Financial Risk Management and Explainable, Trustworthy, Responsible AI - Fritz-Morgenthal, Sebastian; Hein, Bernhard; Papenbrock, Jochen (Frontiers in Artificial Intelligence, 2022)
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 makes reference to recent related publications from central banks, financial supervisors, regulators as well as by other sources and working groups. It aims to give practical advice for establishing a risk-based governance and test framework for the mentioned model types and also discusses the use of recent technologies, approaches and platforms to support the establishment of industrial, Trustworthy AI.