AI fraud detection catches photo forgery in $7 trillion insurance market
Allianz rejected a £1,000 van repair claim in 2024 after discovering the damage photo had been edited. The customer had lifted an image from social media and altered it to show fake damage. The insurer's fraud team caught the scheme, but the incident underscores a growing problem: as AI tools make image manipulation easier, insurance companies need better ways to spot fakes.
Startups are building those tools now. Ravin, an Austin-based company, uses AI vision models to verify vehicle damage through phone video scans. The system captures metadata about location and timing, making it harder for fraudsters to submit doctored images.
"Insurance companies increasingly accept images as evidence," said Eliron Ekstein, Ravin's founder and CEO. "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 scale of the opportunity
The insurance industry is a $7 trillion market still built on manual workflows. Underwriters draft contracts by hand, assess risk through lengthy applications, and process claims one at a time. Public trust in insurance ranks lower than every major consumer industry except social media.
That combination-massive scale, manual processes, and regulatory pressure-attracts venture capital. Global insurtech funding rose 19.5% in 2025, with 78% of that money targeting AI-centered companies in the final quarter, up from 42% a year earlier.
The financial upside is clear. "Some insurance companies underwrite in the tens of billions of dollars, so every little improvement can really help," Ekstein said.
AI-native carriers enter the market
Corgi Insurance became the first AI-native insurance carrier to win U.S. regulatory approval in July 2025. Since then, the San Francisco company has scaled to more than $40 million in annual recurring revenue.
Corgi replaced the labor-heavy workflows that traditional carriers depend on. Most competitors employ more than 40,000 people to interpret contracts, generate regulatory reports, and assess claims. Corgi automates those text-heavy tasks using generative AI and LLM models.
The speed advantage matters to customers. "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," said Nico Laqua, Corgi's co-founder and CEO. "Humans stop working at five o'clock and they don't work weekends."
When a house burns down at midnight, customers need settlement quickly. Traditional carriers can't deliver that.
The hidden cost: compute and compliance
Speed and scale come with a catch. Insurance operates under tight regulations that demand accuracy. AI models can hallucinate or embed bias, and regulators have low tolerance for either.
Corgi runs multiple models in parallel to catch mistakes. One model generates a report; another reviews it. A third checks for bias. A fourth validates the output. This layering multiplies compute costs by a factor of four per inference call.
"We're generating a lot of reports. We're dealing with a lot of forms, a lot of paperwork," Laqua said. "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. So that's just expensive."
Ravin processes 2,000 videos daily and needs regionally compliant cloud infrastructure to handle sensitive claim data. The compute demands are substantial across the industry.
Why insurers aren't just cutting costs
Replacing 40,000 employees with 100 engineers sounds like a cost play. It's not how Corgi thinks about the business.
"The reason we use AI is not to save money," Laqua said. "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."
Corgi's bet is that better customer experience drives growth faster than labor arbitrage. Faster claims. Instant policy issuance. Real-time fraud detection. Those features attract customers and retention.
For professionals in AI for Insurance, the shift is clear: the next wave of competition won't be about who has the cheapest operations. It will be about who builds systems customers actually want to use.
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