Identifying unauthorized transactions from credit cards or Mobile Financial Services (MFS) is a growing challenge. As more people in Bangladesh and around the world use these services for their convenience, the risk of fraud and theft increases. Thieves and hackers are constantly finding new ways to steal money by making transactions that the card or account owner didn’t approve. The main problem is detecting these unauthorized transactions quickly and accurately among the many legitimate transactions that happen every day. The task is to develop a technological solution that can spot these fraudulent activities in real-time. This system must be smart enough to tell the difference between usual spending patterns and suspicious activities that could indicate a theft. It should use advanced data analysis and machine learning to learn from past transactions and get better at identifying what kind of behavior suggests a transaction might be unauthorized. Moreover, this solution needs to be user-friendly, alerting account owners immediately when a suspicious transaction is detected, without causing unnecessary alarm for normal transactions. It also must respect users’ privacy and secure their personal information. In summary, we’re looking for a technology-based approach to protect people’s money in their credit cards and mobile financial accounts by instantly identifying and responding to unauthorized transactions, making digital finance safer for everyone.