prernamittal/FraudTransactionsDetection
Fraud transaction detection model using machine learning techniques, trained on an imbalanced dataset.
This project helps financial institutions automatically spot fraudulent transactions in real-time, preventing losses and enhancing security. It takes raw transaction data, like amounts, times, and account details, and identifies suspicious activities. Financial fraud analysts, risk managers, and operations engineers in banking, e-commerce, and insurance would find this useful.
No commits in the last 6 months.
Use this if you need a system to proactively detect and block suspicious financial transactions across various platforms, from banking to e-commerce.
Not ideal if you are looking for a system to investigate fraud after it has occurred without real-time prevention capabilities.
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Last pushed
May 14, 2023
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