University of Twente Student Theses
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Artificial Intelligence in Early-Warning Systems: Opportunities and Challenges for Financial Risk Monitoring
Bowenkamp, David (2025) Artificial Intelligence in Early-Warning Systems: Opportunities and Challenges for Financial Risk Monitoring.
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| Abstract: | This thesis explores how artificial intelligence can strengthen early warning systems in the finance sector, which are necessary for detecting market risks. Since traditional systems use standard indicators and simple models, they often miss to detect complex risks due to the fast-changing markets. By reviewing recent research and drawing on survey responses, the study finds that new AI techniques like machine learning can identify risk patterns earlier and more accurately, especially when using diverse data sources such as news or market sentiment. However, most organizations are still at the testing stage, facing challenges around transparency, regulation, and expertise. For successful adoption, managers should focus on improving data quality, clear model explanations, and staff training. Ultimately, the value of AI-driven early warning systems will rely as much on careful management as on the technology itself. |
| Item Type: | Essay (Bachelor) |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 83 economics, 85 business administration, organizational science |
| Programme: | International Business Administration BSc (50952) |
| Link to this item: | https://purl.utwente.nl/essays/106751 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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