A new report from Gallagher Re has revealed that Q1 2024 global InsurTech funding dropped 17.3% quarter on quarter to $912.3 million, though deal count climbed to 107, indicating that frequency and interest are not waning, but the average check size per deal is decreasing.
As per the reinsurance broker’s Global InsurTech Report, Q1 2024 was the lowest quarter of funding in four years, largely attributable to a lack of mega-round deals. The average InsurTech deal size also fell below $10 million for the first time since Q3 of 2017.
However, the deal count climbed to 107 in Q1 of 2024 from 100 in the previous year, and early-stage InsurTech funding increased 26.5% quarter on quarter, reportedly “countering” the broader picture.
(Re)insurers also continued to invest in InsurTechs in Q1, securing 37 private technology investments, down slightly from 41 in Q4 2023, but up from 30 year on year.
Andrew Johnston, Head of Global InsurTech, Gallagher Re, commented, “Since the InsurTech investment peak in 2021, we have continued to see a funding reset.
“With activity up but average deal size down, investors are becoming more democratic in their funding allocations and spreading capital more evenly among companies. This has resulted in a more sustainable InsurTech market.”
According to Gallagher’s report, from Q4 2023 to Q1 2024, Property & Casualty InsurTech funding fell by 22.5% and the deal count dropped by six. Life & Health InsurTech funding also dropped by 4.7% quarter on quarter, but the deal count increased by 54.2% over the same period.
Meanwhile, AI-centered InsurTechs in Q1 2024 are said to have accounted for 28% of all deals and saw a slightly higher average deal size ($10.5 million) than overall InsurTechs ($9.8 million).
Gallagher Re noted that 16 of the 30 AI-centered InsurTech deals went to early-stage companies, with average deal sizes of $6.1 million – more than $2 million larger than InsurTechs that were are not AI centered.
On this, Johnston noted, “The focus on AI this year will help guide businesses through the daunting task of understanding the principles of AI, its various subcomponents, and ultimately what advantages can be gained from its application.”
