Abstract: Vehicle insurance fraud has become a significant challenge in the insurance industry, leading to financial losses and delayed claim processing. This paper presents the design and development of a Vehicle Insurance Automation System using Forensic Analysis, aimed at improving claim verification accuracy and reducing fraudulent activities. The system integrates image forensic techniques and machine learning models to automatically analyse accident-related vehicle images submitted during insurance claims. Digital forensic methods such as Error Level Analysis (ELA), metadata examination, and image consistency verification are used to detect tampering or manipulation.

Keywords: Vehicle Insurance Automation, Fraud Detection, Image Forensics, Damage Detection, Claim Verification.

Downloads: | DOI: 10.17148/IARJSET.2026.13337