shakiliitju/Credit-Card-Fraud-Detection-Using-Machine-Learning
Credit card fraud is a significant problem, with billions of dollars lost each year. Machine learning can be used to detect credit card fraud by identifying patterns that are indicative of fraudulent transactions. Credit card fraud refers to the physical loss of a credit card or the loss of sensitive credit card information.
This project helps credit card companies and financial institutions automatically spot suspicious transactions in real-time. By analyzing historical transaction data, it identifies patterns that indicate fraud, allowing you to flag potentially fraudulent activity. The output is a clear indication of whether a transaction is legitimate or fraudulent, designed for fraud analysts and risk management teams.
No commits in the last 6 months.
Use this if you need a way to quickly and accurately identify fraudulent credit card transactions to protect customers and minimize financial losses.
Not ideal if you require a solution that incorporates real-time geolocation data or other external data sources beyond transaction details.
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67
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49
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 07, 2024
Commits (30d)
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