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    Utilizing Data Analytics for Fraud Detection and Prevention in Online Banking Systems of Saudi Arabia
    (University of Portsmouth, 2024-09) Almotairy, Yazeed; Jiacheng, Tan
    This thesis addresses the critical issues of online banking and online banking fraud in Saudi Arabia. The thesis focusses on the older methodologies of the online banking systems in Saudi Arabia. The frauds are discussed in detail that are occurring in the online banking systems and are causing inconvenience to the users and account holders of the online banks and applications. In this thesis, online banking frauds are discussed thoroughly, and the traditional fraud detection methods are elaborated as well. The vulnerabilities in the current systems are explored. It discusses how the older systems are not performing well and why the new system encompasses the power of data analytics and machine learning. The methods proposed use a set of data analytics and machine learning algorithms and techniques to detect fraud or any fraudulent activity that a scammer or fraudster may perform. The results of this study explain how the proposed system can outperform the traditional methodologies being used in Saudi Arabian online banking systems. The proposed system can also enhance the user experience. The possible privacy and ethical concerns are also discussed. In the end, it is also discussed what the future prospects are for the researchers who are looking to enhance this research or want to work in the field of data analytics and machine learning to improve the security of the security of online banking applications. In conclusion, this thesis not only contributes to the body of knowledge on online banking frauds in Saudi Arabia and their detection but also features future research topics for new researchers.
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    Perception of Insurance and Risk Management Strategies Among Consumers In Saudi Arabia: A Quantitative Study
    (Saudi Digital Library, 2023-11-23) Alajmi, Mubarak; Vera, Zhao
    The insurance landscape in Saudi Arabia is undergoing significant transformation due to various influencing factors such as technological advancements, demographic shifts, and evolving consumer preferences. This dissertation aims to provide an in-depth analysis of consumer decision-making in the selection of insurance products within the Saudi Arabian market. Employing advanced statistical methods including cluster analysis and contingency tables, the study addresses four principal objectives: understanding the demographic variables that influence insurance choices, pinpointing the key sources of information that guide consumers, assessing the degree of consumer confidence in insurance-related decisions, and exploring behavioral patterns that have a notable impact on these choices. The research uncovers complex relationships and segmented consumer behaviors based on age, gender, and income levels. These insights offer valuable recommendations for insurance companies in Saudi Arabia to refine their product designs, customer service, and marketing strategies. The dissertation serves as a comprehensive guide for both scholars and practitioners interested in enhancing consumer engagement and tailoring insurance offerings in the Saudi Arabian context.
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