The insurance industry is grappling with the integration of big data and artificial intelligence (AI), with efforts to regulate their use being hindered by misconceptions, according to the National Association of Mutual Insurance Companies (NAMIC). NAMIC’s issue paper concludes that “unfounded notions about the effects of using big data and AI in insurance are running rampant, inappropriately serving as the basis for and inappropriately driving creation of new policy relative to risk-based pricing.”
The Role of Big Data and AI in Insurance
Big data and AI are proving to be a natural fit for the insurance world, enhancing underwriting decisions, risk assessments, and connecting producers with potential buyers. A recent LIMRA survey found that 47% of technology executives believe AI will significantly impact the insurance industry in the next three years. However, 48% of insurers lack an AI training program.
Regulatory Concerns and Challenges
The adoption of AI by insurers has raised concerns among regulators, advocates, and policymakers about proxy discrimination and algorithmic bias. While rulemaking has been slow, some states have enacted statutes regulating AI use. Colorado’s AI regulation requires life insurers to report on their AI model reviews and use of external consumer data. Other states are considering similar legislation to restrict how insurers handle personal and public data.
Insurance as a Risk-Based Industry
Lindsey Klarkowski, NAMIC’s policy vice president, emphasizes that insurance works best when underwriters accurately assess risk pools. Many AI bills “are taking a one-size-fits-all approach” without recognizing the distinct nature of insurance as a risk-based product. Klarkowski argues that precise risk profiles benefit consumers and allow insurers to take on riskier policyholders.
Legal Challenges and Existing Protections
As AI’s role in insurance grows, so do discrimination complaints. State Farm faced a class-action lawsuit alleging its AI discriminates against Black customers. Klarkowski notes that existing laws prevent discrimination, requiring rates to be actuarially sound and not unfairly discriminatory.
The issue paper, titled “Big Data, Artificial Intelligence and Risk-Based Pricing: Dispelling Five Common Myths,” aims to address misconceptions surrounding the use of big data and AI in insurance. By understanding the true potential of these technologies, the industry can work towards more effective regulation that benefits both insurers and policyholders.
