Detecting and Preventing Fake Cheque Scams

Abstract - Fraud by cheques is a considerable problem in the financial world that causes tremendous loss of money. This project focuses on the problem by suggesting that a system for detecting and discouraging fraud via cheques incorporate Optical Character Recognition (OCR), machine learning, and pattern study. The system detects anomalies in cheque information, authenticates the same, and sends out signals for fraud possibility. The aim is to promote financial security and minimize scams relating to cheque transactions. The suggested system combines automation with smart anomaly detection, such that it offers a scalable, efficient, and reliable solution for cheque verification. The novelty comes from the fusion of OCR and machine learning algorithms to automate cheque fraud detection, providing a proactive solution to combat cheque fraud. The benefits are improved accuracy, quicker detection, and less human intervention, making financial transactions using cheques more confident for users.