Production-grade synthetic retail banking data generator that simulates customers, accounts, transactions, loans, cards, churn events, and customer lifecycles. Generates realistic, relational datasets at scale for Data Engineering, Analytics, Machine Learning, and MLOps projects.

Synthetic banking AI risk management control tower demonstrating AI inventory, risk assessment, mitigation planning, controls, evidence tracking, ownership, and framework mapping.

public-data macro-financial stress test for JPMorgan Chase, integrating credit risk, regulatory capital, liquidity analysis, DFAST-style scenarios and reproducibility documentation.

Interest Sensitivity (IS) Gap–based IRRBB model to analyze Net Interest Income (NII) impact under upward and downward interest rate shocks, implemented in Python with FRM-aligned methodology.

Streamlit MVP for SME loan pre-screening with credit scoring, KYC checks, and explainable Go/Review/Decline decisions.