Saudi Cultural Missions Theses & Dissertations
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Item Restricted Supervised Machine Learning. A Strategic Approach for Financial Fraud Detection(University of Nottingham, 2024-03) Bashehab, Omar Sami; Wang, HuamaoFinancial fraud is an increasingly concerning issue in the present day. The rapidly growing rate of fraudulent activities has led to significant financial losses for many stakeholders. Card-not-present (CNP) fraud has risen with the growth of digital sales. The same benefits attracting online banking and transactions have attracted fraudsters and cybercriminals. Consequently, the incentive for fraud detection for mitigating financial risk is evident. However, traditional detectors are outdated, and rule-based systems fail to keep up with the dynamic innovative methodologies of cybercriminals. Thus, the ML-based system is needed. However, various challenges exist within ML-based detectors. Firstly, datasets are typically highly imbalanced and secondly, a lack of real-world datasets makes research extremely difficult. To tackle these problems, different resampling methods such as RUS, ROS, SMOTE and a hybrid sampling approach (ROS + RUS) were used and evaluated. Furthermore, a novel dataset was used, augmented from an original PAYsim real-world synthetic data. Furthermore, predictive models such as Decision Tree, Logistic Regression, Random Forests, Support Vector Machine and (Gaussian) Naïve Bayes were used with the different resampling methods in a comparative approach. Finally, the importance of data preprocessing and feature engineering was explored and evaluated amongst the classifiers. The experimental results illustrate the Random Forest, with Grid Search CV optimisation and RUS as well as feature engineering performed the best. The methodological approach exhibited an increase in F1 score, True Positive Rate, Recall and Accuracy for the classifier. The final model outputted an F1 score of 69%, ROC-AUC of 88% and True Positive Rate (TPR) of 93%.78 0Item Restricted Balancing Innovation and Protection: Is AI Regulation the Future of Saudi FinTech?(King's College London, 2024-09) Alkhathlan, Alaa Saad; Keller, AnatThis study investigates the implications of artificial intelligence in the Saudi FinTech sector, focusing on the evolving regulatory landscape. While AI holds substantial promise for driving innovation, it also poses ethical and practical challenges such as data privacy, algorithmic transparency, and fairness. This study examines the current regulatory framework in Saudi Arabia, highlighting efforts like the AI Ethics Principles and the Personal Data Protection Law. Despite these measures, significant gaps remain due to the voluntary nature of the AI Ethics Principles and Generative AI Guidelines, resulting in inconsistent implementation. The primary aim of this study is to guide policymakers on regulating AI in the Saudi FinTech sector while preserving innovation. Key recommendations urge policymakers to develop regulations based on international best practices, addressing issues such as data privacy, algorithmic biases, and systemic risks. Emphasising the need for continuous dialogue among regulators, FinTech companies, and international partners, the study also calls for enhancing human-machine collaboration, establishing regulatory sandboxes, creating an AI Oversight Committee, and supporting research to better understand AI's implications. By aligning with Saudi Vision 2030 goals, these recommendations aim to strengthen Saudi Arabia's AI regulatory framework, support sustainable growth in the FinTech sector, and build public trust in AI-driven financial services.49 0Item Restricted The influence of financial technology (Fintech) on the financial performance of National Saudi Arabia and Bahrain Banking(Cardiff University, 2024-09) Adawi, Eman; Jahanshahloo, HosseinIn recent years, the world has witnessed the rise of Financial Technology, often known as FinTech. Globally, this is a much-debated matter within the financial sector, particularly throughout the banking industry. In recent years, this emerging phenomenon has attracted the interest of scholars and has been extensively investigated in prior research. This study examines various aspects of the impact of financial technology on banking performance in Saudi Arabia and Bahrain. The research aimed to explore the potential influence of financial technology (FinTech) on the operational effectiveness of banks in the Kingdom of Saudi Arabia and Bahrain. The study employs a quantitative analysis of 17 banks from Saudia Arabia and Bahrain, which covers the period from 2017 to 2023. The findings of the study indicate that there was no statistically significant relationship found between the following FinTech tools: Banking messages (SMS), Internet banking (IB), Mobile applications (MMA), and Digital transfers (DT), and the metrics of Return on Assets (ROA), Return on Equity (ROE), and Net Interest Margin (NIM) for each respective item. Although the primary objective of this study was to investigate the impact of FinTech on crucial financial performance indicators, the findings indicate that the relationship may be complex and dependent on various factors such as regulatory environment, customer adoption, and technological infrastructure that should have been included in the focused analysis conducted in this research. Subsequent investigations should broaden the range of examination by incorporating these additional variables and dimensions through which FinTech could exert its influence.7 0Item Restricted THE MERITS OF DIVIDEND-BASED PORTFOLIO INVESTMENT STRATEGIES(Saudi Digital Library, 2023-12-01) Alsheban، Mohammad; Khoo, Shee; Gwilym, Owain1.Dividend-Based Portfolio Investment Strategies: This study explores the advantages of incorporating dividends into investment decisions, emphasizing how such strategies enhance portfolio performance, provide stability, and offer consistent income. Through historical data and empirical analysis, the abstract highlights the merits of using dividend-focused approaches in navigating financial complexities. 2. Credit Rating Agency: Examining the role of credit rating agencies in the global financial system, this abstract discusses their methodologies, impact on markets, and regulatory frameworks. It addresses challenges and controversies, proposing potential reforms for improved accuracy. The study aims to clarify the significance of credit ratings in influencing investment decisions and shaping market dynamics. 3. Behavioral Finance: Investigating psychological influences on financial decision-making and market dynamics, this abstract synthesizes established theories and recent empirical research. It uncovers behavioral biases affecting investor behavior and financial stability. The study contributes to a comprehensive understanding of market dynamics, offering insights into strategies for mitigating irrational decision-making. 4. Financial Technology (FinTech): This abstract explores the transformative impact of FinTech on the financial industry, examining innovations like blockchain and artificial intelligence. It discusses how FinTech reshapes traditional services, addressing potential benefits, challenges, and implications for financial inclusion and regulatory frameworks. The study provides insights into the evolving financial ecosystem.18 0