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The Role of Artificial Intelligence "AI" on the Fraud Detection in the Private Sector in Saudi Arabia
| المصدر: | مجلة الفنون والأدب وعلوم الإنسانيات والاجتماع |
|---|---|
| الناشر: | كلية الإمارات للعلوم التربوية |
| المؤلف الرئيسي: | Mohammed, Ahmed Farouk Ali (Author) |
| مؤلفين آخرين: | Essam, Adel (Advisor) , Al-Abdul Rahman, Huda Muhammad (Co-Author) |
| المجلد/العدد: | ع100 |
| محكمة: | نعم |
| الدولة: |
الإمارات |
| التاريخ الميلادي: |
2024
|
| الشهر: | فبراير |
| الصفحات: | 472 - 506 |
| ISSN: |
2616-3810 |
| رقم MD: | 1448757 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | +HumanIndex |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Artificial Intelligence | Fraud Detection | Private Sector | Saudi Arabia
|
| رابط المحتوى: |
عدد مرات التحميل
7
| المستخلص: |
This study examines the use of Artificial Intelligence (AI) in detecting fraud within the private sector in Saudi Arabia. The research seeks to comprehend the obstacles and possibilities that organizations encounter when implementing and utilizing AI technologies for fraud detection. This study utilizes a combination of qualitative and quantitative methods to explore how AI contributes to fraud detection in Saudi Arabia's private sector. To begin, an extensive literature review is conducted, focusing on AI-enabled fraud detection studies specifically within the private sector in Saudi Arabia. This review serves as a basis for knowledge and identifies gaps in existing research. Quantitative data is gathered through surveys and questionnaires administered to private-sector organizations in Saudi Arabia, covering aspects such as current fraud detection practices, AI technology implementation challenges, and perceived effectiveness in preventing fraudulent activities. To gain a deeper understanding, qualitative data is collected through interviews with key stakeholders including fraud detection experts, managers, and IT professionals. These interviews provide insights into their experiences and perspectives regarding the implementation of AI technologies for fraud detection in the private sector of Saudi Arabia. Additionally, detailed case studies are conducted on selected organizations that have employed AI technologies for fraud detection purposes. Data analysis involves both statistical techniques for quantitative data such as descriptive statistics, correlation analysis, and regression analysis; while thematic analysis is employed to examine qualitative data from interviews and case studies to identify emerging themes and patterns. Ethical considerations play a crucial role throughout this research process: necessary approvals from relevant research ethics committees are obtained, measures are taken to ensure confidentiality and anonymity of participants' information. The findings from this research will contribute to a thorough understanding of how AI plays a role in detecting fraud within Saudi Arabia's private sector. By employing a mixed methodology approach, this study aims to provide valuable insights and recommendations for enhancing fraud detection processes using AI technologies within organizations. |
|---|---|
| ISSN: |
2616-3810 |
عناصر مشابهة
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