What Property and Casualty Insurers Need to Know About Using Credit in Underwriting

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This post is part of a series sponsored by TransUnion.

Credit-based insurance risk scores draw from credit data to more accurately assess consumer risk and improve the underwriting process

Today, credit-based insurance scores are widely used by the personal property and casualty insurance industry, but that was not always the case. Before the introduction of insurance risk scores, carriers lacked new tools to refine pricing and expand their services to new markets. The traditional risk-assessment process was also difficult to shift to emerging online and direct channels. The market was very polarized with limited product offerings and prices for largely two segments: non-standard and standard. For consumers, insurance was limited in choice and price, time-consuming to obtain or change, and reliant upon in-person engagement. Insurers sought new ways to assess risk and assign price in real-time, differentiate their product offerings, and expand their market penetration. This sought-after transformation was ultimately made possible with the translation of consumer data into insurance risk scores.

In the commercial insurance industry, the use of credit-based insurance scores based on business owners ‘ personal credit or aggregated consumer information has been less ubiquitous than personal lines. However, TransUnion research has demonstrated that for businesses with ten or fewer employees, business owners’ insurance risk scores are correlated with claims propensity for Commercial Auto policies. Additionally, aggregated credit data provides a way for insurers to improve risk selection/segmentation by easily incorporating credit into pricing and underwriting.

What factors go into a consumer’s insurance risk score?

40%: Historical information. How many accounts a consumer has held over time and their tenure
30%: Derogatory information. Delinquencies or delinquent activity, such as bankruptcies and poor payment histories
20%: Shopping information. Instances where a consumer has applied for new credit
10%: Utilization. The ratio of a consumer’s balance to their limit

Credit scores vs. insurance risk scores: What’s the difference?

It’s easy to understand why some might think of an insurance score as just another version of the traditional credit score — but that’s not the case. Both scores are similar in that they predict future risk, but they differ in why and how they are created.

Traditional credit scores…

Predict credit delinquencies of financial transactions, such as for credit cards or mortgages
Are used as the primary tool in credit underwriting decisions
Are subject to the Fair Credit Reporting Act (FCRA)
Permit the use of account balance amount

Insurance risk scores…

Predict insurance losses
Are used to make insurance underwriting decisions, along with other variables (e.g., age and claims history)
Are likewise subject to FCRA, along with unique state regulations regarding use of credit in insurance
Exclude account balance amount

Insurance risk scores: A tool for fairness

Insurance risk scores are scalable, objective and actuarially sound, and help insurers compete nationally and in previously underserved areas. This lowering of barriers to competition lowers costs and thus leads to greater access and more choices for consumers. Insurance risk scores also result in lower premiums for the majority of consumers. A 2007 study by the US Federal Trade Commission found “that if credit-based insurance scores were used, more consumers (59%) would be predicted to have a decrease in their premiums than an increase (41%).”

To improve pricing models, insurers need credit-based insurance scores that reflect consumer behavior as it changes over time, rather than the snapshots in time found in traditional scores. By looking at changes over time, they can get better insights into consumers to create more profitable strategies.

Certain insurance risk scores, such as TransUnion’s, use trended data to create a more accurate score, incorporating how an individual has changed their credit usage and payment behaviors over time. They’re built on current-generation data, enhanced with credit data, to capture a robust view of consumers’ past behavior. This lets insurers evaluate them holistically and identify credit trends. As a result, carries get more predictive credit-based insurance scores for better pricing and underwriting decisions.

Using trended data and longitudinal variables that show not only where the consumer is today, but also how they got there, may improve the lift of existing models as much as 20%.

Credit-based insurance scores provide a stable, reliable means to assess insurance customers

Even during the COVID-19 pandemic, insurance risk scores showed strong stability. TransUnion grouped consumers into ten equal risk segments based on CreditVision® Auto insurance risk scores as of March 2020, and then analyzed how these consumers moved among risk segments through October 2020. Between March and October 2020, 85% of consumers either remained in the same or moved to a lower risk (higher score) score segment. Small business owners’ credit-based insurance scores also remained stable throughout the pandemic, with insurance scores nearly 30 points higher on average than the broader consumer population. Insurance risk scores have proved remarkably stable, and have even shown moderate improvement over the course of the pandemic.

All in all, insurance risk scores are a vital predictive variable for risk assessment across property and casualty lines of business.