AI in the Banking sector; the Benefits and Risks of Artificial Intelligence implementation in Banking Risk Management

dc.contributor.advisorSifat, Imtiaz
dc.contributor.authorLuijten, Sjoerd
dc.date.issued2024-07-05
dc.description.abstractThis thesis investigates the impact of AI implementation in banking risk management. The study follows a comprehensive approach, focusing on the benefits and risks associated with its integration. First, it examines the effect of AI on the efficiency and accuracy of banking risk management, conducting a Systematic Literature Review. Second, the study researches the effect of AI implementation on data security in banking risk management with a thematic analysis. Findings show that AI has the ability to significantly enhance the precision and speed of risk assessment in areas such as credit, market and operational risk management. AI-powered methods outperform traditional methods in managing large datasets, detecting fraudulent activities and through its flexibility. Though there are significant beneficial effects through the use of AI, it also introduces new challenges. Banks have to be aware of data privacy concerns due to the accumulation of data. Moreso, banks face obstacles such as the complexity of AI systems, and the need for specialized training for banking professionals. This thesis contributes to the understanding of both sights of AI implementation in banking risk management. This study offers insights for policymakers, financial institutions and researcher interested in the integration of AI in banking risk management.
dc.identifier.urihttps://theses.ubn.ru.nl/handle/123456789/17430
dc.language.isoen
dc.thesis.facultyFaculteit der Managementwetenschappen
dc.thesis.specialisationspecialisations::Faculteit der Managementwetenschappen::Master Economics::Corporate Finance & Control
dc.thesis.studyprogrammestudyprogrammes::Faculteit der Managementwetenschappen::Master Economics
dc.thesis.typeMaster
dc.titleAI in the Banking sector; the Benefits and Risks of Artificial Intelligence implementation in Banking Risk Management

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