financial-risk-analytics

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.

End-to-end Credit Risk engine using Python. Achieved 93.04% Cross-Validated Recall and 0.98 ROC-AUC. Implemented advanced preprocessing (Log/Robust Scaling) and SMOTEENN to handle class imbalance. Champion model (Logistic Regression) provides full interpretability for strategic financial risk mitigation. 🏦📈

This project analyzes 284,000+ banking transactions to detect suspicious activity using time-series anomaly detection and an Agentic AI investigation workflow.

Market Risk analysis using R language to compare VAR and Expected shortfall for single and multi asset portfolio

The project involved developing a credit risk default model using a given data which had to be checked for outliers, missing values, multicollinearity etc. Univariate and Bivariate Analysis had to be conducted and the model had to be built using Logistic Regression on most important variables. Model Performance Measures were undertaken that incl…

Calculate the return of a portfolio of securities as well as quantify the market risk of that portfolio, an important skill for financial market analysts in banks, hedge funds, insurance companies, and other financial services and investment firms.

End-to-end financial risk intelligence platform combining supervised ML, anomaly detection, agentic AI, grounded LLM review, and human-in-the-loop investigation.

Pipeline ETL modular e idempotente en Python. Transforma datos transaccionales asíncronos en artefactos Parquet con rigor analítico para riesgo financiero y Power BI.

Cost-effective analysis, financial risk protection, catastrophic expenditure; Part of GHP 501

The RAG-based Financial Risk Assessment Tool uses advanced AI models to automate financial risk assessment. By leveraging retrieval-augmented generation (RAG) techniques, the tool provides predictive insights and risk analysis for financial data, enhancing decision-making and workflow efficiency.

This project aims to build a comprehensive systemic financial risk monitoring framework to analyze the risk status of China's financial market through multiple dimensions.

A Reflexive RAG (R-RAG) framework utilizing a multi-agent consensus panel and deterministic Python sandboxing to eliminate mathematical hallucinations in SEC 10-K financial compliance auditing.

Developed a machine learning pipeline to identify fraudulent loan applications, using ensemble and oversampling techniques to handle class imbalance and achieve high detection accuracy across multiple model architectures.

Exploratory analysis of Bitcoin OHLCV with business‑framed insights and anomaly detection.

Nexus Credit Intelligence is an AI-powered platform that transforms credit risk assessment for financial institutions. It leverages advanced machine learning to deliver instant risk scoring, portfolio insights, and explainable AI, while real-time processing and intuitive dashboards enable smarter lending decisions and scalable growth.

AI-powered fraud detection and financial risk intelligence platform with real-time analytics, explainable AI, live monitoring dashboards, and machine learning-based fraud prediction.

Credit Risk And Default Analysis Using Microsoft Sql

Vedetta is the korra.finance pay-per-call market intelligence API for AI agents. It sells sentiment-vs-price divergence verdicts across crypto, US stocks and macro, live analyst answers, falsifiable predictions and a verifiable track record over the x402 payment protocol — Descriptive research, not financial advice.

Financial Risk Management