The International Association of Insurance Supervisors (IAIS), a global representative body for insurance sector supervisors and regulators, is seeking industry feedback on a new paper designed to support regulators in overseeing artificial intelligence (AI) adoption and use by insurers.

While not a standards setter per se, the application paper offers guidance to assist regulators with the creation of relevant supervisory material, including advice, illustrations, recommendations and examples of good AI use practice, based on the IAIS’s current Insurance Core Principles (ICPs).

The paper’s objective, effectively, is to support supervisors to promote appropriate and globally consistent oversight of the use of AI within the insurance sector.

“The application paper reinforces the importance of the ICPs, outlining how existing expectations around governance and conduct remain essential considerations for supervisors and insurers using AI,” IAIS wrote.

“Furthermore, noting that AI can amplify existing risks, this paper emphasises the importance of continued board and senior managers’ education to establish robust risk and governance frameworks to ensure good consumer outcomes.”

The application paper covers four broad sections:

• Governance and accountability: including the need to integrate AI into risk management systems, provide human oversight of AI risks and considerations around the use of third parties.
• Robustness, safety and security: considering issues related to the robustness, safety and security of AI systems.
• Transparency and explainability: setting out requirements for AI outcomes to be explainable and tailored to the needs of different stakeholders.
• Fairness, ethics and redress: setting out principles for fairness by design, monitoring of outcomes and adequate redress mechanisms. It also highlights the need for supervisors and insurers to consider the broad societal impacts of granular risk pricing on the principle of risk pooling.

The IAIS underscored both the opportunities and risks associated with AI implementations, noting the potential for AI systems, when left unchecked to “reinforce historic societal biases or discrimination and, for individuals, can increase concerns around data privacy”.

“For insurers, the opaque and complex nature of some AI systems can lead to accountability issues, where it becomes difficult to trace decisions or actions back to human operators, and uncertainty of outcomes (particularly in a changing external environment).

“Addressing such concerns is paramount to maintaining trust and fairness in the industry.”

Feedback on the applications paper must be submitted before 17 February 2025.