Card companies lose billions of dollars annually due to fraudulent credit card transactions. A sophisticated fraud detection system with a cutting-edge fraud detection algorithm is believed to be necessary in order to reduce fraud losses. Our main accomplishment was creating a fraud detection system based on deep learning architecture. Perform a comparative analysis to evaluate the efficacy of the suggested framework using actual data from one of the biggest commercial banks. The results for the trial demonstrate the viability and effectiveness of the method we suggested for identifying credit card fraud. In terms of practice, While maintaining a respectable false positive rate, our suggested method can detect a higher percentage of fraudulent transactions than existing methods. The management value of our research is in the ability of credit card issuers to implement a recommended technique to quickly identify fraudulent transactions, safeguard client interests, and minimize fraud losses & regulatory costs.

Deep learning,Deep Belief Networks,CNN,Credit Card Fraud Detection