Risk detection through LLMs: An EU banking case study in monitoring media with AI
Abstract
This paper presents a case study of an artificial intelligence (AI)-supported media monitoring system implemented in a European commercial banking group to enhance early detection of emerging risks. The pipeline processes millions of media articles daily using a scalable Databricks-based architecture and large language models (LLMs) for relevance scoring, novelty detection and summarisation. It demonstrates how AI-based text analysis supports credit, liquidity and geopolitical risk monitoring by transforming unstructured news into risk-relevant intelligence delivered through automated e-mail briefings, dashboards and early warning system (EWS) integration. The case study further illustrates how such AI-supported media monitoring can be governed and deployed within the regulatory and supervisory framework of the European banking sector while strengthening risk awareness and decision making and offering additional value for compliance, operational risk and communication functions. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
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Author's Biography
Vedad Sehanovic is a Senior Developer for Risk Models at Erste Bank, Austria’s largest banking group. He focuses on corporate business models and the development of advanced credit risk solutions. Formerly a product owner and director in the AI Center of Excellence at Raiffeisen Bank International in Vienna, Vedad combines experience in artificial intelligence (AI) and credit risk modelling to drive innovation in reshaping risk management within the bank. He holds degrees in economics and quantitative finance.
Lorenz Bacca is a Senior Machine Learning Engineer in the AI Center of Excellence at Raiffeisen Bank International in Vienna. He takes technical leadership over the development and implementation of machine learning and generative artificial intelligence (GenAI) solutions. Lorenz’s professional background includes roles in the telecommunications and banking sectors. He holds degrees in business informatics.
Charles Dietz serves as Senior Data Scientist and Product Owner in the AI Center of Excellence at Raiffeisen Bank International, overseeing artificial intelligence (AI) and automation projects across the bank. He combines a rigorous quantitative background from his PhD in physics with practical expertise in machine learning (ML) and large language model (LLM) engineering, product delivery and cross-functional leadership.
Citation
Sehanovic, Vedad, Bacca, Lorenz and Dietz, Charles (2026, March 1). Risk detection through LLMs: An EU banking case study in monitoring media with AI. In the Journal of Risk Management in Financial Institutions, Volume 19, Issue 2. https://doi.org/10.69554/XDDX5506.
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