Deepfakes: Insurance Fraud Has Never Been Easier

As the use of artificial intelligence (AI) becomes more prevalent in the insurance industry, it is important to consider the potential for AI to be a causative reason for a rise in insurance fraud. One particular concern is the use of deep fake car accident videos and fake photographs regarding fake vehicular damage, which can easily be submitted via self reporting ENOL services.

Deep fake technology has made it easier than ever to create convincing fake videos and images. In the context of insurance fraud, this means that fraudsters can create fake car accident videos or photos in order to make false claims on their insurance policies. They might, for example, create a video that shows a car being rear-ended, or a photograph that shows extensive damage to a vehicle.

The problem with deep fake technology is that it can be very difficult to detect. Even experts can struggle to distinguish between a real video or image and a deep fake. This means that insurance companies may be more vulnerable to fraudulent claims than ever before.

Fortunately, technology is evolving to help detect deep fake videos and images. Researchers are developing AI-powered tools that can analyze videos and images to determine whether they are authentic or not. These tools are based on machine learning algorithms that have been trained on vast amounts of data, allowing them to identify patterns and anomalies that may indicate a fake.

To that end, we have quickly adopted new technology that is able to detect deep fake videos by analyzing the way that light and shadows move across the image. A real video will have consistent lighting and shadows that move in a predictable way, while a deep fake may have inconsistencies that reveal it as fake.

Similarly, when it comes to fake photographs of vehicular damage, our AI-powered tools can be trained to detect inconsistencies in the damage patterns. A real accident will leave a particular pattern of damage on a car, while a fake image may have damage that is inconsistent with the laws of physics or the nature of the accident. (Think of the old school airbrushed images, where a female celebrity has an unusually slim waist, which distorts the background, or another where a male has strangely large biceps and chest muscles, but the background appears at odds with the rest of the image)

As AI technology continues to advance, it is likely that these tools will become even more effective at detecting deep fake videos and images. This will help insurance companies to prevent fraudulent claims and ensure that they are only paying out on legitimate claims.

In conclusion, the rise of deep fake technology presents a real challenge for the insurance industry, but it is not an insurmountable one. By using AI-powered tools to detect fake videos and images, insurance companies can protect themselves against fraudulent claims and ensure that they are providing fair and accurate coverage to their policyholders.