How AI steers insurers to find new risks to cover

• Resistance to disruption contributes to insurers' underperformance
• AI can issue more quotes for more complex risks
• Advanced data and modeling capabilities improve underwriting pricing

AI gives insurers the tools to grow based on finding new risks, rather than just increasing rates, according to a new report by McKinsey & Company.

The global insurance industry is underperforming and "resistant to disruption," according to the McKinsey report, which points to 4.9% annual growth in gross written premiums since 2005, but profits before tax growing only 4.3% in the same period. 

"On the commercial lines side, we're seeing complex risks that used to take two days to quote are now taking half a day to quote. The amount of quotes that you can do is much higher, and that's leading to growth," said Nick Milinkovich, partner in the Toronto office of McKinsey, and a co-author of the report. "We're seeing more of that type of AI-enabled growth."

Applying AI to real-time portfolio monitoring provides a view of risk that used to be collected only semi-annually or annually, he added. AI makes it possible for insurers to shift from being insurance payers, focused on processing claims, to being risk partners who work with insureds to prevent losses and mitigate costs and risk, Milinkovich explained.

"Two years ago, a lot of the conversations we were having with carriers were about: what are the use cases where AI might make a difference?" he said. "Now a lot of the conversations are more around where to build, how to redesign entire parts of my business to put AI at the center, and what that means for vendor strategy, tech architecture and talent."

Aside from driving the industry's shift to risk partnership, AI creates or better serves new risk categories such as cyber risk, non-physical business interruption and workforce transitions, the report states. 

In underwriting, AI makes it possible to cover climate risks, cyber risks and even AI-related risks that could not be reliably priced without AI, according to the report. 

"Better real-time data ingestion and continuous model recalibration can sharpen pricing on volatile risks," the report stated. "And improved claims accuracy — more precise reserving, earlier identification of problems, better settlement decisions — reduces the cost uncertainty that forces conservative pricing in the first place."

The pace of change that AI is driving is challenging for an industry that is naturally risk-averse, according to Milinkovich. "A lot of insurers are starting to put really clear guardrails in place around what they are trying to achieve economically with AI technology," he said.

Co-authors of the report include Jason Ralph, Sid Kamath, Johannes-Tobias Loren, Gabriella Meijer and Tanguy Catlin.