RP-333/Fraud-Analytics-with-AI-ML
Comprehensive portfolio showcasing AI/ML applications in fraud detection, including foundational EDA, transaction fraud, identity fraud, and KYC/AML compliance systems.
This project offers practical, AI-driven solutions to detect various types of financial fraud and ensure regulatory compliance. It takes in transactional data, identity information, and behavioral patterns to identify suspicious activities like check kiting, identity theft, or deepfake-based fraud. Financial institutions, risk analysts, compliance officers, and fraud prevention teams can use this to enhance their fraud detection capabilities.
No commits in the last 6 months.
Use this if your organization needs to build or improve systems for identifying and preventing financial fraud, including transaction fraud, identity theft, or compliance breaches.
Not ideal if you are looking for a general-purpose machine learning library outside of financial crime detection.
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Jupyter Notebook
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Last pushed
Jul 01, 2025
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