The legislation under consideration in Illinois underscores the need for legislators and other policymakers to become more educated about the importance of risk-based pricing and how it works.
The Motor Vehicle Insurance Fairness Act would prevent insurers from considering non-driving factors such as credit scores when setting premium rates. The prohibitions include factors that actuaries say are highly correlated to the likelihood of a driver ultimately making a claim, as well as factors that insurers are already prohibited from using.
This suggests a lack of understanding of risk-based pricing that is not limited to Illinois legislators – in fact, similar proposals are made at the state and federal levels from time to time.
Confusion is understandable
Risk-based pricing means offering different prices for the same coverage based on risk factors specific to the insured person or property. If policies weren’t priced this way, lower-risk drivers would be subsidized. Charging higher premiums from higher-risk policyholders helps insurers underwrite a broader range of covers, improving both availability and affordability of insurance.
The concept becomes complicated when actuarially sound rating factors overlap with other attributes in a way that may be perceived as unjustifiably discriminatory. For example, concerns are raised about the use of credit-based insurance values, geography, home ownership, and motor vehicle records in setting home and auto insurance premium rates. Critics say this can lead to “proxy discrimination,” where people of color in neighborhoods are charged more than their suburban neighbors for the same coverage.
Confusion is understandable given the complex models used to assess and price risk. To manage this complexity, insurers hire actuaries and data scientists to quantify and differentiate a range of risk variables while avoiding unfair discrimination.
Appropriate protective measures are in place
It’s important to remember that insurers don’t make money from it not insure people. They are involved in pricing, underwriting and underwriting.
Insurance is one of the most regulated industries in the world because of the critical role insurers play in facilitating commerce and protecting the life and property of individuals. To ensure that sufficient funds are available to settle claims, regulators require insurers to maintain what is known as a policyholder surplus buffer.
Credit rating agencies like Standard & Poor’s and AM Best expect insurers to generate excesses in excess of what regulators require to maintain their financial strength ratings. A strong financial strength rating allows insurers to borrow money at cheap rates – further promoting the availability and affordability of insurance.
In addition to these limitations, state regulators have the power to limit the rates that insurers can charge in their jurisdictions.
No profit, no insurers – no insurers, no coverage
Like any other business, insurers need to make a reasonable profit to stay solvent. Because they cannot easily move money like less regulated industries can, the only way to make underwriting profits is through strict pricing and cost and loss control. Insurers don’t want to overcharge and let consumers shop at a better price, or undercharge and suffer losses that erode their ability to pay claims.
In this regard, it is important to note that personal auto and home insurance premium rates have remained relatively unchanged as inflation and replacement costs have skyrocketed from the pandemic and supply chain issues related to the Russian invasion of Ukraine (see graphic below).
During this time, the writers of these covers struggled to make an underwriting profit. Passenger cars were a key reason for the weak underwriting results across the industry. Triple-I Chief Insurance Officer Dale Porfilio recently said that the 2022 personal auto insurance combined ratio is forecast at 111.8, 10.4 points worse than 2021 and 19.3 points worse than 2020. The Combined ratio represents the difference between paid damages and expenses and premiums charged by insurers. A combined ratio below 100 represents an underwriting profit, above 100 a loss.
Even as inflation eases, claims trends in both of these lines – combined with increased accident frequency and severity for autos and extreme weather trends for homeowners and autos – will require rising premium rates. The question is: will costs decrease equally for all policyholders, or will rates more accurately reflect policyholder risk characteristics?
Protected Classes
The United States recognizes “protected classes”—groups who share characteristics and for whom federal or state law prohibits discrimination based on those characteristics. Race, religion and national origin are most commonly referred to when describing protected classes in the context of insurance ratings, and insurers generally do not collect information about these “big three” classes. Any discrimination based on these attributes would have to result from the use of data that could serve as proxies for protected classes.
Algorithms and machine learning show promise for ensuring fair pricing, but research shows these tools can reinforce implicit bias.
The insurance industry has responded to such concerns. For example, recent legislation in Colorado requires insurers to demonstrate that their use of external data and complex algorithms does not discriminate against protected classes, and the American Academy of Actuaries has offered the state’s insurance commissioner comprehensive guidance on how to implement it. The Casualty Actuarial Society also recently published a series of articles (see links at the end of the post) on the subject.
Correlation matters
Certain demographic factors have been shown to correlate with an increased risk of filing a claim. Gender and age are highly correlated with crash involvement, as shown by the National Highway Traffic Safety Administration (NHTSA) data shown on the right.
Likewise, the data below from the National Association of Insurance Commissioners (NAIC) clearly shows that higher credit scores are strongly correlated with lower crash claims.
Similar correlations can be shown for other evaluation factors. It is important to remember that no single factor is important – many are used to assess a policyholder’s level of risk.
Consumers “get it” – when it’s explained to them
A recent study conducted by the Insurance Research Council (IRC) found that explaining the predictive power of credit-based insurance ratings to consumers appears to reduce skepticism about the link between credit history and future insurance claims. Through an online survey of more than 7,000 respondents, IRC found the following:
- Almost all believe that maintaining a good credit history is important, and most believe that improving their credit score would be “very” or “somewhat” easy;
- Consumers see the link between credit history and future bill payments, but are less certain about the link between credit history and future insurance claims.
- After reading that many studies have proven their predictive power, most agree with the use of credit-based insurance values to evaluate insurance, especially for drivers with good credit who could benefit.
If consumers “get it” when you share the data with them, maybe politicians and legislators can too.
Learn more:
Triple-I issues briefs
Risk-based insurance pricing
race and insurance prices
Private car insurance rates
Drivers of increases in homeowners insurance rate
How inflation affects P/C insurance premium rates – and how it doesn’t
The Triple I Blog
Inflation trends shed some light for P&C, but underwriting gains still elude most lines of business
IRC poll suggests education can overcome doubts about credit-based insurance outcomes
Matching the price to the hazard helps keep insurance available and affordable
Addressing racial concerns in insurance pricing
The Delaware legislature adjourns with no action banning sex as an auto insurance factor
Triple-I: Rating Factor Diversity Promotes Accuracy in Auto Insurance Ratings
Auto Insurance Rating Factors Explained
The Casualty Actuarial Society
• Definition of discrimination in insurance
• Methods to quantify discriminatory effects on protected classes of insurance
• Understanding the potential impact of racial bias on P&C insurance: Four valuation factors examined
• Approaches to tackling racial prejudice in financial services: lessons for the insurance industry
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2023-02-14 21:22:38
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