AML Checker detection and analysis tools for cryptocurrency transactions using machine learning and blockchain data. Ensuring compliance and reducing money laundering risks.

Open-source Python toolkit for AML detection and financial crime analytics — transaction graph analysis, anomaly scoring, SAR pattern matching, and SQL helpers for BSA/FinCEN compliance.

Automation of KYC process

Financial Intelligence Unit (FIU) case study on the PaySim synthetic transactions dataset. Featuring SQL and Python (Pandas, NumPy, Scikit-learn, Matplotlib) workflows for anomaly detection, AML threshold analysis, and financial crime data visualization.

Graph neural network system that detects money laundering, fraud patterns, and security threats in blockchain transactions and smart contracts.

Analytical portfolio demonstrating transaction monitoring, judgment-based alert review, and Excel-driven risk analysis across fraud, AML, and KYC workflows, with a focus on regulator-safe decisioning and operational consistency.

Automated regulatory reporting system for CTR, FTR, STR, and SAR submissions to NFIU.

🔍 Analyze transaction data to identify fraud risks, streamline alert reviews, and ensure compliance in AML and KYC contexts using Excel-driven techniques.