In a recent interview with Reinsurance News, Andrew Johnston, author of the InsurTech Quarterly report series and global head of insurtech at reinsurance broker Gallagher Re, discussed how investment trends, artificial intelligence and emerging liability risks are reshaping the insurance and reinsurance markets.
First, Johnston highlighted a clear shift in funding patterns compared to recent years, suggesting continued increases in benchmark investment levels rather than volatility driven by a handful of large deals.
“We’re now seeing over $1.6 billion in funding for the second quarter in a row, which is a huge uptick from what we saw in the previous two and a half years, which was around $1.1 billion, which was incredible. And where that’s off from $1.1 billion is because there’s one or two very large individual deals going on,” Johnston said. “What we’re seeing is the beginning of a new sustained level of funding, which is $500 million more than we’ve seen in the previous two years.”
When asked about where the money is going, Johnston spoke unequivocally about the dominance of artificial intelligence. “When it comes to AI technology, about 95% of the money is going into technology with AI tools,” he commented. He explained that most of the capital is going toward tools built around machine learning and large language models, particularly those that can analyze large amounts of data and return human-like output.
He detailed the capabilities: “It can process data very quickly, or it can run very predictable models. When we talk about AI technology, we’re talking about tools that mimic human cognition, so typically tools that can consume large amounts of data and then give you human-like analysis.”
He explains that these systems are becoming more integrated into daily workflows: “For example, using some AI tools, you might upload an 800-page claim document, provide the individual’s name, reference number and details, and it will return the relevant information, just like talking to someone.”
Fraud detection is one of the most prominent use cases attracting investment. “We’re seeing a lot of tools that can verify the authenticity of an image. In some cases, people are faking images of car crashes or images of hail damage,” Johnston said. He further explained how models identify suspicious patterns: “They are trained to spot red herrings, and historically we know that if these data points all occur at the same time, there is a 70% increase in the likelihood of a fraudulent claim. Those claims are then highlighted as suspicious and then reviewed by humans.
“So there’s a lot of attention and therefore cash in the form of investment in that space and any technology surrounding it.”
Speaking about the development of AI liability insurance, Johnston described a market that is rapidly forming across the entire value chain. “It’s really growing. Now we have an emerging group of market players, from consultants, analysts, to MGAs creating products for the AI liability space, who themselves have a lot of expertise, all the way to the reinsurance market that is ready to support these MGAs and the insurance companies that offer these products.”
He draws direct comparisons to the early days of cyber insurance. “In terms of its trajectory as a theme, it’s very similar to what we saw in cyber about 10 years ago. This emerging risk category is noticing losses from the digital space, which you could say is within the traditional loss pillars, but clearly not.” He added: “I think we’re going through the exact same thing in terms of AI liability.”
Johnston emphasized that as AI adoption accelerates, new forms of risk are emerging, particularly around accountability. “Transparency in the value chain is key. If I buy a service from you and something goes wrong with that service, but you delegate what you do to an AI function, do you know where the problem starts? Where should the transparency be?”
He suggested regulatory expectations may change, explaining that regulators may one day force companies to share training manuals and modules with the public so people know exactly what sentiment analysis is being done and what biases are being done.
He also stressed that the market is still in its early stages of addressing these issues. “We’re in this embryonic stage. I think the best thing we can do is communicate and be clear.”
Regarding how insurers and reinsurers should respond, Johnston encouraged active participation in the field. “Be open to the space. Be open to education and be willing to talk to companies that are very proactive.” He added that companies should rely on their existing expertise: “When new business categories emerge, my advice to reinsurers is to always be brave and trust their underwriting instincts and portfolio management instincts.”
He concluded that opportunities could expand significantly. “I really don’t understand how they could pass up this opportunity because I think this opportunity will continue to grow and everyone will have ample opportunity to see these opportunities first hand.
“We’re seeing a lot of reinsurers being very proactive and having dedicated staff talking to their own underwriters about how this might impact their own business.”
Overall, therefore, the industry is entering a phase characterized by stronger and more consistent investment, rapid adoption of artificial intelligence, and the formation of new liability frameworks that echo early developments in cyber insurance.
