Using demographic information as a proxy for assessing risk, traditional underwriting models have created unequal access to insurance.
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Historically, models used by insurance companies in the U.S. have adversely affected the ability of poor and non-white individuals to obtain adequate coverage. Using zip codes, home ownership status, credit scores, and other demographic information as a proxy for assessing risk, traditional underwriting models have created unequal access to insurance as a financial safeguard, and consequently reduced some families’ ability to build generational wealth.
Longstanding bias in traditional insurance pricing models
There are laws against discrimination in underwriting, including some, like the Fair Housing Act, that even attempt to address disparate impact on protected classes as separate from the intent of certain practices. However, the issue remains, leading The National Association of Insurance Commissioners (NAIC) to form a special committee in 2020 to determine ‘what barriers exist in the industry that potentially disadvantage people of color and historically underrepresented groups.’
The auto insurance industry has been particularly guilty of archaic underwriting standards. From marital status to educational attainment, rating systems for auto carriers penalized prospective customers for aspects of their lives they cannot control as well as life choices that should have no bearing on their ability to qualify for affordable coverage.
Creating fair insurance for all
Loop insurance, a startup founded by John Henry and Carey Nadeau, aims to address these discriminatory pricing practices in the auto insurance space. Founded on the belief that everyone deserves affordable auto insurance, they use proprietary AI to focus on factors that have a direct correlation to how consumers drive.
According to Loop, their technology does not punish customers for their occupation, credit, education, or homeownership status. In fact, they provide consumers with a breakdown for how much an insurance rate will vary based on each deciding factor. Loop uses just two key metrics to give its customers a price: road conditions and driver behavior. By collecting data about how and where someone drives, Loop can set insurance premiums that are less dependent on demographic details out of their control.
Equitable Insurance does not have to be a fantasy
The trend of underwriting without using traditional factors is expected to increase. In fact, other industries outside of insurance have adopted this practice. Meritize, a lender which looks beyond FICO scores, is an attractive alternative for student loan borrowers. This lender considers an applicant’s academic or military achievements to enhance credit worthiness and improve loan options. ResidentScore, Transunion’s unique scoring model – used by landlords to screen renters – identifies the characteristics of renters least likely to default on rent payments by using actual rental outcome data to predict the likelihood of evictions.
Though Loop is currently tackling affordable and equitable access in the auto insurance market, their mission could be applied to other insurance markets. While it can be argued that bias will continue to exist in AI – since code is programmed by people, who bring their biases into a digital framework – committing resources and taking actionable steps to address inequity for all will provide insurers with increased trust from traditionally excluded consumers, resulting in affordable options by which consumers can protect themselves against the daily risks of living and increased revenue for insurers. This is truly a win-win situation for all stakeholders.