financial-risk

This project studies the effects of the shape parameter estimator uncertainty at different threshold levels on the value-at-risk confidence interval for quantitative risk management (QRM) using the Generalized Pareto Distribution (GPD) from the Extreme Value Theory (EVT) approach.

Evidence-grounded financial risk analysis from corporate filings, combining constrained LLM interpretation, deterministic analytics, versioned rules, and auditable evidence trails.

A股个人择时选股系统 — 三级择时漏斗 × 财务排雷 × 量化策略引擎 | FastAPI + Next.js 16 + SQLite

Climate physical-risk analysis, hands-on. Jupyter notebooks for the Alpha-Klima platform API - hazard screening, asset-level impact, real-estate portfolios, and bank Pillar 3 / ECB pipelines.

An risk prediction LLMs system that analyzes 31 multi-dimensional domain signal.

The significance test for Granger causality of financial risks in stock indices

Completed as part of the 365 Data Science Credit Risk Modeling in Python Udemy course. Developed an end-to-end credit risk modeling pipeline for consumer lending, covering data preprocessing, feature engineering, Probability of Default , Loss Given Default , Exposure at Default , scorecard development, model validation, population stability

🔐4- Cybersecurity -Social Engineering - Modular end-to-end AI-powered risk intelligence infrastructure for banking and fintech incidents analytics, integrating semantic analysis, interactive dashboards, APIs and LLM-powered insights to support governance, compliance and regulatory decision-making.

🏦 Machine Learning system for credit default prediction using a RandomForestClassifier. Features an end-to-end pipeline including synthetic financial data generation, robust preprocessing (ColumnTransformer), and comprehensive evaluation with ROC-AUC and Confusion Matrices.

Excel and Power BI-ready fraud analytics portfolio featuring synthetic banking transactions, explainable risk scoring, investigation tracking, SQL analysis, and an executive dashboard.

Data-driven optimization of Teradyne’s excess inventory approval process using Python, lead-time adjusted demand modeling, and financial risk analysis to improve capital efficiency and reduce excess spend.

Financial-risk prediction experiments comparing point and interval features, with temporal validation and synthetic-data benchmarks.

Autonomous financial risk intelligence platform, SEC EDGAR ingestion, Isolation Forest anomaly detection, Benford's Law forensic analysis, corporate network graph, SHAP explainability, and Gemini AI analyst. Built with DuckDB, dbt, and Streamlit.

Python-based financial risk analysis covering transaction behaviour, customer profiling, risk identification, and statistical analysis.

Credit risk & campaign analytics dashboard — Power BI, DAX (55+ measures), Python EDA, SQL. Interactive HTML dashboard live on GitHub Pages.

Cost-sensitive loan default prediction using Python and machine learning, with threshold optimization, business cost simulation, model interpretation, and responsible AI considerations.

End-to-end credit risk modeling workflow for probability calibration, temporal validation, and business-aligned risk segmentation.

Batch financial risk scoring and Isolation Forest anomaly detection project using Python, SQL, and BI-ready outputs.

A structured collection of 38 educational flowcharts covering model validation, model risk management, governance, quantitative methods, and validation decision workflows.

4-agent AI pipeline for financial risk classification using NLP, RAG, sentence embeddings and LLM (Qwen3). Built with Python, HuggingFace and scikit-learn.