This project is focused on delving into key performance indicators (KPIs) within the Indian banking sector. As a business analyst, we are working on a comprehensive dashboard that meticulously tracks HDFC Bank's card usage metrics, allowing for an insightful comparison with its competitors.

Interactive Excel dashboard analyzing Indian banking transactions to uncover regional trends, payment insights, and fraud patterns.

This project performs a comprehensive relative value analysis on major Indian banking stocks using synthetic financial data. The analysis explores valuation metrics, fundamental performance indicators, and implements machine learning models to assess banking sector performance and inter-bank relationships.

To perform relative value analysis on major Indian banks using synthetic financial data and machine learning techniques.

To perform relative value analysis on major Indian banks using synthetic financial data and machine learning techniques.

Value at Risk (VaR) analysis using Parametric, Historical Simulation, and Monte Carlo methods for major Indian banking stocks and the NIFTY 50 using Python.

Indian Bank Branch Data API: Accurate and comprehensive API for Indian bank branches. Get bank names, branch details, contact persons, IFSC codes, and more. Filter by name or code. Perfect for fintech, banking systems, and data analysis. Updated regularly. Contributions welcome. Empower your apps with reliable Indian bank branch data.

<h1> Hello And Welcome to Nifty Bank Stock Analysis </h1> <br> <b>Nifty Bank, or Bank Nifty</b>, is an index comprised of the most liquid and large capitalised <b>Indian banking stocks</b>. <br>It provides investors with a benchmark that captures the capital market performance of Indian bank stocks. The top stocks of the index include HDFC Bank Ltd. 31.61%, ICICI Bank Ltd. 18.20%, Axis Bank Ltd.

SQL analysis of 100K Indian banking customers using DuckDB — exploring demographics, credit scores, transactions, and risk patterns

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Developed an interactive dashboard using Microsoft Excel to analyze financial performance of major Indian banks Evaluated key metrics such as revenue growth, profitability, and financial ratios Used pivot tables, charts, and slicers to create dynamic data visualizations

This project performs a comprehensive relative value analysis on major Indian banking stocks using synthetic financial data. The analysis explores valuation metrics, fundamental performance indicators, and implements machine learning models to assess banking sector performance and inter-bank relationships.

This project performs a comprehensive relative value analysis on major Indian banking stocks using synthetic financial data. The analysis explores valuation metrics, fundamental performance indicators, and implements machine learning models to assess banking sector performance and inter-bank relationships.

Financial analysis of the Indian banking sector using Python and machine learning

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Academic equity research and fundamental analysis focused on Indian private-sector banks, examining profitability drivers, asset quality and valuation logic.

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A quantitative risk assessment of India’s "Big Five" banks (HDFC, SBI, ICICI, Kotak, Axis) using Value at Risk (VaR) and Expected Shortfall (ES). This project explores the systemic stability of the banking sector in 2025 and validates a Monte Carlo model through historical backtesting.

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Change-point analysis of NPAs in Indian banking (1996–2023) to detect structural stress regimes.

Evaluating speech-to-text providers for Indian banking: methodology, metrics pipeline, and cross-provider analysis across 5 languages

AI-powered structured data extraction pipeline for Indian banking compliance and credit card product analysis using custom structured encoding.

Loan portfolio risk analysis using MySQL — credit scoring, NPA classification, CIBIL segmentation and composite risk scoring for Indian banking data

Conducted comparative analysis of deep learning and machine learning algorithms for improving the accuracy of forecasting of Indian banking stocks.

Replication materials for "Climate Migration, Night Lights, and Bank Fragility." Analysis of disaster-induced liquidity stress in Indian banking networks (2015-2024).

End-to-end SQL analysis of 100 Indian banking transactions across 40 customers and 15+ cities — uncovering spending patterns, risk indicators, and customer lifetime value.

A factor-based machine learning framework utilizing Principal Component Analysis (PCA) and Random Forest Classification to extract structural alpha and predict directional movement in the Indian Banking Sector (NSE)

A comprehensive research report analyzing the Indian Banking Industry, covering sector overview, structure, key players, financial performance, regulatory environment, SWOT analysis, and recent developments. Includes data-driven insights on top banks and industry trends for 2024–25

Comprehensive research report on the Punjab National Bank (PNB) analyzing its financial performance, operations, and market position. Covers key ratios, digital initiatives, SWOT analysis, regulatory framework, and growth outlook for 2024–25 within the Indian banking and financial services landscape.