Risk Management in the Driver s Seat: Navigating the World of Automated Vehicles EMR001

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Risk Management in the Driver s Seat: Navigating the World of Automated Vehicles EMR001 Speakers: Jonathan Charak, FCAS, MAAA Associate Vice President, Zurich Insurance Vice Chair of the Automated Vehicle Taskforce, Casualty Actuarial Society http://www.linkedin.com/in/jonathancharak Kay Wakeman Research Analyst for Highway Loss Data Institute https://www.linkedin.com/in/kaywakeman

Learning Objectives At the end of this session, you will understand: A Vehicle symbol pricing models Will you receive a discount for purchasing an automated vehicle? B Risk minimization introduction strategy C Summarize crash avoidance technology s current risk profile Front crash prevention Adaptive headlights Lane departure warning D Predicted timeline for the fitment of crash prevention technologies Electronic stability control & front crash prevention timelines IIHS front crash prevention testing

Antitrust Notice The Casualty Actuarial Society is committed to adhering strictly to the letter and spirit of the antitrust laws. Seminars conducted are designed solely to provide a forum for the expression of various points of view on topics described in the programs or agendas for such meetings. Under no circumstances shall CAS seminars be used as a means for competing companies or firms to reach any understanding expressed or implied that restricts competition or in any way impairs the ability of members to exercise independent business judgment regarding matters affecting competition. It is the responsibility of all seminar participants to be aware of antitrust regulations, to prevent any written or verbal discussions that appear to violate these laws, and to adhere in every respect to the CAS antitrust compliance policy.

Casualty Actuarial Society - Automated Vehicle Task Force - Mission Further the understanding of risk surrounding automated vehicles to help ensure the product is brought to market as safely and efficiently as possible Actuaries role: To facilitate better decision making where there is risk and uncertainty Source: http://www.casact.org/about/

A Vehicle symbol pricing models Assuming automated vehicles decrease losses: Will auto insurance decrease? vs. Will I receive a discount for purchasing an automated vehicle?

A Vehicle symbol pricing models Auto insurance level setting Cost based pricing approach As auto insurance losses decrease, premiums eventually decrease Rate Change = Projected Loss Ratio Target Loss Ratio 1 Law of large numbers Risks grouped by characteristics Rates charged based on group rating Actual discount determined by vehicle rating Rating Characteristic Examples Driver age Location Driving history Mileage Vehicle

A Vehicle symbol pricing models and some Automated Vehicle Caveats Lower frequency lower losses Higher severity can offset any frequency reduction Pricing cares about loss reduction Lower frequency risk fewer accidents Increase miles driven may offset lower risk Safer cars safer drivers Drivers may adjust habits (e.g. cell phone usage)

A Vehicle symbol pricing models CAS partnered with a national personal auto carrier Goal: To understand the discount that current credibility methods will provide insureds who purchase automated vehicles Analysis Vehicle symbol: option 1 Assume a brand new vehicle No initial prior year factor, growth trend impacts credibility Vehicle symbol: option 2 Assume update to a current vehicle Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

A Vehicle symbol pricing models Current methods may only provide 15% discount to new AVs Option 1: Brand new vehicle Number of Exposures Loss Reduction Yr 25% 50% 75% 100% 2,500 1 0.5% 0.9% 1.3% 1.8% 5,000 2 1.4% 2.6% 3.9% 5.1% 7,500 3 2.8% 5.1% 7.4% 9.7% 10,000 4 4.4% 8.0% 11.6% 15.2% Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

A Vehicle symbol pricing models With a larger discount for existing vehicle symbol types Option 2: Update to a current vehicle Maximum vehicle premium discount Number of Exposures Actual Actual Loss Reduction Yr 25% 50% 75% 100% 1 4.3% 7.4% 10.5% 13.6% 2 7.1% 13.7% 20.0% 26.3% 3 9.7% 18.2% 25.7% 35.4% 4 11.1% 21.0% 31.0% 41.2% 1 7.4% 15.0% 22.7% 30.6% 2 12.2% 24.7% 37.5% 50.5% 3 15.8% 31.9% 48.3% 65.6% 4 18.8% 38.0% 57.6% 77.6% Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

A Vehicle symbol pricing models Analysis leads to the following conclusions Model Analysis Current models will take a long time to reflect loss performance Optional equipment is unidentified Next Steps New models will have to be developed Actuaries will need much more data Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

A Vehicle symbol pricing models Fair pricing of risks benefits all Risk priced too low Risk priced too high Vehicle Sales & public safety Mfg s actions Financial Results Encourages sales of AVs Safety not as strong as discount indicates Remain manufacturing No incentive to take insurance risk Disastrous to financial performance Discourages new technology in vehicles Enter market: Properly priced risk transfer helps encourage sales Disastrous to financial performance Data is needed to for insurer to properly price Manufacturer has data may not know how to assess risk properly Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

B Risk minimization introduction strategy The goal of introducing any new product is to maximize profits Profits = Revenue Cost Cost = Cost of goods sold + liability cost n Liability Cost = i=1 Incident exposure i Incident frequency i (Average incident severity) i

B Risk minimization introduction strategy A risk (cost) minimization strategy will involve three steps 1 Change paradigm 2 Identify & quantify all risks 3 Develop a comprehensive introduction strategy that minimizes overall cost Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

B Risk minimization introduction strategy The following assumptions are required Item Technology assumptions Requirement Technology will not operate in inclement weather Accurate up to date maps of surrounding environment All other errors will be random & error rate lower than human more technology would equal less loss Manufacturer assumptions Primary goal is to minimize frequency Product liability costs: 60% to claimants vs. 40% to lawyers Secondary goal is to minimize severity Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

B Risk minimization introduction strategy Restating the NMVCCS improves understanding risks of AVs Comments Data Source: 2008 National Motor Vehicle Crash Causation Study Data is old & insufficient Identify & quantify all risks Quantify risks & correlations Supplement data with judgment Source: http://www.casact.org/pubs/forum/14fforum/cas%20avtf_restated_nmvccs.pdf

Introduction strategy Vehicle Design Operation Details B Risk minimization introduction strategy One approach for introduction could be Company owned public transportation service human cannot take control Operates in small location (major city; favorable climate; lots of hospitals) Conduct trials prior to broad introduction in city Fleet size large enough for scale, but will not drown out other options Includes an emergency response button Designed to minimize risk to pedestrians and passengers Eliminate unnecessary features Fleet will not run in inclement weather Service regularly Expansion to new cities will be dependent on results on preceding cities Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

B Risk minimization introduction strategy Which would help minimize the following risks (1/2) Item Behavioral / skill deterioration Infrastructure Weather Vehicle issues Other driver interactions Physical Impairment Description Avoid: risk eliminated, no pass off Minimize: defined operating area Avoid: operating area & shutdown protocol Company ownership reduces frequency Restricting area reduces costs Minimize: pre-testing fleets and defined operating area Operating area to reduce severity with proximity to hospitals Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

B Risk minimization introduction strategy Which would help minimize the following risks (2/2) Item Animal Hacking Random Errors Unknowns Severity Description Operating in a city reduces interactions Removing driver may increase risk Restricted area impact unknown Removing driver may increase risk Restricting area and speed reduces severity Success measured in errors per trip Restricting area reduces number of unknowns City imposes natural speed limits and minimizes distance to hospital City increases pedestrian interactions Source: CAS Automated Vehicles Task Force yet-to-be released analysis, expected publication 2016

B Risk minimization introduction strategy Implications of potential introduction strategy Conclusions of scenario Introduction will be locally rapid, globally disjointed Technology will follow parallel development paths Liability may initially reside with the manufacturer for level 4 AVs More data is required to help refine analysis

The insurance industry can benefit from more involvement Insurance industry has value to add We are leaders in risk analysis Insurance industry has inherent incentive to assess risk fairly Quantification and pricing of risks Ensure claimants are compensated fairly and efficiently Insurance industry officials like you can play a key role in helping the technology come to market as safely and efficiently as possible CAS s automated vehicle task force is performing studies to further the understanding of risk surrounding the technology

Thank you The information in this publication was compiled from sources believed to be reliable for informational purposes only. Any and all information contained herein is not intended to constitute advice (particularly not legal advice). Accordingly, persons requiring advice should consult independent advisors when developing programs and policies. We do not guarantee the accuracy of this information or any results and further assume no liability in connection with this publication and sample policies and procedures, including any information, methods or safety suggestions contained herein.