Reverse Stress Testing Geopolitical Risk in Corporate Credit Portfolios: A Formal and Operational Framework

2026-01-07

AI Summary

This study addresses the need to enhance the resilience of credit portfolios against extreme geopolitical shocks by quantifying scenarios most likely to drive a bank’s Common Equity Tier 1 (CET1) capital ratio below regulatory thresholds. It proposes a novel “geopolitical point reverse stress testing” framework that embeds explicit geopolitical risk factors into a macro-financial joint scenario vector, which is then mapped—via a latent factor model—to stressed default probabilities and losses, ultimately propagating to tail losses and CET1 impacts. The approach formulates the problem as a constrained maximum likelihood estimation in scenario space and characterizes a near-optimal scenario set to support sensitivity analysis and governance decisions. Compatible with Internal Ratings-Based (IRB) frameworks, the method is interpretable, actionable, and applicable at both individual exposure and sectoral levels, thereby strengthening regulatory compliance and forward-looking risk management.

Technology Category

• Machine Learning: Calibration & Uncertainty Quantification
• Reasoning under Uncertainty: Stochastic Optimization
• Game Theory and Economic Paradigms: Adversarial Learning

Application Category

• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

This paper proposes a formal framework for reverse stress testing geopolitical risk in corporate credit portfolios. A joint macro-financial scenario vector, augmented with an explicit geopolitical risk factor, is mapped into stressed probabilities of default and losses given default. These stresses are then propagated to portfolio tail losses through a latent factor structure and translated into a stressed CET1 ratio, jointly accounting for capital depletion and risk-weighted asset dynamics. Reverse stress testing is formulated as a constrained maximum likelihood problem over the scenario space. This yields a geopolitical point reverse stress test, or design point, defined as the most probable scenario that breaches a prescribed capital adequacy constraint under a reference distribution. The framework further characterises neighbourhoods and near optimal sets of reverse stress scenarios, allowing for sensitivity analysis and governance oriented interpretation. The approach is compatible with internal rating based models and supports implementation at the exposure or sector level.

Problem

• geopolitical risk
• reverse stress testing
• corporate credit portfolios
• capital adequacy
• stress testing

Innovation

• reverse stress testing
• geopolitical risk
• macro-financial scenarios
• constrained maximum likelihood
• latent factor model