Generative AI is supercharging insurance fraud by making it easier to falsify accident evidence at scale and in rapid time. Insurance fraud is a pervasive and costly problem, amounting to tens of billions of dollars in losses each year. In the vehicle insurance sector, fraud schemes have traditionally involved staged accidents, exaggerated damage, or forged documents. The rise of generative AI, including deepfake image and video generation, has introduced new methods for committing fraud at scale. Fraudsters can now fabricate highly realistic crash photos, damage evidence, and even fake identities or documents with minimal effort, exploiting AI tools to bolster false insurance claims. Insurers have begun deploying countermeasures such as AI-based deepfake detection software and enhanced verification processes to detect and mitigate these AI-driven scams. However, current mitigation strategies face significant limitations. Detection tools can suffer from false positives and negatives, and sophisticated fraudsters continuously adapt their tactics to evade automated checks. This cat-and-mouse arms race between generative AI and detection technology, combined with resource and cost barriers for insurers, means that combating AI-enabled insurance fraud remains an ongoing challenge. In this white paper, we present UVeye layered solution for vehicle fraud, representing a major leap forward in the ability to detect, mitigate and deter this new wave of fraud.

Amazon is splashing out on new vehicle inspectors to watch for damage or wear to its vast fleet of delivery vans--and they're not human. The retailer is installing camera-studded inspection stations equipped with artificial intelligence-powered technology called AVI, or automated vehicle inspection, at hundreds of its distribution centers worldwide. When a driver working out of any of the 20 delivery centers currently equipped with the tech returns their vehicle at the end of a shift, they slowly drive it through a sensor-laden archway made by startup UVeye, which has headquarters in the US and Israel. The technology is made up of three separate high-res camera systems: One scans a vehicle's undercarriage, another checks tire quality, and another focuses on the vehicle exterior. The data they gather is compiled into a 3D image of the vehicle and used by machine-learning software to identify whether the vehicle is damaged or needs maintenance.

Fox News correspondent Grady Trimble has the latest on fears the technology will spiral out of control on'Special Report.' This is what you call speedy service. UVeye is a new system that uses artificial intelligence to perform multi-point vehicle inspections in seconds, saving hours of work compared to traditional methods. "It's kind of like an MRI for your car," UVeye Chief Marketing Officer Yaron Saghiv told Fox News Digital. The technology uses computer vision and deep learning originally developed in Israel as a security system that could scan below vehicles for explosive devices and other smuggled items.

General Motors is bringing artificial intelligence into the vehicle inspection process. The automaker is making an undisclosed "strategic investment" in Israeli startup UVeye, which makes vehicle diagnostic systems that use sensors and AI to quickly identify damaged parts or maintenance issues. The investment in UVeye was made by GM Ventures, the automaker's venture fund, which also has investments in a variety of other AI-themed startups. As part of the collaboration, GM will sell UVeye's technology to its dealer network to upgrade their vehicle inspection systems. GM will also work with UVeye on a variety of vehicle inspection technology projects involving used car auctions, fleet operations, and automotive dealership sales.

This is a fascinating discussion on how UVEye is applying computer vision and machine learning to vehicle inspection for use cases such as terrorism prevention. Sramana Mitra: Let's start by introducing our audience to yourself as well as to UVEye. Amir Hever: I'm the Co-Founder and CEO of UVEye. We are introducing to the market the new standard of inspection. There are a lot of different use cases to understanding the exterior or expanse of a vehicle that range from security to commercial. That includes car manufacturers, public transportation, rental companies, and insurance companies. Sramana Mitra: Let's take three customer use cases that illustrates three different aspects of how you create value. You choose whatever you want to highlight. Amir Hever: The first use case would be the one that we started with. It was a security organization trying to understand whether the vehicle was modified, especially in the undercarriage. If someone attaches something to the

An Israel start-up has created an inspection technology based on artificial intelligence to check cars for problems and defects. FREMONT, CA: The Tel Aviv-based Israeli company, UVeye provides high-end solutions for automatic external inspection of vehicles, using advanced technologies. Recently they have introduced a smart-machine inspection service driven by AI. The company raises 31 million USD to expand AI-driven inspection systems since 2017. The new artificial intelligence-based system will thoroughly inspect a moving car in three to four seconds. It will end those nasty damage arguments at the rental-car return counter by checking any kind of fluid leak and for dents or defects as small as 0.08 inch.

Intelligent machines may not be driving us to the movies yet. But a small Israeli company called UVeye has created a smart-machine inspection service that should help end those nasty damage arguments at the rental-car return counter. "It started out as a smuggling and bomb-detection inspection system," explains CEO Amir Hever. Then it leapt over to the auto industry. Hever tells us that his artificial-intelligence-based system can fully inspect a moving car in three to four seconds for any kind of fluid leak and for dents or defects as small as 0.08 inch. That's very significantly faster than a human can inspect a vehicle.

Amir Hever was driving into a government facility a few years ago when he discovered a huge flaw in their security process. As he approached the entrance gate, a security guard dropped to his knees to look underneath his vehicle. "When he stood up, I asked him what he was looking for," said Hever, CEO and co-founder of computer vision startup UVeye. "The security guard answered honestly that he was looking for threats but actually couldn't see anything. That's when I realized that something wasn't working right."

UVeye, an Israeli startup that is building computer vision and machine learning technology to be used to help detect security threats by scanning the underside of passing vehicles, has raised $4.5 million in seed funding. The round was led by Ahaka Capital, with participation from angel network SeedIL. Initially being applied to roadside security -- such as stopping car bombs or drugs smuggling -- UVeye's tech claims to be able to analyse any vehicle from underneath to identify and detect threats that would otherwise be concealed to the human eye, even as it is moving, up to 28 MPH, apparently. It does this using "strategically angled and synchronised hi-res cameras" to build a 360 degree digital model, and says that three seconds after a vehicle passes over UVeye's ground installed device, the system is able to process multiple images to create a 3D model of the undercarriage and provide high resolution full colour visuals to rule out any security risks. This is also where UVeye's combination of vehicle manufacture-supplied data and machine learning kicks in, which can compare and track characteristics of different vehicle models for differentiators, such as weight and part placement.