Abstract :

This Study, Titled Quantitative Risk Management In Financial Institutions At State Bank Of India, Evaluates The Mathematical Modeling Frameworks, Credit Risk Dynamics, And Capital Adequacy Reserves Maintained By Indias Largest Public Sector Lender. Quantitative Risk Management (QRM) Is Essential To Preserve Banking Solvency Across Credit, Market, Operational, And Liquidity Risk Vectors. This Research Explores The Financial Performance And Risk Configurations Of State Bank Of India (SBI) Over A 5-year Project Lifecycle (2021-2025) Of An Automated Quantitative Risk Appraisal Engine Designed To Track Basel III Adequacy Indicators. Feasibility Is Evaluated Using Standard Capital Budgeting Techniques: Net Present Value (NPV), Internal Rate Of Return (IRR), Payback Period (PBP), And Benefit-Cost Ratio (BCR). Quantitative Metrics Demonstrate That Credit Risk Accounts For 75% Of Risk Weighted Assets (RWA). Transition To Quantitative Models Helped SBI Reduce Its Gross NPA Ratio From 4.90% To 1.80%, While Strengthening Its Capital Adequacy Ratio (CAR) To 15.10% By 2025. Market Risk Backtesting Shows Zero Breaches Of Value At Risk (VaR) Parameters. The Financial Evaluation Yields A Positive NPV Of 284.5 Crores And An IRR Of 38.6%, Far Exceeding The Banks WACC Of 10%. The Study Concludes That Algorithmic And Quantitative Risk Engines Are Highly Viable Infrastructure Investments, Critical To Mitigate Default Losses And Ensure Systematic Stability.

Published:

04-9-2026

Issue:

Vol. 26 No. 9 (2026)

Page Nos:

65-73

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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