Car Insurance Fraud Detection Using Image Verification Techniques

Insurance fraud is a growing problem in the automobile industry that costs thousands of individuals and businesses a significant amount of money and makes claims less effective.Multi-angle verification on AI-based systems can be used to detect this type of fraud.The proposed system gathers information related to the registration of the user, and three images of the insured car (front, left, and right).It followed by verifying the authenticity of these images with an already trained machine learning model.The information about the user and AI-based image analysis will be used to help the system to distinguish between a real and a bogus claim.This will reduce losses incurred on the financial side and will improve efficiency in claims processing.Empirical research shows that the approach is an efficient means of distinguishing between valid and invalid claims.This makes it a good solution in the insurance business.The system also increases regularity and transparency of the confirmation of claim process.It also integrates easily with the available insurance systems and is scalable and verifiable in real-time.This also serves as an opportunity to open the gates to more sophisticated AI-based fraud-detection solutions in the future.