20121 1,173,155 60,478,972 1,181 10,176,184 0.101 8,617 8.67 51.55 16.8 1,177,264 0.105 8,363 8.79 1.000 1.000 1.000 0.000 0.000 16.250 7.500 20122 1,225,881 64,557,619 1,454 12,524,349 0.119 8,614 10.22 52.66 19.4 1,222,072 0.116 9,233 10.67 1.000 1.000 1.000 1.000 1.000 16.750 8.000 20131 1,218,398 1,234 10,465,018 0.101 8,477 8.59 1,218,398 0.101 8,477 8.59 1.000 1.000 1.000 0.000 0.000 17.250 8.500 20132 1,264,770 1,408 13,179,809 0.111 9,359 10.42 1,264,770 0.111 9,359 10.42 1.000 1.000 1.000 1.000 0.650 17.750 9.000 20141 1,260,968 1,231 10,578,934 0.098 8,593 8.39 1,260,968 0.098 8,593 8.39 1.000 1.000 1.000 0.000 0.000 18.250 9.500 20142 1,308,961 1,404 13,323,277 0.107 9,486 10.18 1,308,961 0.107 9,486 10.18 1.000 1.000 1.000 1.000 0.650 18.750 10.000 20151 1,305,026 1,228 10,694,090 0.094 8,710 8.19 1,305,026 0.094 8,710 8.19 1.000 1.000 1.000 0.000 0.000 19.250 10.500 20152 1,354,696 1,401 13,468,306 0.103 9,616 9.94 1,354,696 0.103 9,616 9.94 1.000 1.000 1.000 1.000 0.650 19.750 11.000 PYWtd 2,599,483 2,633 23,981,515 0.101 9,107 9.23 Earned Car-Years of Exposure Beta Hat Parameter Estimates: 13.421 N/A N/A 0.020 N/A 0.034 N/A Ultimate Claim Frequency Beta Hat Parameter Estimates: -1.319-0.163-0.168 0.113 N/A -0.037 N/A Ultimate Claim Severity Beta Hat Parameter Estimates: 8.508-0.017 0.321 0.092 N/A 0.014 N/A Ultimate Claim Cost/Car-Year Beta Hat Parameter Estimates: 2.584-0.180 0.153 0.205 N/A -0.024 N/A Earned Car-Years of Exposure R*2 Statistic = 98.8%; T-Test Statistics on 31 Degrees of Freedom: 1,819.175 N/A N/A 3.004 N/A 50.152 N/A Ultimate Claim Frequency R*2 Statistic = 93.3%; T-Test Statistics on 29 Degrees of Freedom: -30.166-2.348-2.653 3.479 N/A -4.567 N/A Ultimate Claim Severity R*2 Statistic = 92.9%; T-Test Statistics on 29 Degrees of Freedom: 295.103-0.375 7.680 4.305 N/A 2.532 N/A Ultimate Claim Cost/Car-Year R*2 Statistic = 78.9%; T-Test Statistics on 29 Degrees of Freedom: 57.578-2.529 2.349 6.157 N/A -2.823 N/A Earned Car-Years of Exposure Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 0.523 N/A 0.000 N/A Ultimate Claim Frequency Two-Sided T-Test Tail Probability %: 0.000 2.590 1.281 0.161 N/A 0.008 N/A Ultimate Claim Severity Two-Sided T-Test Tail Probability %: 0.000 71.042 0.000 0.017 N/A 1.700 N/A Ultimate Claim Cost/Car-Year Two-Sided T-Test Tail Probability %: 0.000 1.712 2.583 0.000 N/A 0.850 N/A Earned Car-Years of Exposure Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 673,759.549 1.000 1.000 1.020 1.000 1.035 1.035 Ultimate Claim Frequency Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 0.267 0.850 0.845 1.120 1.000 0.964 0.964 Ultimate Claim Severity Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 4,953.977 0.983 1.378 1.096 1.000 1.014 1.014 Ultimate Claim Cost/Car-Year Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 13.245 0.835 1.165 1.228 1.000 0.977 0.977 Note: 1. Earned Exposure, Frequency, Severity, and Loss Cost are projected by Linear Regression on their Natural Logarithms 2. Regression Equation is: Ln Y = X x Beta + Epsilon, where X is matrix of independent variables, and Epsilon is distributed Normal (0, I x Sigma*2) 3. Independent Variables with Beta Hat and T Statistic and T Tail Probability = N/A have been judgmentally omitted from the Regression Time: 9:48:09 a.m. May 15, 2013 34

Exhibit 2 - All-Industry Alberta PPAxF Accident Half Year Trend Analysis (Selected Model) - Page 7 Alberta Private Passenger Automobile (excluding Farmers) Valuation Date: 20121231 Data Basis: Direct All-Industry Calendar/Accident Year Data (incl. Facility Association) Coverage/KoL: Accident Benefits - Supplementary Benefits (KoL 37) Data Source: AIX All-Industry Loss Development Exhibit Item: Projected Experience for Policy Year starting 01/11/2013 Description: Historical Estimated and Future Projected All-Industry Ultimate Accident Half-Year Experience (excluding Health Levy but including ULAE), under various Products Historical Estimated Ultimate Statistics & Future Projected Ultimate Statistics Fitted Regression Estimates Independent Variables for Regression Acc. Car-Years Pro Rata # $ % $ $/Car $/Car % Car-Years % $ $/Car OldP/ 04-2P/ 07-1P/ 2nd Wthr OldP/ 04-2P/ Half Earned $ Earned Claim Claim Claim Claim Loss Earned Loss Earned Claim Claim Loss Prior Prior Prior Hlf Yr Cat Prior Prior Year Exposure Premium Count Amount Freqcy Severity Cost Premium Ratio Exposure Freqcy Severity Cost Level Level Level Level Level Trend Trend 19961 702,438 23,454,310 4 11,939 0.001 2,985 0.02 33.39 0.1 679,569 0.000 460 0.00 1.000 0.000 0.000 0.000 0.000 0.250 0.000 19962 716,995 28,781,304 0 0 0.000 0 0.00 40.14 0.0 705,434 0.000 460 0.00 1.000 0.000 0.000 1.000 1.000 0.750 0.000 19971 709,388 30,569,244 0 1,393 0.000 0 0.00 43.09 0.0 703,313 0.000 460 0.00 1.000 0.000 0.000 0.000 0.000 1.250 0.000 19972 732,097 33,698,955 3 29,592 0.000 9,864 0.04 46.03 0.1 730,081 0.000 460 0.00 1.000 0.000 0.000 1.000 0.000 1.750 0.000 19981 745,435 35,593,233 7 304,337 0.001 43,477 0.41 47.75 0.9 727,887 0.000 460 0.00 1.000 0.000 0.000 0.000 0.000 2.250 0.000 19982 753,625 36,570,499 0 3,438 0.000 0 0.00 48.53 0.0 755,590 0.000 460 0.00 1.000 0.000 0.000 1.000 1.000 2.750 0.000 19991 743,979 36,929,834 0 0 0.000 0 0.00 49.64 0.0 753,319 0.000 460 0.00 1.000 0.000 0.000 0.000 0.000 3.250 0.000 19992 760,146 37,546,087 0 0 0.000 0 0.00 49.39 0.0 781,990 0.000 460 0.00 1.000 0.000 0.000 1.000 0.000 3.750 0.000 20001 780,439 38,654,226 2 1,137 0.000 569 0.00 49.53 0.0 779,639 0.000 460 0.00 1.000 0.000 0.000 0.000 0.000 4.250 0.000 20002 807,484 40,543,620 0 630 0.000 0 0.00 50.21 0.0 809,313 0.000 460 0.00 1.000 0.000 0.000 1.000 1.000 4.750 0.000 20011 812,443 41,479,104 1 645 0.000 645 0.00 51.05 0.0 806,880 0.000 460 0.00 1.000 0.000 0.000 0.000 0.000 5.250 0.000 20012 844,102 44,727,646 0 0 0.000 0 0.00 52.99 0.0 837,590 0.000 460 0.00 1.000 0.000 0.000 1.000 0.000 5.750 0.000 20021 832,380 46,097,890 0 0 0.000 0 0.00 55.38 0.0 835,072 0.000 460 0.00 1.000 0.000 0.000 0.000 0.000 6.250 0.000 20022 869,522 49,952,888 1 204 0.000 204 0.00 57.45 0.0 866,855 0.000 460 0.00 1.000 0.000 0.000 1.000 0.000 6.750 0.000 20031 853,159 50,517,919 0 109 0.000 0 0.00 59.21 0.0 864,249 0.000 460 0.00 1.000 0.000 0.000 0.000 0.000 7.250 0.000 20032 875,870 54,589,148 0 0 0.000 0 0.00 62.33 0.0 897,143 0.000 460 0.00 1.000 0.000 0.000 1.000 0.000 7.750 0.000 20041 864,301 54,928,139 0 0 0.000 0 0.00 63.55 0.0 894,445 0.000 460 0.00 1.000 0.000 0.000 0.000 0.000 8.250 0.000 20042 893,636 55,456,343 0 0 0.000 0 0.00 62.06 0.0 928,488 0.000 460 0.00 1.000 0.500 0.000 1.000 1.000 8.750 0.125 20051 888,577 52,506,871 0 0 0.000 0 0.00 59.09 0.0 925,697 0.000 460 0.00 1.000 1.000 0.000 0.000 1.000 9.250 0.500 20052 941,650 53,913,225 0 0 0.000 0 0.00 57.25 0.0 960,929 0.000 460 0.00 1.000 1.000 0.000 1.000 0.000 9.750 1.000 20061 945,397 52,001,984 0 0 0.000 0 0.00 55.01 0.0 958,041 0.000 460 0.00 1.000 1.000 0.000 0.000 0.000 10.250 1.500 20062 1,000,816 54,290,492 0 1,909 0.000 0 0.00 54.25 0.0 994,504 0.000 460 0.00 1.000 1.000 0.000 1.000 1.000 10.750 2.000 20071 1,001,481 54,239,291 0 1,045 0.000 0 0.00 54.16 0.0 991,514 0.000 460 0.00 1.000 1.000 0.670 0.000 1.000 11.250 2.500 20072 1,056,479 56,744,348 0 0 0.000 0 0.00 53.71 0.0 1,029,252 0.000 460 0.00 1.000 1.000 1.000 1.000 1.000 11.750 3.000 20081 1,053,298 56,211,621 0 0 0.000 0 0.00 53.37 0.0 1,026,157 0.000 460 0.00 1.000 1.000 1.000 0.000 0.000 12.250 3.500 20082 1,098,212 58,435,948 0 3 0.000 0 0.00 53.21 0.0 1,065,213 0.000 460 0.00 1.000 1.000 1.000 1.000 1.000 12.750 4.000 20091 1,080,743 58,722,935 0 0 0.000 0 0.00 54.34 0.0 1,062,011 0.000 460 0.00 1.000 1.000 1.000 0.000 0.000 13.250 4.500 20092 1,119,991 61,978,670 1 28,894 0.000 28,894 0.03 55.34 0.0 1,102,431 0.000 460 0.00 1.000 1.000 1.000 1.000 1.000 13.750 5.000 20101 1,100,667 60,035,766 2 14,459 0.000 7,230 0.01 54.54 0.0 1,099,117 0.000 460 0.00 1.000 1.000 1.000 0.000 0.000 14.250 5.500 20102 1,147,571 61,221,644 0 161 0.000 0 0.00 53.35 0.0 1,140,950 0.000 460 0.00 1.000 1.000 1.000 1.000 1.000 14.750 6.000 20111 1,128,672 58,812,870 0 0 0.000 0 0.00 52.11 0.0 1,137,520 0.000 460 0.00 1.000 1.000 1.000 0.000 0.000 15.250 6.500 20112 1,178,746 60,786,682 1 981 0.000 981 0.00 51.57 0.0 1,180,814 0.000 460 0.00 1.000 1.000 1.000 1.000 1.000 15.750 7.000 20121 1,173,155 60,478,972 1 6,430 0.000 6,430 0.01 51.55 0.0 1,177,264 0.000 460 0.00 1.000 1.000 1.000 0.000 0.000 16.250 7.500 20122 1,225,881 64,557,619 0 112 0.000 0 0.00 52.66 0.0 1,222,072 0.000 460 0.00 1.000 1.000 1.000 1.000 1.000 16.750 8.000 20131 1,218,398 2 756 0.000 460 0.00 1,218,398 0.000 460 0.00 1.000 1.000 1.000 0.000 0.000 17.250 8.500 20132 1,264,770 2 785 0.000 460 0.00 1,264,770 0.000 460 0.00 1.000 1.000 1.000 1.000 0.650 17.750 9.000 20141 1,260,968 2 783 0.000 460 0.00 1,260,968 0.000 460 0.00 1.000 1.000 1.000 0.000 0.000 18.250 9.500 20142 1,308,961 2 813 0.000 460 0.00 1,308,961 0.000 460 0.00 1.000 1.000 1.000 1.000 0.650 18.750 10.000 20151 1,305,026 2 810 0.000 460 0.00 1,305,026 0.000 460 0.00 1.000 1.000 1.000 0.000 0.000 19.250 10.500 20152 1,354,696 2 841 0.000 460 0.00 1,354,696 0.000 460 0.00 1.000 1.000 1.000 1.000 0.650 19.750 11.000 PYWtd 2,599,483 4 1,614 0.000 460 0.00 Earned Car-Years of Exposure Beta Hat Parameter Estimates: 13.421 N/A N/A 0.020 N/A 0.034 N/A Ultimate Claim Frequency Beta Hat Parameter Estimates: -8.911 N/A N/A N/A N/A N/A N/A Ultimate Claim Severity Beta Hat Parameter Estimates: 6.131 N/A N/A N/A N/A N/A N/A Ultimate Claim Cost/Car-Year Beta Hat Parameter Estimates: -7.385 N/A N/A N/A N/A N/A N/A Earned Car-Years of Exposure R*2 Statistic = 98.8%; T-Test Statistics on 31 Degrees of Freedom: 1,819.175 N/A N/A 3.004 N/A 50.152 N/A Ultimate Claim Frequency R*2 Statistic = 0.0%; T-Test Statistics on 33 Degrees of Freedom: -100.529 N/A N/A N/A N/A N/A N/A Ultimate Claim Severity R*2 Statistic = 0.0%; T-Test Statistics on 33 Degrees of Freedom: 22.606 N/A N/A N/A N/A N/A N/A Ultimate Claim Cost/Car-Year R*2 Statistic = 0.0%; T-Test Statistics on 33 Degrees of Freedom: -22.304 N/A N/A N/A N/A N/A N/A Earned Car-Years of Exposure Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 0.523 N/A 0.000 N/A Ultimate Claim Frequency Two-Sided T-Test Tail Probability %: 0.000 N/A N/A N/A N/A N/A N/A Ultimate Claim Severity Two-Sided T-Test Tail Probability %: 0.000 N/A N/A N/A N/A N/A N/A Ultimate Claim Cost/Car-Year Two-Sided T-Test Tail Probability %: 0.000 N/A N/A N/A N/A N/A N/A Earned Car-Years of Exposure Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 673,759.549 1.000 1.000 1.020 1.000 1.035 1.035 Ultimate Claim Frequency Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 0.000 1.000 1.000 1.000 1.000 1.000 1.000 Ultimate Claim Severity Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 459.947 1.000 1.000 1.000 1.000 1.000 1.000 Ultimate Claim Cost/Car-Year Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 0.001 1.000 1.000 1.000 1.000 1.000 1.000 Note: 1. Earned Exposure, Frequency, Severity, and Loss Cost are projected by Linear Regression on their Natural Logarithms 2. Regression Equation is: Ln Y = X x Beta + Epsilon, where X is matrix of independent variables, and Epsilon is distributed Normal (0, I x Sigma*2) 3. Independent Variables with Beta Hat and T Statistic and T Tail Probability = N/A have been judgmentally omitted from the Regression Time: 9:48:09 a.m. May 15, 2013 35

Exhibit 2 - All-Industry Alberta PPAxF Accident Half Year Trend Analysis (Selected Model) - Page 8 Alberta Private Passenger Automobile (excluding Farmers) Valuation Date: 20121231 Data Basis: Direct All-Industry Calendar/Accident Year Data (incl. Facility Association) Coverage/KoL: Accident Benefits - Uninsured Motorist (KoL 39) Data Source: AIX All-Industry Loss Development Exhibit Item: Projected Experience for Policy Year starting 01/11/2013 Description: Historical Estimated and Future Projected All-Industry Ultimate Accident Half-Year Experience (excluding Health Levy but including ULAE), under various Products Historical Estimated Ultimate Statistics & Future Projected Ultimate Statistics Fitted Regression Estimates Independent Variables for Regression Acc. Car-Years Pro Rata # $ % $ $/Car $/Car % Car-Years % $ $/Car OldP/ 04-2P/ 07-1P/ 2nd Wthr OldP/ 04-2P/ Half Earned $ Earned Claim Claim Claim Claim Loss Earned Loss Earned Claim Claim Loss Prior Prior Prior Hlf Yr Cat Prior Prior Year Exposure Premium Count Amount Freqcy Severity Cost Premium Ratio Exposure Freqcy Severity Cost Level Level Level Level Level Trend Trend 19961 702,438 23,454,310 4 201,166 0.001 50,292 0.29 33.39 0.9 679,569 0.001 28,554 0.16 1.000 0.000 0.000 0.000 0.000 0.250 0.000 19962 716,995 28,781,304 6 252,273 0.001 42,046 0.35 40.14 0.9 705,434 0.001 28,554 0.16 1.000 0.000 0.000 1.000 1.000 0.750 0.000 19971 709,388 30,569,244 4 300,412 0.001 75,103 0.42 43.09 1.0 703,313 0.001 28,554 0.16 1.000 0.000 0.000 0.000 0.000 1.250 0.000 19972 732,097 33,698,955 3 296,281 0.000 98,760 0.40 46.03 0.9 730,081 0.001 28,554 0.16 1.000 0.000 0.000 1.000 0.000 1.750 0.000 19981 745,435 35,593,233 7 301,181 0.001 43,026 0.40 47.75 0.8 727,887 0.001 28,554 0.16 1.000 0.000 0.000 0.000 0.000 2.250 0.000 19982 753,625 36,570,499 4 95,823 0.001 23,956 0.13 48.53 0.3 755,590 0.001 28,554 0.16 1.000 0.000 0.000 1.000 1.000 2.750 0.000 19991 743,979 36,929,834 5 37,901 0.001 7,580 0.05 49.64 0.1 753,319 0.001 28,554 0.16 1.000 0.000 0.000 0.000 0.000 3.250 0.000 19992 760,146 37,546,087 4 293,159 0.001 73,290 0.39 49.39 0.8 781,990 0.001 28,554 0.16 1.000 0.000 0.000 1.000 0.000 3.750 0.000 20001 780,439 38,654,226 6 290,086 0.001 48,348 0.37 49.53 0.8 779,639 0.001 28,554 0.16 1.000 0.000 0.000 0.000 0.000 4.250 0.000 20002 807,484 40,543,620 7 82,097 0.001 11,728 0.10 50.21 0.2 809,313 0.001 28,554 0.16 1.000 0.000 0.000 1.000 1.000 4.750 0.000 20011 812,443 41,479,104 4 92,191 0.000 23,048 0.11 51.05 0.2 806,880 0.001 28,554 0.16 1.000 0.000 0.000 0.000 0.000 5.250 0.000 20012 844,102 44,727,646 7 211,893 0.001 30,270 0.25 52.99 0.5 837,590 0.001 28,554 0.16 1.000 0.000 0.000 1.000 0.000 5.750 0.000 20021 832,380 46,097,890 1 109,517 0.000 109,517 0.13 55.38 0.2 835,072 0.001 28,554 0.16 1.000 0.000 0.000 0.000 0.000 6.250 0.000 20022 869,522 49,952,888 7 164,278 0.001 23,468 0.19 57.45 0.3 866,855 0.001 28,554 0.16 1.000 0.000 0.000 1.000 0.000 6.750 0.000 20031 853,159 50,517,919 6 64,645 0.001 10,774 0.08 59.21 0.1 864,249 0.001 28,554 0.16 1.000 0.000 0.000 0.000 0.000 7.250 0.000 20032 875,870 54,589,148 3 21,342 0.000 7,114 0.02 62.33 0.0 897,143 0.001 28,554 0.16 1.000 0.000 0.000 1.000 0.000 7.750 0.000 20041 864,301 54,928,139 7 66,840 0.001 9,549 0.08 63.55 0.1 894,445 0.001 28,554 0.16 1.000 0.000 0.000 0.000 0.000 8.250 0.000 20042 893,636 55,456,343 3 101,491 0.000 33,830 0.11 62.06 0.2 928,488 0.001 48,576 0.28 1.000 0.500 0.000 1.000 1.000 8.750 0.125 20051 888,577 52,506,871 6 898,196 0.001 149,699 1.01 59.09 1.7 925,697 0.001 82,637 0.47 1.000 1.000 0.000 0.000 1.000 9.250 0.500 20052 941,650 53,913,225 4 1,808,984 0.000 452,246 1.92 57.25 3.4 960,929 0.001 82,637 0.47 1.000 1.000 0.000 1.000 0.000 9.750 1.000 20061 945,397 52,001,984 1 56,006 0.000 56,006 0.06 55.01 0.1 958,041 0.001 82,637 0.47 1.000 1.000 0.000 0.000 0.000 10.250 1.500 20062 1,000,816 54,290,492 4 736,419 0.000 184,105 0.74 54.25 1.4 994,504 0.001 82,637 0.47 1.000 1.000 0.000 1.000 1.000 10.750 2.000 20071 1,001,481 54,239,291 7 1,001,719 0.001 143,103 1.00 54.16 1.8 991,514 0.001 82,637 0.47 1.000 1.000 0.670 0.000 1.000 11.250 2.500 20072 1,056,479 56,744,348 12 1,086,508 0.001 90,542 1.03 53.71 1.9 1,029,252 0.001 82,637 0.47 1.000 1.000 1.000 1.000 1.000 11.750 3.000 20081 1,053,298 56,211,621 8 269,852 0.001 33,732 0.26 53.37 0.5 1,026,157 0.001 82,637 0.47 1.000 1.000 1.000 0.000 0.000 12.250 3.500 20082 1,098,212 58,435,948 13 1,006,405 0.001 77,416 0.92 53.21 1.7 1,065,213 0.001 82,637 0.47 1.000 1.000 1.000 1.000 1.000 12.750 4.000 20091 1,080,743 58,722,935 5 951,590 0.000 190,318 0.88 54.34 1.6 1,062,011 0.001 82,637 0.47 1.000 1.000 1.000 0.000 0.000 13.250 4.500 20092 1,119,991 61,978,670 11 782,903 0.001 71,173 0.70 55.34 1.3 1,102,431 0.001 82,637 0.47 1.000 1.000 1.000 1.000 1.000 13.750 5.000 20101 1,100,667 60,035,766 8 1,384,162 0.001 173,020 1.26 54.54 2.3 1,099,117 0.001 82,637 0.47 1.000 1.000 1.000 0.000 0.000 14.250 5.500 20102 1,147,571 61,221,644 9 1,208,949 0.001 134,328 1.05 53.35 2.0 1,140,950 0.001 82,637 0.47 1.000 1.000 1.000 1.000 1.000 14.750 6.000 20111 1,128,672 58,812,870 9 616,477 0.001 68,497 0.55 52.11 1.0 1,137,520 0.001 82,637 0.47 1.000 1.000 1.000 0.000 0.000 15.250 6.500 20112 1,178,746 60,786,682 12 659,931 0.001 54,994 0.56 51.57 1.1 1,180,814 0.001 82,637 0.47 1.000 1.000 1.000 1.000 1.000 15.750 7.000 20121 1,173,155 60,478,972 3 85,322 0.000 28,441 0.07 51.55 0.1 1,177,264 0.001 82,637 0.47 1.000 1.000 1.000 0.000 0.000 16.250 7.500 20122 1,225,881 64,557,619 0 0 0.000 0 0.00 52.66 0.0 1,222,072 0.001 82,637 0.47 1.000 1.000 1.000 1.000 1.000 16.750 8.000 20131 1,218,398 7 573,339 0.001 82,637 0.47 1,218,398 0.001 82,637 0.47 1.000 1.000 1.000 0.000 0.000 17.250 8.500 20132 1,264,770 7 595,161 0.001 82,637 0.47 1,264,770 0.001 82,637 0.47 1.000 1.000 1.000 1.000 0.650 17.750 9.000 20141 1,260,968 7 593,371 0.001 82,637 0.47 1,260,968 0.001 82,637 0.47 1.000 1.000 1.000 0.000 0.000 18.250 9.500 20142 1,308,961 7 615,955 0.001 82,637 0.47 1,308,961 0.001 82,637 0.47 1.000 1.000 1.000 1.000 0.650 18.750 10.000 20151 1,305,026 7 614,104 0.001 82,637 0.47 1,305,026 0.001 82,637 0.47 1.000 1.000 1.000 0.000 0.000 19.250 10.500 20152 1,354,696 8 637,477 0.001 82,637 0.47 1,354,696 0.001 82,637 0.47 1.000 1.000 1.000 1.000 0.650 19.750 11.000 PYWtd 2,599,483 15 1,223,234 0.001 82,637 0.47 Earned Car-Years of Exposure Beta Hat Parameter Estimates: 13.421 N/A N/A 0.020 N/A 0.034 N/A Ultimate Claim Frequency Beta Hat Parameter Estimates: -7.465-0.005 N/A N/A N/A N/A N/A Ultimate Claim Severity Beta Hat Parameter Estimates: 10.260 1.063 N/A N/A N/A N/A N/A Ultimate Claim Cost/Car-Year Beta Hat Parameter Estimates: -1.811 1.057 N/A N/A N/A N/A N/A Earned Car-Years of Exposure R*2 Statistic = 98.8%; T-Test Statistics on 31 Degrees of Freedom: 1,819.175 N/A N/A 3.004 N/A 50.152 N/A Ultimate Claim Frequency R*2 Statistic = 0.0%; T-Test Statistics on 32 Degrees of Freedom: -54.685-0.028 N/A N/A N/A N/A N/A Ultimate Claim Severity R*2 Statistic = 25.7%; T-Test Statistics on 32 Degrees of Freedom: 46.407 3.323 N/A N/A N/A N/A N/A Ultimate Claim Cost/Car-Year R*2 Statistic = 20.4%; T-Test Statistics on 32 Degrees of Freedom: -7.092 2.862 N/A N/A N/A N/A N/A Earned Car-Years of Exposure Two-Sided T-Test Tail Probability %: 0.000 N/A N/A 0.523 N/A 0.000 N/A Ultimate Claim Frequency Two-Sided T-Test Tail Probability %: 0.000 97.800 N/A N/A N/A N/A N/A Ultimate Claim Severity Two-Sided T-Test Tail Probability %: 0.000 0.224 N/A N/A N/A N/A N/A Ultimate Claim Cost/Car-Year Two-Sided T-Test Tail Probability %: 0.000 0.736 N/A N/A N/A N/A N/A Earned Car-Years of Exposure Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 673,759.549 1.000 1.000 1.020 1.000 1.035 1.035 Ultimate Claim Frequency Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 0.001 0.995 1.000 1.000 1.000 1.000 1.000 Ultimate Claim Severity Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 28,554.275 2.894 1.000 1.000 1.000 1.000 1.000 Ultimate Claim Cost/Car-Year Exponentiated Beta Hat Parameter Estimates, with Cumulative Trend: 0.163 2.878 1.000 1.000 1.000 1.000 1.000 Note: 1. Earned Exposure, Frequency, Severity, and Loss Cost are projected by Linear Regression on their Natural Logarithms 2. Regression Equation is: Ln Y = X x Beta + Epsilon, where X is matrix of independent variables, and Epsilon is distributed Normal (0, I x Sigma*2) 3. Independent Variables with Beta Hat and T Statistic and T Tail Probability = N/A have been judgmentally omitted from the Regression Time: 9:48:09 a.m. May 15, 2013 36

Exhibit 3 - Derived Accident Half-Year Payment Patterns 37

Exhibit 3 - Projected Payout Patterns - Page 1 Alberta All-Industry Private Passenger (ex. Farmers) Automobile Insurance Projected Current Accident Half Year Payout Patterns by Sub-Coverage Based on PPAxF Loss Development Exhibit Data valued as of 31/12/2012 Run-off (Months) % Payout Pattern of Expected Ultimate by Sub-Coverage TPL-BI TPL-PD AB-FB AB-DB AB-M/R AB-DI AB-SB AB-UM 0-6 1.6 34.2 36.5 26.7 33.8 21.9 23.9 1.8 6-12 6.0 53.1 45.5 49.3 40.9 39.5 24.1 0.5 12-18 5.2 8.1 9.5 14.5 11.1 16.7 38.5 1.6 18-24 5.1 2.2 3.7 2.6 5.7 10.1 8.7 1.1 24-30 7.1 1.1 2.9 6.3 3.7 5.6 4.8 1.1 30-36 7.1 0.3 1.9-1.0 1.2 1.7 3.5 36-42 8.1 0.2 0.4 1.3 0.6 5.8 42-48 8.0 0.2 1.2 0.3 0.3 4.6 48-54 7.8 0.1 0.3 0.4 8.2 54-60 8.5 0.1 0.3 0.8 12.5 60-66 6.9 0.1 0.2 0.4 3.8 66-72 5.9 0.1 0.1 0.9 11.9 72-78 5.1 0.2 0.3 0.2 1.3 78-84 4.1 0.3 0.1 3.4 84-90 3.2 0.1 0.3 24.6 90-96 2.3 0.2 0.1 2.2 96-102 1.6 0.1 0.1 1.4 102-108 3.4 0.1 1.5 108-114 0.8 0.2 0.2 114-120 0.7 0.1 0.7 120-126 0.5 7.1 126-132 0.2 1.1 132-138 0.2 138-144 0.2 144-150 0.1 0.1 150-156 0.2 156-162 0.1 162-168 168-174 174-180 180-186 186-192 192-198 198-204 204-210 210-216 216-222 222-228 228-234 234-240 240 - Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Time: 10:03:24 a.m. May 15, 2013 39