AI Insurance: The $7 Trillion Rebuild
In 2024, Allianz received a photo of a damaged van from a customer with a £1,000 repair invoice. The fraud team investigated and found the image had been edited to show fake damage - it matched an identical photo from the customer's social media. The claim was denied.
This case illustrates why startups are now racing to build AI tools for insurance companies. The $7 trillion insurance market operates under massive financial risk, with every claim decision carrying real cost. Fraud detection, claims processing, and underwriting remain stubbornly manual. The opportunity is enormous - and so are the computational demands.
Fraud Detection Gets Smarter
Eliron Ekstein, founder and CEO of Austin-based startup Ravin, is building AI-powered damage verification tools that make it harder to fool the system with edited photos. His technology requires customers to video scan vehicle damage with their phones, collecting metadata about location and timestamp alongside images.
"Insurance companies increasingly accept images as evidence," Ekstein said. "With our technology, you can't just upload a set of images of your vehicle. You need to perform a scan that will take the images for you."
The tool protects insurers from deepfakes while speeding up payouts. Previously, damaged vehicles sat in body shops for days awaiting assessment. Now, insurers can settle claims immediately and issue checks without waiting for physical inspection.
Text-Heavy Work Suits Generative AI
Corgi Insurance became the first AI-native carrier to win U.S. regulatory approval in July 2025, and has since scaled to more than $40 million in annual recurring revenue. Co-founder and CEO Nico Laqua credits rapid growth to the text-heavy nature of insurance work.
Insurance carriers spend enormous resources drafting contracts, assessing buyers, assigning risk categories, and processing claims. Most competitors employ over 40,000 people doing repetitive, language-based workflows. Corgi automates as much as possible using Generative AI and LLM models.
"If you're using humans and a call center to do these very repetitive tasks, the customer experience is inevitably worse, because humans aren't instant," Laqua said. "Humans stop working at five o'clock and they don't work weekends."
When a house burns down at midnight, customers deserve immediate claim settlement. Only AI can deliver that speed.
The Hidden Cost: Compute for Safety
Running AI in regulated insurance comes with steep computational overhead. Unlike consumer-facing AI applications, insurance demands extreme caution around hallucinations and bias. Every error can result in regulatory fines or wrongful claim denials.
Corgi runs supervisory models alongside primary models to catch mistakes. One model checks another model's work on sensitive decisions. This layering multiplies compute costs by a factor of four per inference call.
"We use a lot of tokens, and then we need to double and triple and quadruple-check all of the work that we do because we're selling a financial product, and it needs to be correct," Laqua said. "So that's just expensive."
Ravin processes 2,000 videos daily and requires regionally compliant cloud infrastructure to handle sensitive damage data. These compute bills are substantial - but the alternative is hiring thousands of manual assessors.
Investor Appetite Grows
Global investments in insurtech rose 19.5% in 2025. In the final quarter, 78% of funding went toward AI-centered investments, up from 42% in Q4 of 2024.
Venture capital is increasingly willing to fund companies that improve customer experience rather than simply cutting costs. Corgi's strategy reflects this shift: the company uses AI not to save money, but to deliver better service than competitors who charge customers twice as much as they spend on software annually.
"The reason we use AI is not to save money. It's because right now, pretty much every single business and person in the United States spends about twice as much on insurance per year as they do on software, and the experience is just terrible across the board," Laqua said.
For professionals in insurance, understanding AI for Insurance is becoming essential to staying competitive in a sector that is finally embracing technology at scale.
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