Resilience of Saudi Financial Institutions Against AI-Driven Cyber Threats

dc.contributor.advisorAdamos, Vasileios
dc.contributor.authorALshammar, Rushud
dc.date.accessioned2025-10-28T16:49:04Z
dc.date.issued2025
dc.description.abstractArtificial intelligence (AI) is increasingly exploited by cybercriminals, creating advanced threats that challenge the security of financial institutions. Saudi banks, central to Vision 2030’s digital transformation, face heightened risks from AI-driven attacks such as phishing, fraud detection evasion, and adversarial machine learning. The aim of this research was to evaluate the resilience of six major Saudi banks (NCB, Al Rajhi, SABB, Riyad Bank, BSF, and ANB)against AI-enabled cyber threats, with a focus on identifying gaps in current frameworks, assessing employee awareness, and recommending improvements. A quantitative, cross-sectional survey was employed, gathering data from banking professionals across cybersecurity, compliance, and risk management roles. The findings show that while AI-driven threats are widely recognised, frameworks are inconsistently applied, AI-powered defences are rare, and employee training lacks AI-specific content. These shortcomings reduce institutional agility and leave human awareness as the weakest layer of defence. The study is limited by its reliance on survey data, which restricts depth of institution-specific insights. It recommends mandatory AI-focused training, adoption of automated defence systems, and contextualised national frameworks. Future research should include longitudinal studies, case-specific analyses, and simulation-based testing to strengthen resilience in evolving threat environments.
dc.format.extent79
dc.identifier.urihttps://hdl.handle.net/20.500.14154/76766
dc.language.isoen
dc.publisherSaudi Digital Library
dc.subjectCybersecurity
dc.subjectArtificial Intelligence
dc.subjectSaudi Banks
dc.subjectResilience
dc.subjectTraining
dc.titleResilience of Saudi Financial Institutions Against AI-Driven Cyber Threats
dc.typeThesis
sdl.degree.departmentSchool of Computing, Faculty of Technology
sdl.degree.disciplineCyber Security and Forensic Information Technology
sdl.degree.grantorUniversity of Portsmouth
sdl.degree.nameMaster of Science (MSc)

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