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Kiefer, S., & Pesch, G. (2021). Unsupervised Anomaly Detection for Financial Auditing with Model-Agnostic Explanations. In S. Edelkamp, R. Möller, & E. Rueckert (Eds.), KI 2021: Advances in Artificial Intelligence (pp. 291-308). Springer International Publishing.
https://doi.org/10.1007/978-3-030-87626-5_22

has been cited by the following article:

• TITLE: Leveraging Artificial Intelligence in Financial Risk Management: Applications in Large Financial Institutions

  AUTHORS: Zixin Feng, Xiao Liu, Wenzhou Yuan

  KEYWORDS: Artificial Intelligence (AI), Financial Risk Management, Large Financial Institution

  JOURNAL NAME: Journal of Financial Risk Management, Vol.14 No.2, June 10, 2025

  ABSTRACT: This paper explores the transformative role of artificial intelligence (AI) in financial risk management practices within financial institutions. By leveraging machine learning and large language models, institutions can enhance their ability to detect, assess, and mitigate various types of risk. The paper presents applications of AI in market risk, credit risk, liquidity risk, and operational risk, supported by real-world case studies. It also discusses regulatory considerations, ethical implications, and implementation challenges, offering a forward-looking view on integrating AI into financial risk frameworks.