Potential AI Errors: A Looming Challenge for Insurers
Potential AI Errors: A Looming Challenge for Insurers
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Industry experts are signaling a potential risk for underwriters due to claims arising from inaccuracies produced by artificial intelligence (AI), likening it to the "silent cyber" phenomenon of the past.
Clyde & Co partner, Darryl Smith, highlights the issue, emphasizing how AI inaccuracies could impact various insurance policies, sometimes without immediate detection.
The comparison to "silent cyber" recalls previous instances when insurers faced substantial losses because cyber incidents like ransomware were unintentionally covered by non-cyber policies. Mr. Smith advises that policy proposal and renewal forms should scrutinize the use of AI by asking specific questions about its application and purpose.
While AI is becoming integral to a wide array of professional services, its reliability varies, and errors can lead to significant insurance claims. These concerns mirror those previously seen with cyber risks, and although solutions such as exclusions might deter policyholders, they could also lead to new opportunities for tailored coverage solutions.
The potential vulnerabilities mainly threaten professional indemnity and errors and omissions policies, as errors often remain unnoticed for extended periods, potentially intensifying the impact of claims. Furthermore, directors’ and officers’ policies may also face risks of claims related to intellectual property breaches, defamation, or misuse of personal information.
In the future, the insurance sector might evolve to establish dedicated AI policies, minimizing unforeseen exposures similar to the asbestos precedent, which, despite not receiving any premiums, resulted in substantial costs to insurers. AI remains a pervasive factor within numerous organizations, and any associated errors could lead to significant claims.
In navigating this landscape, insurers are encouraged to proactively address these issues and explore new insurance policy structures to safeguard against unanticipated AI-related claims.
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Knowledgebase
Loss Ratio: The ratio of claims paid by an insurer to the premiums earned, used as a measure of profitability.