Insurtech Trends: AI, Regulation, and Strategic Transformation in U.S. Insurance

Tanguy Catlin, a senior partner at McKinsey & Company specializing in insurtech, outlines several fundamental challenges facing the U.S. insurance industry. He notes that while the industry historically grew through personal lines, much of this growth was driven by rising premium prices rather than increased exposure. This pricing approach has contributed to affordability issues, leaving many consumers without adequate coverage, particularly in the face of large-scale catastrophes where insurers cover less than half of total losses. Catlin identifies three core problems: the industry's complexity creating poor customer experiences, insufficient coverage of actual risks, and minimal productivity gains compared to other sectors. Over the past 30 years, insurance productivity has only increased by about 3%, significantly lagging the average 50% improvement seen in other industries. Emerging technologies, including generative AI and agentic AI, present opportunities to address these systemic issues. They can enable more personalized insurance products, enhance risk prediction, and improve operational efficiencies. However, Catlin stresses that technology alone cannot close coverage gaps; regulatory constraints such as price caps and restrictions on underwriting practices also heavily influence market dynamics. For example, in California, regulations limit price increases and restrict risk-based pricing, leading some carriers to exit markets. The integration of technology into insurance requires thoughtful strategic decisions. Companies must balance reducing technical debt, investing in data capabilities, and deciding whether to build proprietary agentic AI platforms or adopt third-party solutions. Catlin warns of risks like vendor lock-in and unintended data sharing that could disadvantage carriers competitively. Insurers are increasingly leveraging technology to provide risk mitigation tools, such as predictive maintenance for water damage or distracted driving prevention. These innovations can reduce claim frequency and lower costs, potentially translating to more affordable premiums and improved coverage availability. Catlin highlights the importance of creating flexible, open architecture platforms that can evolve with technological advancements and support a mix of built and sourced software. Given the nascent state of many AI-driven insurance technologies, carriers face strategic trade-offs between early adoption benefits and long-term control. Overall, this analysis underscores an urgent need for the insurance industry to transform through technology and regulatory adaptation to better serve societal needs, improve customer experiences, and drive sustainable productivity growth.