Overview of the Texas Credit Study: Texas study confirms that credit scoring accurately assesses the risk of future claims
 |
One way for an insurer to match rates as closely as possible with the potential costs of claims is to use credit information on people applying for auto and homeowners insurance.
A two-part report published in December 2004 and January 2005 by the Texas Department of Insurance confirmed that insurance scoring based on credit information is correlated with risk and, when used with other rating factors such as location, enables insurers to better assess the potential for future claims. In the second part of the report, the insurance commissioner also confirmed that the use of insurance scoring is not unfairly discriminatory because it is not based on race or income.
To conduct the study, the Texas Insurance Department obtained data pertaining to two million insurance policies. The companies participating in the study wrote personal lines insurance – private passenger auto insurance or homeowners insurance, or both. Commercial auto insurance was not included. Each set of data was randomly assigned a letter of the alphabet to preserve the anonymity of the company and its policyholders.
| |
|
| |
|
The chart above shows that the average loss per vehicle for people with the worst credit scores is double that of people with the best credit scores.
The chart identifies the relationship of “pure premium,” shown on the right axis, to credit scores, shown along the bottom. Pure premium is the average loss per vehicle. This does not include such items as the company’s overhead expenses or profit margin.
Credit scores are shown in deciles, or ten equal parts. Each decile represents a group of insurance policies that are the same in terms of credit scores. Decile 1 represents the 10 percent of policies that have the worst insurance scores. Decile 10 represents the 10 percent that have the best insurance scores.
| |
|
| |
|
For the homeowners insurance part of the study, the insurance department looked at the relationship between credit scores and average loss ratios. A loss ratio is the dollar amount of losses divided by premiums. For example, a loss ratio of 70 percent means that losses for the period amounted to 70 percent of the premium.
The chart above shows that homeowners insurance loss ratios for people with the worst credit scores are triple those of people with the best scores.
| |
|
| |
|
The chart above shows that drivers with the best credit record are involved in about 40 percent fewer accidents than those with the worst credit scores in this group.
Insurance scores don’t predict the actual experience of one individual. They predict the average claim behavior of a group of people with essentially the same credit history. A good score is typically above 700 and a poor score is below 600. While on average people who have poor credit scores tend to file more claims, there are always exceptions. Within that group, there may be individuals who have stellar driving records and have never filed a claim, just as there are teenage drivers who have never had a crash, although teenagers as a group have more accidents than people in other age groups.
| |
|
| |
|
Other studies have found similar results. An earlier study on the use of credit scores conducted by the Bureau of Business Research at the University of Texas in March 2003 found that poor credit scores were associated with higher auto insurance losses. Incurred losses, which are shown on the side axis of the chart above, are losses that have occurred within a specific period of time, whether or not they have been paid during that period.
| |
| |
|
