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Marty Epstein, FCAS, MFE Global Auto Actuary, AIG Casualty Actuaries of Greater New York (CAGNY) December 6 th, 2012.

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Presentation on theme: "Marty Epstein, FCAS, MFE Global Auto Actuary, AIG Casualty Actuaries of Greater New York (CAGNY) December 6 th, 2012."— Presentation transcript:

1 Marty Epstein, FCAS, MFE Global Auto Actuary, AIG Casualty Actuaries of Greater New York (CAGNY) December 6 th, 2012

2  Broadest definition: the technology of collecting, sending, receiving and/or storing information via telecommunication devices

3  The three most popular Telematics products in use: in vehicle navigation systems, stolen vehicle recovery systems and fleet management systems  A distant 4 th most popular product is what current discussion focuses on most: Pay How You Drive, Pay As You Drive, or User Based Insurance

4  Telematics products are most common in countries with high rates of theft (Italy, Brazil, South Africa) or in expensive, sophisticated markets (UK, Western Europe, United States)  Penetration of Telematics products is globally very low but expected to grow gradually until product is commonplace (10-20 year timeframe)

5  Too expensive for most markets  Hardware is pricy, though becoming cheaper  Data plans must be purchased for each device  Too complicated  Operationally complex  Data volumes can be massive, challenging to interpret  Pricing implementation is a challenge  Intellectual property/patent claims on existing technologies act as a barrier to entry  Most insurers are taking a wait and see approach or investing smaller amounts in pilot projects to test program viability

6  Smartphone’s are now being piloted to enhance or replace dedicated boxes for the collection and transmission of driving data  Mobile only solution is a fraction of current operational costs with the advantage of piggybacking on the customers own mobile plan  Also, the user experience can be dramatically enhanced as context relevant information can be displayed immediately after completing a trip and a variety of additional services can be made available  Mobile phone solutions have their own drawbacks, such as estimating the risk of the phone owner which may not be the same as the vehicle risk  Some countries have plans for mandating Telematics  Singapore plans to mandate use Telematics devices to determine fees for driving on public roads  Brazil seeks to reduce theft through mandatory Stolen Vehicle Recovery systems

7  Risk models that use Telematics data will soon consider the context of driving events, advancing sophistication  Current models adopted in the US market that determine price credits from mileage, braking, accelerating and speed data may be considered crude relative to their potential accuracy  Some examples of driving context: ▪ How do you evaluate a drivers risk if she exceeds the speed limit but travels at the average speed of other drivers on a particular road segment at a particular time? What if she is driving in inclement weather? ▪ Is a driver more risky if you learn that he often brakes midway through a turn rather than before the turn? ▪ What is the risk difference between a driver who rarely texts while driving and one who frequently texts while driving? What if the “texter” only does so while the vehicle is not in motion?  Psychological profiles are being mapped to driving data as a way to understand and explain driving behavior but also to predict behavior of customers in situations outside of driving

8  Most common incentive for enrolling in Telematics in the US is the potential for premium reduction:  Progressive: “you could save up to 30% extra for your good driving”  Allstate: “rewards safe drivers with the big savings they truly deserve”  State Farm: “you have control of how much you save, with the opportunity for discounts up to 50%”  Additional services are offered by some programs, for example, State Farm’s In-Drive program (monthly fee based):  Get help locating your vehicle if stolen  Vehicle diagnostic reports  Emergency response notification  Monitor high-risk drivers in household, such as teen or elderly drivers  Pay as you drive offers a way for low income and uninsured drivers to acquire insurance

9  Context specific driver education  Praise for things you did right, guidance for things you could improve  Eco driving (feedback on your CO2 footprint and how to improve)  eCall (in vehicle emergency service call button)  Planned for the EU in 2015  Claim submission and accident reconstruction  First notice of loss (identify location and time of crash, allow user to attach photos of damage)  Verify facts such as speed prior to impact, location of impact(s), estimate likelihood of property damage and soft tissue damage; reduces fraud risk  Gameification / social networking  Prizes for “safest driver”  User portals with detailed information on driver behavior  Targeted driver safety training and alerts for families with inexperienced or elderly drivers

10  Insurers will have an opportunity to dramatically change the interactive experience with their customers  What can be learned about your driving behavior will be used to help predict your behavior in other situations (subject to user agreements)  Insurers will have an opportunity to understand their customers behavior in ways only dreamed of until now  Human behaviors to be measured such as: aggression/calmness, focus, consistency, thrill seeking, avoidance, pacing

11  Pandora’s box of nearly unlimited, intimate data is open, whether we like it or not  Insurers have been loathe to use the stream of data out of fear of being called “big brother” or seen as taking advantage of privacy standards  Technology focused companies are jumping in to driver safety space with new ideas that have the power to transform the insurance business  How will customers make a value judgment as to whether they should share their data?  Worst-case scenarios have mostly been speculative so far

12  Will the addition of Telematics data to loss cost analysis result in a significant or only marginal lift in predictive power?  Does the use of Telematics data bring us too close to individual risk rating? What might be the unintended consequences?  Telematics models indicate that many drivers ought to receive a surcharge rather than a credit for their riskier than expected driving – US insurers currently only provide price discounts (no discount for riskier drivers) -- is this sustainable long-term?

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