Pension Payouts and Life Expectancy Assumption

Transcription

1 Are you assumed dead before your savings die? The consequences of pension companies decisions on life and death Alexandra Claesson & Angelica Idenving Centre for Finance & Department of Economics Bachelor's thesis in Financial Economics (15 ECTS) Supervisor lector Evert Carlsson Version: In this paper the pension companies and their life expectancy assumptions are compared in terms of pension payout levels and gender differences. The first-ofits-kind survey conducted by the Consumers Banking & Finance Bureau in collaboration with the Financial Supervisory Authority reporting life expectancy assumptions along with estimated payouts serve as a base for this study. This paper shows that the company specific life expectancy assumption leads to unwarranted differences in payout level, among companies and between genders. The results highlight that some companies perform better than others and that the recommended choice differs if you are male or female.

2 Contents 1. Introduction The pension companies and the market The approach of the analysis Assumptions and limitations Execution Calibration of parameters Payout data Nominal payout data Inflation adjusted payout data Inheritance gain DUS06: Gender specific lifespan assumptions Results Concluding remarks References Appendix APPENDIX A APPENDIX B APPENDIX C APPENDIX D APPENDIX E APPENDIX F APPENDIX G

3 Acknowledgments This paper would not have been possible without the guidance of our knowledgeable and persistent supervisor lector Evert Carlsson, whose expertise within the pension system has proven to be as helpful to our thesis as it is impressive in general. We also want to thank the actuaries of the Swedish pension companies and that have helped us gain insight into the closed world of life expectancy denominator. We direct a special thanks to Sven Tengstam for his valuable advice and for being so generous with his time in our time of inflation despair. Furthermore, fellow student Oscar Coster have our deepest gratitude for showing sides of Excel we never knew existed. 1. Introduction The aim of our study is to provide a review of the different choices in occupational as well as in private pension. The main focus is the pension payout levels and their distribution over the Life Expectancy Assumption (LEA), the expected growth of the pension capital, and the consequences of gender differences. The analysis is carried out to find whether or not the pension companies are distributing the adequate amount of monthly payouts, given the LEA. The concluding remarks focus on the differences among the companies and between the genders, and the fact that some companies perform better than others. We use the survey of pension companies presented by the Swedish Consumers Banking and Finance Bureau (CBFB) in collaboration with the Swedish Financial Supervisory Authority (FSA) as a base for this paper and as far as we know little or no analysis has been done previously on the CBFB/FSA survey data. 3

4 The inspiration for this paper is best described in a Network of Pension specialists press release (Nätverket för pensionsspecialister, 2012) containing the motivation to the award Pension specialist of the year 2011: Alf Ohlén has through his ground-breaking articles on LEA brought a subject to light that the pension industry have not spoken about at all but that is of great importance for pension savers. His articles has generated great attention in non-industry specific newspapers and have also led to the inspection of LEA and Forecast Interest Assumption (FIA) carried out by Swedish Consumers' Banking & Finance Bureau in collaboration with the Swedish Financial Supervisory Authority. Ohlén points out the non-transparency problem of LEA in life-long pension plans (Pensioner & Förmåner, 2010) and the crucial role of the FIA for the level of payouts over time (Pensioner & Förmåner, 2010). FIA is defined as the prognosis of future yield that each pension company expects to attain which also affects the distribution of the pension payouts. Ohlén also highlights the differences in LEA among mutual companies, that redistribute company excess gains to the remaining policy holders, and profit companies, that redistribute company excess gains to shareholders (Pensioner & Förmåner, 2010). A pension company, often profit companies with shareholder interests, that combines a low FIA with long LEA, will have payouts that are so unevenly distributed that most retirees risk death before they receive their money s worth (Dagens Nyheter, 2011). 4

5 A retiree s total pension consists of the national retirement pension, and possible occupational pension paid by the employer and optional private pension. These papers focus on occupational and private pension within the conventional insurance with life-long payout schemes. In conventional insurance the pension company is fully in charge of investing the pension saver s deposits and also offers a company specific guarantee of pension levels (Min Pension i Sverige AB). In fund insurance there is no guarantee since the pension level is dependent on how the pension saver decides to invest his or her savings and so making the LEA less essential. Instead the pension level in fund insurance is fully reliant on the performance of the chosen funds. For the above stated reasons this paper analyzes the conventional insurance, with the company specific guarantee, as the LEA is an important factor deciding the level of payouts in conventional pension schemes. The CBFB/FSA survey data used in our analysis is based on an assumption of no repayment cover. This means that if a retiree were to die with savings left, the funds are distributed to the surviving insured without a repayment cover as an inheritance gain (Pensionsmyndigheten, 2010). The analysis will thus include a factor representing the annual inheritance gain based on the probability of death. The retiree s occupational and private pension level is determined by annuity divisors that contain the two previously mentioned factors: the LEA and the FIA (Pensionsmyndigheten, 2010). The FIA, along with the LEA, is an important factor affecting the level of pension payouts. However, to limit our analysis the FIA is excluded from further discussion. If the LEA is high the pension level will be low because the pension capital has to be distributed over a longer period of time, holding all other factors fixed. It is in the pension companies best interest to set the LEA to a realistic level, not too low so that the pension company cannot fulfill future payout commitments and not too high resulting in noncompetitive payout levels, which might lead to consumer flight. 5

6 The occupational pension is gender neutral, in both fees and payout levels, by law since 21 December 2012 (Europeiska unionens officiella tidning, 2012) and the pension agreements is tied to work-place specific collective agreements. In contrast, the private pension is gender specific in both LEA and payout levels and independent of collective agreements. To perform a relevant analysis of pension companies LEAs we need a foundation to build upon. A number of studies have been carried out in the area of expected remaining lifetime of the insured population and the most recent one performed on the Swedish insured population is The Mortality Investigation 2006 (DUS06). It was carried out by a working group established by the Swedish Research Council for Actuarial Science. The study has been carried out on data collected from twelve of the Swedish pension companies (Försäkringstekniska Forskningsnämnden, 2007). For information on participating pension companies in the DUS06 study, see Appendix A. As mentioned in the abstract this paper investigates the gender neutral occupational pension from a gender perspective, using DUS06 gender specific LEA as a benchmark. DUS06 states that even though the gender specific lifespans are approaching one another the difference between the genders is still substantial (Försäkringstekniska Forskningsnämnden, 2007). Finally two additional dimensions to the pension system are introduced, defined contribution and defined benefit pension plans: these determine the basis for how the retiree s pension level will be established. In defined benefit the pension payouts are calculated to a set value, usually a percentage of the pension saver s salary and the financial risk is shared between the employer and the pension company. In a defined contribution scheme the pension payouts are determined by the amount of deposits in ratio to salary (Lydén, 2011). The pension payouts in defined contribution schemes hence depend on how large deposits the employer makes and how the deposits are invested, which means that the employer is free of financial risk regarding the pension payout amount. The defined benefit pension scheme has 6

7 up until recently been dominating, however defined contribution pension schemes is becoming increasingly important in Sweden (Palmgren, 2007). In a defined contribution scheme a greater risk is transferred to the individual pension saver. This demands a transparent and unified language among pension companies in order for the pension saver to make sound choices, a demand that is not satisfied today due to the non-transparency of pension companies (Pensioner & Förmåner, 2010). The remainder of this paper is organized as follows: Chapter 2 is dedicated to general description of the pension companies and some of the most interesting interview-responses. The approach of the analysis is presented in Chapter 3. Chapter 4 describes the calibration of parameters. Chapter 5 is reserved for discussion of the results, while Chapter 6 contains the concluding remarks. 2. The pension companies and the market Figure 2.1 illustrates what the pension market shares looks like for the pension companies in terms of premium income on life insurance. Figure 2.1 Market share in premium income from old and new insurances (Svensk Försäkring, 2012) (Svensk Försäkring, 2012) 7

8 The companies included in this study are: Alecta, AMF, Nordea Liv & Pension, Folksam, KPA, Länsförsäkringar Liv, Handelsbanken Liv, Swedbank, SEB Trygg Liv AB, Skandia Liv, SPP. The passive choice option contains Alecta, AMF, and KPA which are studied as a separate observation. If an individual enters an occupational pension scheme without making an active choice of investment, his or her pension savings will be administered by Alecta, AMF, or KPA depending on occupational agreement. For more detailed information about the included pension companies, see Appendix A. The LEA differs among companies. In the contacts with the pension companies the aim was to find explanations for the LEA differences. Every company in this study was given the same chance to participate and 6 out of 11 responded in various extent. The contacted companies were guaranteed strict confidentiality since the LEA calculations can be considered a business secret. Communication with the companies was handled mainly over the phone and via . A summary of questions asked is attached in Appendix B. Every pension company stated that calculations are based on company specific populations and that this could explain some of the difference between LEAs. The company specific policy for changing insurance payout scheme was also mentioned as a factor that might incur to LEA differences. Actuaries of pension companies argued that a less conservative policy for changing payout schemes results in a remaining insured population that is healthier. Less-healthy retirees are assumed more likely to make early withdrawals of their pension deposits and therefore leave the population at an early stage. Inquiries about LEA calculations revealed that most pension companies use the same model, the Makeham model. An interesting observation since you would expect the LEAs of different companies to be similar when based on the same model. This paper shows that this is not the case. The study DUS06 was mentioned as a benchmark for setting own assumptions 8

9 and DUS06 is based on the Lee-Carter model (Försäkringstekniska Forskningsnämnden, 2007). We will make no further analysis of the specific models used when forecasting remaining lifetime, for further information on the above mentioned models see Appendix G 3. The approach of the analysis 3.1 Assumptions and limitations In order to make a relevant analysis we have used the CBFB/FSA-assumptions: Initial capital of SEK Payouts start at 65 years of age (2011) and payouts are life-lasting Assumptions of 5,5 % nominal annual yield and 2 % annual inflation applies. Annual tax is 0,5% of remaining capital The yield assumption is before reductions for operational costs, actual capital management cost and annual tax For further information see Appendix C. The nominal yield assumption of 5, 5% seem a bit optimistic, but we make no further remark on the nominal yield percentage assumption in this paper. This paper uses both Statistics Sweden (SCB) and DUS06 as a basis. Data from SCB are used exclusively in generating appropriate estimations for mortality and survival probabilities. The reasons for using data from SCB are mainly due the applicability on the population as a whole, and the accessibility of annual estimates. A comparison show that the difference in mortality rates are approximately the same for the population as a whole and the mandatory insured population, only slightly lower for the latter. As the forecasted age increase the difference between the two populations decline (Försäkringstekniska Forskningsnämnden, 2007). 9

10 3.2 Execution The first, second, and third part of this study applies to both private and occupational pension plans. In these three parts we compare the companies in terms of net present values of payouts and the distribution of payouts over the LEA period. The fourth part applies only to occupational pension plans, due to the gender-neutral nature of occupational pension agreements. This last part of the study compares the companies in terms of gender differences hence the exclusion of private pension plans. The first part of this study analyzes whether or not the pension companies are distributing the correct amount to the retiree given the assumptions stated as basis for the CBFB/FSA survey. We examine this by finding the month where the retiree s pension capital is last positive, i.e. when the retiree s pension savings have run out. This will henceforth be referred to as the Economical Lifespan of capital (EL of capital). We find the month of interest by the following procedure: In month 1, the first monthly payout is subtracted from the initial amount of SEK and the remaining capital is then multiplied by a monthly total factor described in the next paragraph. This returns the closing balance for month 1 which will be the balance carried forward to month 2. The procedure is then repeated over 30 years of payouts since this is the period over which the company has given their pension payout prognosis. The period of 30 years is the difference between the first and the last point estimate in the CBFB/FSA survey. At some point during this time the closing balance will turn negative and this month is the breakpoint defined. By this procedure we have now found the EL of capital defined as the time period over which the capital could be paid out given the assumptions of the CBFB/FSA study. 10

11 The monthly total factor mentioned above is divided into two parts: a part that is static over the full period of 30 years and a non-static part that change annually. The general assumptions used in the CBFB/FSA study of monthly nominal growth, monthly tax and monthly company specific capital investment management cost as well as operational costs, make up the static part of the total factor. The annually changing factor is the company specific inheritance gain explained in calibration of parameters. To find values and transformations of the monthly total factor see Appendix D. The second part of the analysis compares the net present value of payouts during the company specific LEA to the calculated EL of capital. The inflation adjusted payouts are summed over the LEA period and over the EL period which leaves us with the net present value of LEA capital and the corresponding value for the EL of capital. The calculated net present value sums will also be presented as an annual percentage point change of the initial capital of SEK. We generate the percentage change for each capital by dividing them both with the initial capital. To give a comparison of the LEA capital percentage change and the EL of capital percentage change we divide them both by the LEA period. 11

12 This procedure generates the percentage point change per year for the LEA capital and a percentage point change per year according to our calculations of the EL of capital. The first percentage point (3.3) describes the average annual change of capital that the company indirectly assumes they can attain. The second percentage point (3.4) describes the average annual change of capital that should or could be attained. The third part of this study aims to give a graphical representation of the distribution of the pension payouts. Each company specific LEA is divided into four subsequent equal periods 1, 2, 3 and 4. These periods will hence be different for each company since the LEA differs among the companies but each period will represent 25% of the company s LEA. The net present value of company specific payouts are then summarized for each period and expressed as a percentage of the net present value of the sum of all payouts over the whole LEA period. For exact values and percentages see Appendix E. The fourth part of this study forecasts the average actual retained net present value of pension payouts if the retiree is either a woman or a man, given that the retiree has an average lifespan according to the gender specific remaining lifespans specified in the industry specific benchmark DUS06. The gender specific net present values of payouts are obtained by summarizing the inflation adjusted payouts for the lifespan assumption period of a woman and man respectively. 4. Calibration of parameters 4.1 Payout data In the original CBFB/FSA-study, LEAs and four point estimates of monthly pension payouts at the age of 65, 75, 85, and 95 were reported for a retiree of the age of 65 in 2011 by eleven profit and mutual life insurance companies (Konsumenternas Försäkringsbyrå, 2011). The 12

13 survey covered both occupational as well as private pension agreements. A total of 93 separate point estimates were reported by the eleven companies across five occupational agreements and the two gender specific private pension agreements. In order to make a relevant comparison all observations with less than four original payout point estimates were eliminated. Nominal payout data The four company specific point estimates of pension levels, reported in the CBFB/FSAstudy, act as the main data. A polynomial trend line was used to estimate a function for yearly point estimates of monthly payout amounts for the next 30 years. The payout amount is assumed to be adjusted once in the beginning of each year. Below is an example of the point estimates given for AMF in the collective agreement SAF-LO before Monthly payout prognosis Company Agreement LEA 65 years 75 years 85 years 95 years AMF SAF-LO pre ,2 years SEK SEK SEK SEK Using the point estimates we obtain a trend line exemplified by the following equation where x is number of years after the age of 65 and y is the payout prognosis for x. Inflation adjusted payout data The same data used for nominal payouts are used to calculate inflation adjusted payouts. The point estimates are first adjusted for inflation using continuously compounded inflation. Again, using AMF as an example the following point estimates were provided in the CBFBstudy. 13

14 Monthly payout prognosis Company Agreement LEA 65 years 75 years 85 years 95 years AMF SAF-LO pre ,2 years SEK 2 712,45 SEK 2 827,41 SEK 2 984,99 SEK The same approach and assumptions used for the nominal payout data above were then applied to the inflation adjusted payouts. The trend line function for the inflation adjusted values is presented below. 4.2 Inheritance gain In the introduction inheritance gain was mentioned as a factor representing the pension balances of deceased persons that will be credited the surviving insured in the same age group. Hence when performing the first and second part of this analysis the inheritance gain needs to be considered as a factor affecting the growth of the retiree s pension capital (Finansinspektionen, Sverige, 2011). It is calculated to correspond with the 1-year mortality probability in the following way: denotes the survival function at age x and is 1-year mortality probability (Pilbacka, 2011) (Andersson, 2005). Equation 4.1 shows how the inheritance gain is calculated in the national pension (Pensionsmyndigheten, 2010). Equation 4.1 will be applied in the analysis since pension companies do not specify how they calculate inheritance gains. The different values of the survival function at different ages have been calculated with data on mortality rates from SCB as a base (Statistics Sweden, 2012). After the performed estimations the obtained values have been compared to the mortality probabilities stated in DUS06 to make sure that the former does not exceed the latter in order not overestimate the inheritance gain 14

15 (1-π) Mortality rates are defined as the number of deaths at a certain age divided by the population at the beginning of the year (Statistics Sweden, 2009) refer to Appendix D for further information. The following transformation specified by SCB is used to generate the mortality probabilities from the mortality rates (Statistics Sweden, 2009). In order to apply the mortality probabilities as an inheritance gain in the calculations the logit framework was used. We obtain Equation 4.3 for the mortality probabilities in the different LEA from the pension companies for men and women respectively. In Equation 4.3 π is the mortality probability which by definition implies that the probability of survival is 1-π, x is age in years, α is the constant and β is the coefficient. Probability of survival 1,2 1 0,8 men 0,6 women 0,4 0, Age in years ( ) Figure 4.1 Probability of survival generated by SCB The company specific LEA of a 65-year old individual is stated in the CBFB/FSA survey and it is assumed that the product of the survival rates should sum up to 0.5 during the LEA period. In the estimation of the above function on data collected from SCB the following values for the parameters α and β were obtained: 15

16 The value of the parameter α is assumed to be approximately the same for every LEA, hence Function 4.5 was used to obtain the β for an assumed remaining lifetime at different levels. ( ) denotes the company specific LEA, see Appendix D for the different calculations and β. The company specific β was solved for and with it slightly different survival rates for the stated LEA was obtained and used when estimating the monthly inheritance gain. As specified above the mortality rates are specified by gender and since the occupational pension is gender-neutral a corresponding mortality rate was calculated. To obtain the gender neutral rate a basic method of assuming equal weights of 0.5 to the mortality rate at every age and year for men and women respectively was used. For specific values and calculations see Appendix D. Different β for each company specific LEA were estimated with the gender-neutral mortality rate by the same procedure as explained above. The inheritance gain is calculated with Equation 4.1 where the survival probabilities (1- π) as was used values for the function. This is the estimate of the inheritance gain percentage, specific for each company s LEA, which corresponds with the 1-year mortality. For further information see Appendix D. 16

17 4.3 DUS06: Gender specific lifespan assumptions Table 4.1 DUS06 Life Expectancy Assumption Women Men Birth year , ,3 16, ,7 18, ,7 19, ,5 20, ,1 21, ,5 22, ,6 23,5 The last part of the analysis is to a compare the differences between genders and as stated earlier the study DUS06 are used as a benchmark for this. The gender specific remaining lifespan assumption of a 65-year-old mandatory insured retiree is estimated for the years in DUS06 and stated in Table 4.1. Since the DUS06 LEAs are specified for each decade there is a need for a procedure that generates annual LEA estimates, since a retiree that is 65 years old in 2011 was born in To obtain the remaining lifespan for an individual born in 1946 we plot the LEAs from Table 4.1 and estimate polynomial trend lines to find a function for the annual LEA. Table 4.2 Women y = -0,0008x 2 + 0,1523x + 18,929 Men y = -0,0004x 2 + 0,1437x + 14,375 In Table 4.2 the estimated equations are presented for women and men respectively, where x is last two digits of the birth year i.e. 46 for a person born in We obtain a LEA for men of approximately years and a LEA for women of approximately years by using the equations presented in Table 4.2. The motive for analyzing the companies using gender specific LEAs is mentioned in the introduction: even though the difference in average lifetime between women and men have diminished during the last 30 years, the difference in estimated remaining lifetime is still substantial (Försäkringstekniska Forskningsnämnden, 2007). 17

18 5. Results The first and second part of this study is closely related and is presented together by Tables and Figure 5.1. The results of the third part are presented in Figure 5.2. The results of the fourth part are illustrated in Figures Detailed results for parts 1 and 3 are found in Appendix F and E respectively. A high LEA might correspond with evenly distributed, high payout amounts while a low LEA might correspond with low payouts that are weighted towards the end of the LEA. A conclusion that a high LEA is bad is therefore inaccurate on its own. The first aspect of the results in the first and the second part of the analysis can be found in Table 5.1 and Figure 5.1. Average company specific LEA Table 5.1 and average EL of capital (expressed in years) Pension company LEA EL Difference: LEA - EL SEB 23,95 26,00-2,05 SPP 23,44 24,57-1,13 Folksam 22,88 23,64-0,76 Swedbank 22,60 23,31-0,71 AMF 21,99 22,52-0,53 KPA 22,80 23,07-0,27 Nordea 24,14 24,36-0,22 Länsförsäkringar 23,50 23,65-0,15 Handelsbanken 21,93 21,89 0,04 Skandia 22,50 22,34 0,16 Alecta 21,40 21,06 0,34 Passive choice 21,30 20,10 1,20 option* LEA column: presents the average LEA over all collective agreements stated by each company. EL column: presents the, in this study, calculated average economic lifespan of capital over all collective agreements i.e. the number of years the company could or should be able to maintain the stated payout scheme Difference: presents the difference when EL is subtracted from LEA Worth noting about the results in Table 5.1 is that most of the pension companies should be able to prolong their LEA with respect only to the EL of capital and with the payouts fixed. Also, there is a big difference between the companies with the longest LEA and the shortest LEA. A few (Passive choice option, Alecta, Skandia, Handelsbanken) set the LEA lower than the EL of capital which we will return to. However, the positive LEA-EL differences are lower in absolute value compared to the absolute value of the negative differences. Large absolute values in the negative differences indicate that pension companies should be able to raise their payout levels or raise 18

19 their LEA. One interpretation of these results is that companies such as SEB, SPP, Folksam, and Swedbank are in fact using the LEA as a strategic instrument to increase their own assets and hence improve their solvency ratio. The companies solvency will be discussed later on. In Figure 5.1 it is evident that the net present value of payouts during the company specific LEA are lower in general, or at best approximately equal, compared to that of the EL of capital for all companies but the passive choice option. When cross-comparing Table 5.1 to Figure 5.1 there are large discrepancies in net present value between companies with approximately the same LEA. It is hard to justify the large net present value difference between i.e. SPP and Länsförsäkringar, when the companies have approximately the same LEA on average. Another feature is the spread of the sum of the net present value of payouts among the companies. Given that the starting capital is fixed, the spread between the companies should be much lower. The approximate SEK 19

20 difference between SEB and Länsförsäkringar seems inexplicable since, given that you live according to their individual LEA, the difference should be a lot smaller and note that their LEAs are approximately the same. Table 5.2 LEA EL Difference LEA-EL Alecta 6,35% 6,27% 0,08% Passive choice 6,29% 5,94% 0,35% option* AMF 6,07% 6,22% -0,16% Skandia 6,00% 5,95% 0,05% KPA 5,98% 6,07% -0,09% Folksam 5,88% 6,11% -0,22% Länsförsäkringar 5,84% 5,88% -0,03% Swedbank 5,76% 6,00% -0,24% Handelsbanken 5,42% 5,41% 0,01% Nordea 5,40% 5,45% -0,05% SPP 5,12% 5,43% -0,31% SEB 4,90% 5,46% -0,56% The numbers presented above are average annual percentage points increase of initial capital ( SEK) over the average LEA period stated by each company. LEA column: presents the increase of the initial capital that each company assumes to be able to attain EL column: presents the increase of the initial capital that each company should be able to attain according to our analysis. Difference: Presents the difference when the EL percentage point is subtracted from the LEA percentage point. Table 5.2 illustrates the reasoning above in annual percentage point change of initial capital for the sum of net present value of payouts. The fourth column states the differences between the two percentage points which further clarify that in general pension companies should be able to raise payout levels. To put these results into perspective, the different profiles of the pension companies need to be considered, as mentioned in the introduction they can be either mutual companies or profit companies. Appendix A presents the different company profiles and an interesting observation is that the profit companies, with the exception of Handelsbanken, are the also the ones that in general should be able to raise their payouts i.e. SPP and Swedbank to mention the most obvious ones. As mentioned in the introduction, in a mutual pension company the pension savers share both good and bad results among them whilst in a profit company the shareholders, along with the pension savers, also shares the excess gains (AMF, 2012). However, if a profit company suffers losses, the companies shareholders are responsible for financing pension 20

21 schemes contrary to the mutual company (Handelsbanken Liv, 2003). This could explain why the profit companies (Swedbank, Handelsbanken, SPP, and Nordea) in general have made more conservative prognoses with lower payout levels and longer LEAs. As noted above, a few companies have set the LEA higher compared to the EL of capital, a first reflection is that this is positive for the individual retiree. However, considering that these companies are mutual, if they make promises that can t be fulfilled they face possible solvency problems which ultimately will affect the retirees negatively. Distribution of payouts over the company specific LEA Nordea SEB Swedbank Alecta 35% 30% 25% 20% 15% 10% 5% 0% Handelsbanken Länsförsäkringar Passive choice option* Period 1 Period 2 Period 3 Period 4 SPP AMF Folksam KPA Skandia Figure 5.2 The periods denoted 1, 2, 3 and 4 each represent 25% of the company specific LEA and so they are different for each company but subsequent and equal in proportion. The inflation adjusted payouts are then summed for each period and expressed as a percentage of the total sum of payouts over the whole LEA period. The figure presents the average percentage for each period over all collective agreements for each company. Starting with Alecta the spread of the distribution over the The third part results are presented in Figure 5.2 and Appendix E. In previous paragraphs we argue that companies in general set their LEA too low with respect to the EL of capital. In this part of the study the focus is the scenario where the LEA is set too high with respect to the fact that the retiree dies sooner than the LEA predicts. Intuitively, the pension 21

22 capital payouts should be evenly spread over the retiree s lifetime. The results, illustrated in Figure 5.2, show that more than half of the pension companies have payout schemes weighted towards the end of the company specific LEA. This means that if you die before you are assumed to die you will lose a larger proportion of your savings in a payout scheme with payouts weighted towards the end compared to a more evenly spread one. Alecta, Handelsbanken, Länsförsäkringar, the passive choice option, and AMF have the most even payout schemes while Swedbank, Nordea, SEB, and SPP have the most unevenly spread ones. An important note on the results so far is that the passive choice option is somewhat of an outlier with a higher performance in comparison overall. A plausible explanation for this fact could be accredited the procurement process of the passive choice option, hence forcing the company to offer a highly competitive pension scheme. The procurement process is handled by a number of different election centrals tied to the collective agreements, such as Collectum, SPV, and Fora (Alecta, 2012). As a final remark to the results of the first, second, and third part of this analysis we return to the solvency and profile of each company specified in Appendix A. The solvency is one of the key factors considered by the FSA in their supervision and is hence an important figure for the pension companies (Finansinspektionen, 2012). It is difficult to make any general conclusions taking the solvency into consideration and also you can t make a valid comparison of solvency ratios between a mutual company and a profit company. What can be said is that Handelsbanken seems to perform somewhat better in most aspects so far compared to the other profit companies. When comparing the solvency ratio among the profit companies, Handelsbanken has the highest ratio which could explain why they are more daring in their prognosis of future payouts with a lower LEA and slightly higher payouts. 22

23 So far the analysis has focused on the company specific gender neutral LEA. The fourth part will focus on the differences between the genders and the net present value of pension payouts if the retiree is either a woman or a man. The benchmark for average remaining lifetime of a men and women is DUS06. Figure 5.3 illustrates the not surprising result that a woman will receive a larger net present value of payouts in all companies compared to a man, provided that the gender specific LEAs of DUS06 holds. The difference in net present value between the genders can be found at the bottom of Figure 5.3. This result implies that the women s payout schemes are subsidized by men since all occupational insurances are gender neutral by law (Europeiska unionens officiella tidning, 2012). The discrimination of men in gender neutral pension plans is therefore inevitable since there is a substantial difference in the average lifetime of men and women according to both Statistics Sweden and DUS06. The level of discrimination depends on the company specific LEA and the distribution of payouts over time, illustrated by Figure

24 In Figure 5.4 we use the gender specific net present values presented in Figure 5.3 and subtract the net present value of payouts calculated according to each company s gender neutral LEA period. The results show that women retain a higher sum of net present payouts and that men retain a lower corresponding amount compared to the net present value sum calculated by using the gender neutral LEA. This implies a discrimination against men and that women profit from this discrimination. A bar close to zero represents a company specific LEA close to the DUS06 estimation of average remaining lifetime for either a man or a woman. If the blue and red bar absolute values are approximately the same the conclusion that men are in fact subsidizing women can be made. When the absolute values of the female comparison value is low compared to the absolute value of the male comparison, like in the case of Nordea, SPP, and Länsförsäkringar, an important consideration needs to be made. If the discrimination of men does not substidize women, excess funds might be used for other purposes i.e. improving solvency, as mentioned in previous discussions Comparison of net present values of pension payouts between the genders within the gender neutral occupational pension plans Female Male Länsförsäkringar KPA Alecta Skandia Folksam Passive choice option* Figure 5.4 Average difference between gender neutral net present value of payouts, using the company specific life expectancy assumption, and the net present value using the gender specific DUS06 life expectancy assumptions (20,14/24,24) AMF Nordea Swedbank SPP Handelsbanken 24

25 The discrimination against men is made worse taking the results of part three into account with payout schemes weighted towards the end of the payout period which is the case e.g. for Swedbank, SPP, and Nordea. The following recommendations can be made after analyzing the results of all four parts of this study. It is hard to justify why a gender neutral retiree, that is a retiree that lives according to the gender neutral LEA, would choose SPP, Nordea, or Handelsbanken over Alecta, the passive choice option, AMF or KPA. The latter companies have high expected payout amounts that are even in distribution and the LEAs are low which leads to a high average annual percentage point change of capital. Men are more inclined towards high early payout amounts and more even payout schemes compared to women because of the shorter lifespan. Assuming that a pension saver wants to maximize the sum of expected payouts over the gender specific LEA. By combining the best choices for men from Figures and Tables Alecta, the passive choice, and KPA are the best choices for men. The LEAs of the companies best suited for men are in the low end of the group (Table 5.1). Women have longer lifespans than men, and would therefore not be as negatively affected by uneven payout schemes as men illustrated in Figure 5.2. The DUS06 female LEA is approximated to 24,24 years for a 65-year-old and is therefore higher than all gender neutral LEAs. Females thus benefit from choosing pension plans with the highest net present values of pension payouts summed for the company specific LEA. Reviewing the pension levels in Figures , Länsförsäkringar, Folksam, and Alecta are good choices for a woman. Skandia could also be a recommendation for a woman with a high net present value of the sum of inflation adjusted payouts in both Figure 5.1 and 5.3 and a prognosis of payouts that approximately coincide with the calculated EL of capital. 25

26 The pension companies are required by the FSA not to set their LEA at unrealistically low levels (Pensioner & Förmåner, 2010). What the definition of an unrealistic level of the LEA remains unsaid. 6. Concluding remarks The main results are that in general the pension companies do not repay the adequate net present value of a retiree s savings, not even if the retiree lives according to the company specific life expectancy assumption. The best way to make the most out of your savings is simply to live longer. However if prolonging your lifespan seem unattainable, there are some grains of gold among the pension companies. Alecta, with a high expected and evenly distributed payout amount combined with a low life expectancy assumption which leads to a high average annual percentage point change of capital, would be our choice for a gender neutral retiree. Other sound choices for the same retiree would be KPA, AMF and the passive choice option on the same basis. However, retirees have genders and the recommendation differs for males and females. The best choices for men are basically the same as it is for the gender neutral retiree, but another valuable option would be to extract the occupational pension savings as soon as possible and reinvest them in gender specific private pension. Excellent choices for women are Länsförsäkringar, Folksam, Alecta and Skandia after reviewing both levels as well as distribution of payouts. The execution of this paper was made difficult because of non-transparency of fee levels and definitions, non-unified language between companies and varied accounting standards regarding financial ratios and key figures. This non-transparency could benefit some companies; if it became known that some companies are better suited from women the problem of a possible overrepresentation of females arises. A further note on the nontransparency of the pension companies is the fact that we are moving towards a pension 26

27 system dominated by defined contribution schemes. As stated in the introduction this means that the financial risk in the system is transferred to the pension saver. This prompts the need for the individual to be able to make well-informed choices when it comes to saving for his or her life as a retiree. However, as stated above this is not an easy task considering the information available to the public today. As a final remark, the companies with the best results in this study were generally the most accommodating in our contact with them. This might imply that strengthened transparency can have positive influence on payout schemes from a retiree perspective. 27

28 References Alecta. (2012). Vem gör vad - Valcentralerna. Retrieved from alecta: den 22 May 2012 AMF. (2012). All vinst tillbaka till kunderna. Retrieved from AMF: 11 June 2012 Andersson, G. (2005). Livförsäkringsmatematik I. Stockholm: Svenska Försäkringsföreningen. Bahr, B. v. (12 April 2007). Ny dödlighet i tryggandegrunderna - Bilaga 1. Retrieved from Finansinspektionen: gandegrunderna_remiss_ pdf 11 June 2012 Dagens Nyheter. (8 November 2011). Så räknas din pension ned. Dagens Nyheter. Europeiska unionens officiella tidning. (13 January 2012). Riktlinjer för tillämpningen av rådets direktiv 2004/113/EG på försäkringar mot bakgrund av EU- domstolens dom i mål C-236/09 (Test-Achats). Retrieved from EUR-lex: 29 April 2012 Finansinspektionen. (2012). Om Solvens. Retrieved from Finansinspektionen: 22 May 2012 Finansinspektionen, Sverige. (2011). FFFS 2011:39. Finansinspektionen, Sverige. 28

29 Försäkringstekniska Forskningsnämnden. (2007). Försäkrade i Sverige - dödlighet och livslängder, Prognoser Stockholm: Svenska försäkringsföreningen. Handelsbanken Liv. (12 June 2003). Release archive. Retrieved from Thomson Reuters: +rapport+ger+starkt+st%c3%b6d+f%c3%b6r+vinstutdelande+livbolag+hug html 11 June 2012 Konsumenternas Försäkringsbyrå. (17 November 2011). Stora skillnader i bolagens pensionsutbetalningar. Retrieved from Konsumenternas vägledning inom bank och försäkring: 29 March 2012 Lydén, A. (9 March 2011). Fråga - Förmånsbestämd eller premiebestämd tjänstepension? 09_fraga---formansbestamd-eller-premiebestamd-tjanstepension 5 May 2012 Min Pension i Sverige AB. (u.d.). Minpension.se. Retrieved from Ordlista: 2 May 2012 Retrieved from compricer.se: Nätverket för pensionsspecialister. (31 January 2012). Bisnode. Retrieved from Alf Ohlén utsedd till årets pensionsspecialist 2011: 17 May 2012 Palmgren, B. (10 May 2007). Pension under utbetalning. Retrieved from Finansinspektionen: t2007_8.pdf 11 June

30 Pensioner & Förmåner. (1 September 2010). Alecta ger unga pensionärer mest pension för pengarna. Retrieved from LLBAKA=1&zold_patterns=Alecta+ger+unga+pension%E4rer+mest+pension+f%F6r +pengarna&zsection=archive 15 May 2012 Pensioner & Förmåner. (2010). Din död är ren vinst. Pensioner & Förmåner, nr.13, Pensioner & Förmåner. (13 October 2010). Döden har ingen lag - Sex års skillnad mellan livslängdsantaganden för samma kollektiv. Pensioner & Förmåner(12). Pensioner & Förmåner. (2010). Efter Pensioner & Förmåners avslöjande: FI tittar närmare på de vinstutdelande bolagen. Pensioner & Förmåner. Pensioner & Förmåner. (1 September 2010). Hemliga antaganden avgör pensionen. Retrieved from LLBAKA=1&zold_patterns=Hemliga+antaganden+avg%F6r+pensionen&zsection=ar chive Pensionsmyndigheten. (2010). Orange report. Pensionsmyndigheten. Pilbacka, A. (2011). Beskrivning av analys av metoder för beräkning av utbetalningar inom pensionsförsäkring. Stockholm: Stockholms universitet. Statistics Sweden. (2009). Demographic reports 2009:1, The Future population of Sweden Statistics Sweden. Statistics Sweden. (2012). Sveriges Statistiska Databaser. Dödstal efter kön och ålder. Prognosår Statistics Sweden. 30

31 Svensk Försäkring. (23 February 2012). Svensk Försäkrings Branchstatistik. (1/2012), 14. Stockholm. Teclu, H. (2007). Hur bra fungerar prognoser med Lee-Cartermodellen? Stockholm: Stockholms universitet. 31

32 Appendix APPENDIX A Key figures for the pension companies included in our study along with a list of the companies included in the DUS06 study. 32

33 Companies included in DUS06 AMF Pension Folksam Liv If KP KPA Pensionsförsäkring Robur Försäkringar Skandia Länsförsäkringar (Liv och Fondliv) Handelsbanken Liv Pension & Försäkring Moderna försäkringar SEB Trygg Liv (Gamla, Nya och Fond) SPP Livförsäkring APPENDIX B A summary of the questions asked in the communications with the pension companies included in this study. The first contact was made by phone along with a short presentation of our thesis. What is the general approach, in short, when calculating your annuity divisors? Do you use data from an in-house database as grounds for your calculated life expectancy assumptions? If an in-house database is used, how often it is updated? What factors do you take in consideration when analyzing the data used as a base for you calculation? Size of population, age of population, level of health in population, gender etc.? What would you state as the most important factors influencing the estimation of a life expectancy assumption? How is the forecast interest rate handled in your calculations? Do you use any data from Statistics Sweden? If so, to what extent and for what purpose do you use it? Is the study DUS06 used as a base? If so, to what extent? Do you use any other publications? Is the mathematical models Lee-Carter or Makeham used as a base, or other? What is the motive for using the model that you have specified in the question above? 33

34 APPENDIX C The pension companies were given instructions to calculate a pension payout projection for a retiree of the age 65 in the year of 2011 and report the results. The assumptions were provided to us in Swedish from Göran Ronge, actuary at the FSA. The following assumptions were provided to the pension companies: The calculations should base on life-lasting, or longest electable, payouts without a repayment policy Payouts start at 65 years of age The pension capital, including dividend payouts, is SEK Assumptions of 5, 5 % nominal annual yield and 2 % annual inflation applies Annual tax is 0,5% The yield assumption is before reductions for operational costs, actual capital investment management cost and annual tax. The projection must use the company s actual charge for operational costs Apply the life insurance company s own life expectancy denominator Future inheritance gains are assumed equal to the life expectancy assumptions of the company s life expectancy denominator. In profit companies, reductions for yield payouts shall be taken into consideration in the projection of the pension capital 34

35 APPENDIX D Mortality rates and total factor calculations Table D.1 MEN WOMEN NEUTRAL =(0,5*mortality rate men) + Age Year Mortality rate Mortality rate Mortality rate (0,5*mortality rate women) , , ,00911 =(0,5*0,01099)+(0,5*0,00723) , , ,00974 =(0,5*0,01182)+(0,5*0,0766) , , ,01061 =(0,5*0,01294)+(0,5*0,00828) , , ,01142 =(0,5*0,01388)+(0,5*0,00896) , , , : , , , : ,0177 0, , : ,0198 0, , : , , ,01794 : , , , , , , , , , , , , ,0398 0, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,1078 0, , , , , ,145 0, , , , , , , , , , , , , , , , , , , , , , , , , ,4894 0, , , , , , , , , , , , ,5177 0, , , ,

36 Mortality probability Mortality probability Mortality rates are calculated in following manner Where x = age at year's end, D = deaths during year t, P = Size of population at end of year t- 1 and year t for the cohort. We transformed the mortality rates into mortality probabilities with the following formula Logit estimation When using the logit framework to find an approximation of the different mortality probability functions we obtained the following values for α and β with the different mortality probabilities The mortality rates along with the estimated function is plotted below Mortality probability men 0,3 0,25 0,2 Man 0,15 0,1 Man est 0, Age in years ( ) 105 Mortality probability women 0,3 0,25 0,2 0,15 Woman 0,1 Woman est 0, Age in years 85( )

37 Mortality probability 0,3 Mortality probability gender neutral 0,25 0,2 0,15 Neutral 0,1 Neutral est 0, Age in years ( ) Company specific life expectancy assumptions To obtain the specific mortality probabilities for each company we assumed α to be constant for all of them and used the below equation to estimate different β ( ) denotes the company specific life expectancy assumption at the age of 65, and so we solved Equation A.3 for each assumption and hence generated different values for β. On the next page all the estimated values for α and β are presented for each life expectancy assumptions. 37

38 Total factor The total factor contains factor that is static over the pension payout period and one that changes annually. The factor that changes annually is the inheritance gain percentage and the factor that is static contains the general assumptions of monthly nominal growth, monthly tax and monthly company specific capital investment management cost as well as operational costs. The inheritance gain factor is calculated by using the following procedure: Where is our annual inheritance gain percentage (corresponding to the 1-year mortality probability) and denotes the survival function. We use the mortality probabilities, π, 38

39 above to calculate values for the survival function as 1-π. As an example, using the data from statistics Sweden the annual inheritance gain factor for the first year as a 65-year-old retiree (men) would be approximately The monthly factor would then be obtained by the following procedure This factor is calculated annually and makes up the non-static part of the total factor. The static part contains the following percentages Assumed annual tax rate on capital: 0,5% Assumed nominal growth rate: 5,5% Capital costs and fees specific for each company The static part of the total factor is calculated and transformed into a monthly rate as follows: We have now specified our monthly total factor which we have used in our analysis to estimate the change of the capital over time. On the next page we have specified the costs and fees that have been used for each company in our analysis. 39

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41 APPENDIX E Payout scheme layout Each company specific life expectancy assumption is divided into four subsequent equal periods 1, 2, 3 and 4. Different for each company but equal in proportion to the company specific LEA (25%). The net present value of payouts are then summarized for each period and expressed as a percentage of net present value of all payouts over the whole life expectancy assumption period. In this appendix we give the individual values and percentages for every collective agreement and company included in this analysis. The net present values are stated in SEK and percentages for each period. 41

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47 APPENDIX F Tables presenting all different life expectancy assumptions over all collective agreements and companies included in our analysis. There are two rows for each company one for their LEA and one for our calculated economic lifespan of capital denoted EL after company name. 47

48 48