ArticleFrontiers in artificial intelligence2022
Financial Risk Management and Explainable, Trustworthy, Responsible AI.
Article in Frontiers in artificial intelligence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- AI-driven financial risk management in complex mobile economies: a contextual-technology fit and security reassurance model.Frontiers in artificial intelligence · 2026Article
- Quantum computing in finance: a literature review and future directions for trustworthy financial AI.Frontiers in artificial intelligence · 2026Review
- The Role of Smart Governance in Mitigating Financial Risks in the Era of Artificial Intelligence: Evidence from Iraqi Banks.F1000Research · 2026Article
- Interpretable multimodal reasoning for robo-advisory: the FinErva framework.Frontiers in artificial intelligence · 2025Article
- DOMINO: Domain-aware loss for deep learning calibration.Software impacts · 2023Article
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Authors and funding
3 authors.
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Abstract
This perspective paper is based on several sessions by the members of the Round Table AI at FIRM, with input from a number of external and international speakers. Its particular focus lies on the management of the model risk of productive models in banks and other financial institutions. The models in view range from simple rules-based approaches to Artificial Intelligence (AI) or Machine learning (ML) models with a high level of sophistication. The typical applications of those models are related to predictions and decision making around the value chain of credit risk (including accounting side under IFRS9 or related national GAAP approaches), insurance risk or other financial risk types. We expect more models of higher complexity in the space of anti-money laundering, fraud detection and transaction monitoring as well as a rise of AI/ML models as alternatives to current methods in solving some of the more intricate stochastic differential equations needed for the pricing and/or valuation of derivatives. The same type of model is also successful in areas unrelated to risk management, such as sales optimization, customer lifetime value considerations, robo-advisory, and other fields of applications. The paper refers to recent related publications from central banks, financial supervisors and regulators as well as other relevant sources and working groups. It aims to give practical advice for establishing a risk-based governance and testing framework for the mentioned model types and discusses the use of recent technologies, approaches, and platforms to support the establishment of responsible, trustworthy, explainable, auditable, and manageable AI/ML in production. In view of the recent EU publication on AI, also referred to as the EU Artificial Intelligence Act (AIA), we also see a certain added value for this paper as an instigator of further thinking outside of the financial services sector, in particular where "High Risk" models according to the mentioned EU consultation are concerned.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.