Gallagher Re's quarterly insurtech report finds that AI-driven predictive models are increasingly relevant to credit insurance, trade finance and political risk underwriting, while investment into the insurtech sector declined sharply in the third quarter.
Key findings from the report
- Gallagher Re highlights that machine learning systems can provide early-warning tools for sovereign default risk similar to models used for natural catastrophe analysis. The report cites Tellimer's technology as an example: Tellimer has identified 26 of 28 sovereign eurobond defaults since the 2008 global financial crisis, and in some cases signalled warning signs up to 48 months before the actual default.
- The report notes that traditional credit-rating frameworks have struggled to foresee certain events, and the industry has paid an estimated $25–50 billion in claims in this area since 2008.
- Wider adoption of data-driven predictive models could reduce dependence on credit-rating agencies and improve the profitability of these insurance lines.
Market moves and strategic responses
- Gallagher Re points to the strategic importance of risk-assessment software and workflow automation for modernising insurance operations. As an example, Duck Creek Technologies acquired UK-based insurtech Send in July, illustrating consolidation and a focus on simplifying operational processes.
- In response to market developments, Gallagher Re launched a new digital-risks business unit led by Ian Newman, its cyber insurance head. The unit will focus on AI-related risks affecting infrastructure, data centres and cloud-based software.
Investment numbers and trends
- Insurtech investment fell almost 47% quarter-on-quarter in Q3 to $1.36 billion.
- Insurers completed only 25 technology investments in Q3, about half of the 51 deals a year earlier.
- 83.2% of invested capital went to companies focused on artificial intelligence, with most funding coming from private equity and venture capital funds.
- About 42% of deals were seed and angel investments.
- US-based insurtech firms accounted for 64% of transactions.
Why this matters
The spread of predictive AI models could materially change how credit and political risk is underwritten—leading to earlier signals, better risk selection and potential cost savings. At the same time, the drop in funding and weaker early-stage financing suggest investors are being more selective, a dynamic accentuated by an unusually large Q2 benchmark of a few very large transactions.
Conclusion
Gallagher Re's analysis indicates that AI is becoming a core tool for risk managers in credit-related insurance lines, but the evolving investment landscape points to a period of consolidation and selective capital deployment. Insurers and insurtechs will need to integrate predictive models into underwriting workflows while navigating a more cautious funding environment.
Source: Reuters
Cover image: illustrative.
