Insurtech funding falls 44.6% as mega-round activity slows: Gallagher Re

Global Insurance technology funding fell 44.6% quarter-on-quarter to $1.36bn in Q3 2026, driven primarily by a decline in mega-round activity, according to Gallagher Re.

Funding from rounds of $100m or more dropped from $1.67bn in Q2 to $660m in Q3, accounting for most of the reduction in overall investment.

Deal activity remained broadly stable, with 104 transactions completed during the quarter compared with 107 in Q2.

AI-focused businesses continued to dominate activity, attracting 83.2% of all InsurTech funding.

These companies raised $1.13bn across 72 deals during the quarter.

Andrew Johnston, global head of insurtech at Gallagher Re, said: “The headline decline in funding tells only part of the story. Q2 was boosted by an unusually large concentration of mega-round transactions, so a moderation in Q3 was always possible.

“What the underlying numbers actually show is a market that remains remarkably resilient. Deal activity was broadly unchanged, early-stage funding recovered, and AI-focused companies continued to attract the overwhelming majority of available capital.”

Early-stage funding increased 20.1% quarter-on-quarter to $317.3m.

The share of deals involving US-based InsurTechs also reached a record 64.4%, while US investors represented 75.9% of the active InsurTech investor population.

Re/insurance companies backed 25 technology investments during the quarter, although Gallagher Re said insurer-backed deal activity remained well below prior-year levels.

AI moves deeper into underwriting

The report also examined the growing use of AI across credit risk protection, trade finance insurance, financial protection and hedge insurance.

Gallagher Re said these classes have historically depended on fragmented financial, economic and behavioural data, creating opportunities for AI to improve underwriting accuracy, risk monitoring and pricing.

Johnston said: “Some insurance classes have always been constrained by the quality, availability and timeliness of data. Credit insurance, trade finance and financial protection are all examples where underwriters have traditionally had to make decisions using incomplete information.

“AI creates the possibility of moving those markets from being primarily reactive to increasingly predictive. That does not remove the need for underwriting judgment, but it can give insurers a far richer understanding of risk and help them identify deterioration or opportunity much earlier than was previously possible.

“The firms creating the most value are not necessarily inventing entirely new products. Many are using AI to make long-established classes of business more accurate, more efficient and more scalable,” he added.