Vol: 13, Issue: 4 2023

Page: 122-130

An Integrated Quantitative Risk-Scoring Model for Financial Institutions Using Multi-Factor Indicators

Shourya Gupta

Received Date: 2023-10-08

Accepted Date: 2023-12-18

Published Date: 2023-12-24

http://doi.org/10.37648/ijtbm.v13i04.010

Financial institutions operate in an environment where credit, market, liquidity, operational, model, and conduct risks interact nonlinearly and can amplify each other through feedback loops. Traditional “silo” risk management often fails to capture these interactions, creating blind spots in capital planning, risk appetite calibration, and crisis response. Building on enterprise risk management (ERM) evidence and recent advances in stress testing, risk data governance, and board-level risk oversight, this paper proposes an Integrated Risk Management Model (IRMM) for banks and other regulated financial institutions. The IRMM combines (i) governance and accountability via an enhanced lines-of-defense structure, (ii) a unified risk taxonomy and common measurement language, (iii) scenario-driven aggregation across balance sheet and income statement, and (iv) continuous monitoring with risk appetite triggers tied to decision rights. The model is presented as a practical operating system with clear artifacts (risk appetite statements, scenario library, risk register, model inventory, capital/liquidity dashboards) and an implementation roadmap. Comparative analysis shows that IRMM operationalizes ERM principles while strengthening cross-risk aggregation and actionability, addressing gaps frequently observed in real-world ERM maturity. Empirical and conceptual literature supports the model’s expected benefits: lower default risk and improved governance quality when ERM is effectively implemented [2], [1], and improved performance when risk committees are strong and structurally capable [3].

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