An Overview - Stress Test Designs for the Evaluation of AI and ML Models Under Shifting Financial Conditions to Improve the Robustness of Models

30 Pages Posted: 22 Nov 2023

See all articles by Joerg Osterrieder

Joerg Osterrieder

University of Twente; Bern Business School

Veni Arakelian

Council of Economic Advisors, Ministry of Finance, Hellenic Republic; UCL Centre for Blockchain Technologies

Ioana Florina Coita

Universitatea din Oradea; University of Economics in Bratislava; "Sofia University "St. Kliment Ohridski

Branka Hadji-Misheva

University of Pavia - Department of Economics and Management

Audrius Kabasinskas

Kaunas University of Technology

Marcos Machado

University of Twente

Codruta Mare

Babes-Bolyai University - Faculty of Economics and Business Administration

Date Written: November 15, 2023

Abstract

The dynamic landscape of financial risk management is increasingly influenced by the integration of Artificial Intelligence and Machine Learning models. These advanced computational approaches have shown remarkable proficiency in analyzing complex, voluminous financial data, leading to enhanced predictive accuracy and decision-making in finance. This paper presents a comprehensive overview of evaluating and enhancing the robustness of AI and ML models in finance through advanced stress testing designs. We delve into the methodologies of stress testing AI and ML models, focusing on scenario development, model input variation, and performance metrics. The paper also critically examines regulatory perspectives and compliance with specific focus on Basel Committee guidelines and the integration of stress testing in risk governance. Challenges in regulatory compliance for AI/ML models are analyzed, highlighting the need for balancing predictive performance with regulatory standards. The discussion extends to the effectiveness of current AI/ML stress testing approaches and strategies for enhancing model robustness and reliability. We underscore the implications for policymakers and financial institutions, emphasizing the necessity for adaptive and resilient financial systems. The paper concludes by outlining future research directions, advocating for advancements in AI/ML methodologies and their applications in financial risk management to foster robust, efficient, and transparent financial systems. This study aims to provide valuable insights for academics, practitioners, and policymakers involved in financial risk management and AI/ML application in finance.

Keywords: Artificial Intelligence, Machine Learning, Financial Risk Management, Stress Testing, Model Robustness, Regulatory Compliance, Basel Committee Guidelines, Predictive Analytics, Financial Stability, Risk Governance

JEL Classification: G00

Suggested Citation

Osterrieder, Joerg and Arakelian, Veni and Coita, Ioana Florina and Hadji-Misheva, Branka and Kabasinskas, Audrius and Machado, Marcos and Mare, Codruta, An Overview - Stress Test Designs for the Evaluation of AI and ML Models Under Shifting Financial Conditions to Improve the Robustness of Models (November 15, 2023). Available at SSRN: https://ssrn.com/abstract=4634266 or http://dx.doi.org/10.2139/ssrn.4634266

Joerg Osterrieder (Contact Author)

University of Twente ( email )

Drienerlolaan 5
Departement of High-Tech Business and Entrepreneur
Enschede, 7522 NB
Netherlands

Bern Business School ( email )

Brückengasse
Institute of Applied Data Sciences and Finance
Bern, BE 3005
Switzerland

Veni Arakelian

Council of Economic Advisors, Ministry of Finance, Hellenic Republic ( email )

5-7 Nikis str
Athens, 10180
Greece

UCL Centre for Blockchain Technologies ( email )

Malet Place
London, London WC1E 6BT
United Kingdom

Ioana Florina Coita

Universitatea din Oradea ( email )

Str. Universităţii nr. 1
Oradea
Romania
+40744369226 (Phone)

HOME PAGE: http://https://steconomice.uoradea.ro/

University of Economics in Bratislava ( email )

Dolnozemská cesta 1
Bratislava, 852 35
Slovakia
+40744369226 (Phone)

HOME PAGE: http://www.euba.sk

"Sofia University "St. Kliment Ohridski ( email )

1 Koziak, str
Sofia, 1407
Bulgaria
+40744369226 (Phone)

HOME PAGE: http://https://www.uni-sofia.bg/eng

Branka Hadji-Misheva

University of Pavia - Department of Economics and Management ( email )

Strada Nuova, 65
Pavia, 27100
Italy

Audrius Kabasinskas

Kaunas University of Technology ( email )

studentu 50-144
Kaunas, 51368
Lithuania

Marcos Machado

University of Twente

Codruta Mare

Babes-Bolyai University - Faculty of Economics and Business Administration ( email )

58-60, Teodor Mihali str
Cluj-Napoca, Cluj 400591
Romania
0745324563 (Phone)

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