Webinar: Decoding AI in the Global Insurance Industry

May 17, 2024
5 min read

The webinar "Decoding AI Regulation in the Global Insurance Industry" discussed the growing importance and challenges of AI in the insurance sector, with a focus on regulation, risk management, and the unique landscape across different jurisdictions.

- The session opened with a brief introduction, highlighting the increasing significance of AI in insurance, its projected $1.1 trillion annual value, and its application areas, such as underwriting, fraud detection, and claims management.

- AI poses risks like reputational damage, legal liability, and challenges in a rapidly evolving regulatory environment.

- Armilla AI's role in the industry was introduced, emphasizing its tech-based AI assessments and risk transfer programs.

Key Discussions:

EU AI Act:

- Dennis Noordhoek, Director of Public Policy & Regulation at The Geneva Association detailed the EU AI Act's three-tier risk model (unacceptable, high, and low risk).

- Insurance falls under the high-risk category, especially in life and health sectors, requiring stringent regulatory compliance.

- The Act's timeline was discussed, with full implementation expected 24 months post-publication.

UK Regulatory Approach:

- Charlotte Clark, Director of Regulation at The Association of British Insurers described the UK's pro-innovation and sectoral approach.

- The UK's strategy focuses on integrating AI within existing regulatory frameworks rather than creating new cross-sectoral legislation.

- Emphasis on promoting innovation, consumer protection, and robust governance.

US Regulatory Landscape:

- Kathleen Birrane, Maryland Insurance Commissioner and NAIC Innovation, Cybersecurity and Technology Committee Chair and Lindsey Klarkowski, Director of Data Science & AI/ML Policy at The National Association of Mutual Insurance Companies explained the NAIC's model bulletin, promoting a principles-based approach to AI regulation.

- The US approach involves contextual education for regulators and establishing governance and risk management frameworks for AI use in insurance.

- Discussion on the challenges of dual regulation, the need for uniform standards, and ongoing efforts to address third-party data and model vendors.

Panel Observations and Advice:

- Common themes included the importance of governance, risk management, and testing for bias and fairness.

- Significant differences remain in how jurisdictions handle AI regulation, impacting multinational insurers and insurtech vendors.

- Recommendations for companies included engaging in policy discussions, understanding jurisdictional nuances, and ensuring transparency and effective communication in AI practices.

Conclusion:

- The panel emphasized the need for ongoing collaboration and dialogue among regulators, insurers, and stakeholders to navigate the evolving AI regulatory landscape effectively.

- Building trust through transparency, robust governance, and continuous learning from various regulatory approaches were highlighted as critical for the industry's future.

Watch now on YouTube

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