A major controversy is growing in the world of insurance regulation over price optimization. Regulators are becoming increasingly aggressive on the issue. Maryland, California, Ohio and New York have all taken steps to restrict the practice. The National Association of Insurance Commissioners is actively studying whether the practice needs to be curbed. The issue is heating up rapidly.

What is price optimization?

There is no clear definition. Maryland defined it as “the practice of varying rates based upon factors other than the risk of loss.” California defined it as “any method of taking into account an individual’s or class’s willingness to pay a higher premium relative to other individuals or classes.” (Editor’s Note: Just last week, Florida banned the practice of price optimization. See related article, “Florida Bans Price Optimization; Insurers Question Definition.”)

In general, regulators seem to use the term to refer to setting rates with an eye on business considerations other than losses or expenses.

The Maryland definition is clearly too strict in that it fails to recognize the expense component of rate-making and rate decisions. An insurer whose strategy is to provide high levels of customer service will have higher expenses than one trying to offer the lowest-priced coverage. There are “factors other than the risk of loss” that are properly used in setting insurance rates.

The controversy is based upon regulators’ belief that price optimization involves rating based upon factors with no legitimate connection to the cost of providing insurance. A common assertion is that insurers are using sophisticated data-mining technology to charge, in the terms used by New York, “higher premiums based on whether a consumer is less likely to notice, shop around or object.” It is feared that loyal customers will be charged higher rates because the insurer concludes it can do so without losing the customer. There is little, if any, hard evidence that this is actually occurring, but the perception that it is or could be happening is enough to create regulatory problems for insurers.

Insurance regulator interest appears to have been stimulated in 2013 when Earnix, a company that provides data analysis services to banks and insurance companies, published its “2013 North America Auto Insurance Pricing Benchmark Survey.” In this publication, price optimization was defined as “using mathematical algorithms to determine optimal values of rating factors to meet certain business goals and constraints (e.g., maximizing profitability while achieving X percent of policy growth).” Regulators may have interpreted this to mean basing rates upon business goals rather than upon factors directly related to the costs of providing insurance.

Most states have laws saying that insurance rates shall not be “unfairly discriminatory.” Those regulators attempting to restrain price optimization assert that use of price optimization results in rates that are unfairly discriminatory.

It seems entirely reasonable that insurers will evaluate their pricing decisions against market and business considerations. It is neither unusual nor derogatory to say that insurers want to maximize profits. Like any business, setting prices is an important—perhaps the most important—decision that an insurer makes in maximizing its profits. If an insurer is considering raising its prices, it is going to analyze its book of business. The impact of a price change on profitability is certainly going to impact its decision. This analysis has little or nothing to do with its costs, but it is entirely reasonable.

Yet regulators are highly skeptical of insurers basing insurance rates on factors unrelated to loss costs or expenses. Charging different rates for different risks is discriminatory, in the sense that it discriminates between different risks, but it is not considered to be unfairly discriminatory. Indeed, this type of discrimination is the essence of insurance pricing.

However, if insurers appear to be basing rates on factors unrelated to risk of loss or expense, regulators will be skeptical and will scrutinize these factors aggressively.

Price optimization appears to have even less relation to a consumer’s insurance risk than credit history does. It is therefore no surprise that regulators are scrutinizing and restricting the practice.

Insurers are understandably going to analyze their customer data in every way possible in the pursuit of maximum profits. Understandable or not, insurers need to be aware that regulators are going to object to rating plans based upon factors that have no clear relation to verifiable factors involving risk or expense. This is a simple reality of insurance regulation.

Ultimately, insurers may want to use a number of factors in rate development and underwriting. Portions of this analysis may appear to be “price optimization” under the broad definitions being used by some regulators in forming their general business decisions and strategies. However, care should be taken to ensure that rating plans and underwriting guidelines submitted to regulators can be supported on the basis of expected risk of loss and expense.