“Price optimization,” a long-established economic concept, generally refers to the application of mathematical techniques using data to address pricing at a more granular level. Price optimization in property and casualty insurance ratemaking, or what has been referred to as “non-risk based pricing,” has been argued to be unfairly discriminatory and unlawful. On August 22, 2015, the Pennsylvania Insurance Department issued Notice 2015-06, published in the Pennsylvania Bulletin, and joined California, Florida, Indiana, Maryland, Ohio, Vermont and Washington in limiting and/or prohibiting the practice.
Most states have unfair insurance practices laws which provide that rates cannot be “excessive, inadequate or unfairly discriminatory.” Under these laws, insurers are required to treat similarly situated risks similarly. Pennsylvania’s recent notice prohibiting the practice cautions insurers as follows: “With the advent of sophisticated pricing tools, including computer software and rating models referred to as price optimization, insurers, rating organizations and advisory organizations are reminded that policyholders and applicants with identical risk classification profiles — that is, risks of the same class and essentially the same hazard — must be charged the same premium. Rates that fail to reflect differences in expected losses and expenses with reasonable accuracy are unfairly discriminatory. . .and will not be approved.” In short, rates must be based on the costs associated with the risk.
There is, however, no widely-accepted industry definition of or approach to price optimization as used in insurance ratemaking, creating issues for both regulators and insurers regarding the permissible uses of data in setting rates. The National Association of Insurance Commissioners’ (NAIC) Casualty Actuarial and Statistical (C) Task Force (CAS Task Force) has been working towards releasing a final Price Optimization White Paper in order to provide the industry with some direction and guidance.
The CAS Task Force began examining the practice at the request of the NAIC Auto Insurance (C/D) Study Group in 2013, in response to the urging of consumer advocacy groups to regulators around the country seeking to stop insurers from using price optimization. These groups characterize the practice as a radical departure from the actuarial practice of pricing insurance premiums according to the risk of loss assumed by the insurer. They assert that the practice allows insurers to raise customers’ premiums and increase profits based on individual shopping habits and perceived “price elasticity of demand,” which is a measurement of a consumer’s tolerance for price changes. They argue that the practice can be used to charge each consumer the highest price the market will bear, arguably resulting in two policyholders with the same loss history and risk profile being charged different rates. They claim further that price optimization has been developed to increase insurers’ profits by raising premiums on individuals who are the least likely to shop for a better price and presume that many of the people impacted are low income consumers with a lack of access to other choices.
The CAS Task Force issued a draft White Paper in March 2015 and a revised draft was released in May 2015. Numerous comments and proposed suggestions and changes to the draft were submitted by the American Academy of Actuaries, American Insurance Association, Casualty Actuarial Society, Consumer Federation of America & Center for Economic Justice, National Association of Mutual Insurance Companies and Property Casualty Insurers Association of America, among others, for consideration. The CAS Task Force met on Saturday, August 15, 2015, during the NAIC’s Summer National Meeting in Chicago, to discuss further comments and substantive changes to the revised draft based on the submissions received. The White Paper revisions remain open for comment until September 8, 2015, and it is expected to be finalized by the CAS Task Force in November, at the NAIC’s national meeting in Washington, D.C.