Credit card fraud detection

Credit Card Fraud Detection is a system designed to identify suspicious and unauthorized transactions using advanced technologies like machine learning. The main aim of this project is to protect users from financial loss by detecting fraud in real time. The system analyzes transaction data such as amount, location, time, and spending patterns. By learning from past transaction records, it can differentiate between normal and fraudulent activities. When unusual behavior is detected, the system raises an alert or blocks the transaction to prevent misuse. This project uses data preprocessing, feature selection, and classification algorithms to improve accuracy. Common techniques include logistic regression, decision trees, or neural networks. The model is trained and tested using datasets to ensure reliable performance. Overall, this system helps banks and financial institutions enhance security, reduce fraud risks, and build customer trust by ensuring safe and secure digital transactions.

Built With

• flask
• javascript
• mangodb
• matplotlib
• mysql
• numpy
• pandas
• python
• seaborn
• sql
• tensorflow