The Role of Professional Judgment in Financial Risk Management: Limitations of Formal Models and Decision-Making Under Uncertainty

Citation: Valeriia Roibu, "The Role of Professional Judgment in Financial Risk Management: Limitations of Formal Models and Decision-Making Under Uncertainty", Universal Library of Business and Economics, Volume 03, Issue 03.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This article examines the role of professional judgment in financial risk management when quantitative models provide incomplete, unstable, or contextually ambiguous decision support. The study integrates a structured review of recent research on model risk, credit-risk assessment, probabilistic forecasting, explainable machine learning, and behavioral finance with a comparative analysis of two organizational settings: receivables management during Air Liquide’s disengagement from Russia and scholarship-program financial administration at UCF Global. The analysis demonstrates that model outputs remain conditional on the quality and relevance of input data, the validity of underlying assumptions, the selected specification, and the correspondence between the model’s operating boundaries and the decision environment. Credit-risk scholarship further indicates that financial variables may be productively supplemented by behavioral, situational, and alternative information, provided that the resulting assessment remains transparent, explainable, and subject to effective governance. On this basis, the article develops an Integrated Professional Judgment Framework comprising quantitative assessment, discrepancy detection, qualitative enrichment, documented authorization, and outcome-based recalibration. The findings provide conceptual support for a hybrid approach in which professional judgment does not substitute for formal analysis but performs a disciplined interpretive and governance function when model applicability is uncertain. The framework is relevant to financial analysts, credit-risk managers, and institutional decision-makers operating in complex, data-constrained, and rapidly changing environments.

Keywords: Professional Judgment, Financial Risk Management, Credit Risk, Accounts Receivable, Value at Risk, Altman Z-Score, Decision-Making Under Uncertainty, Behavioral Finance, Qualitative Risk Factors, Hybrid Decision Model.

https://doi.org/10.70315/uloap.ulbec.2026.0303011