دور الذكاء الاصطناعي كوسيط في تعزيز التقييم الائتماني للحد من المخاطر الائتمانية: دراسة تطبيقية على المصارف الإسلامية في سورية

الموضوعات

إدارة

روابط وملفات

التعريف والنوع

رقم الوثيقة

fc974433-9d25-493b-9730-38e3baad639a

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf image

أسماء الملفات

fc974433-9d25-493b-9730-38e3baad639a_1.pdf

بيانات النشر

ترجمة العنوان

The Role of Artificial Intelligence as a Midtour in Enhancing Credit Assessment to Mitigate Credit Risks: an Applied Study on Islamic Banks in Syria

ألقاب المؤلفين

[{"name_ar":" شادي بيطار","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"ياسمين مصطفى أنبوشة","title_ar":"اعداد","title_en":"Preparation"}]

اللغة

Arabic

المصدر والدورية

اسم المصدر

دور الذكاء الاصطناعي كوسيط في تعزيز التقييم الائتماني للحد من المخاطر الائتمانية: دراسة تطبيقية على المصارف الإسلامية في سورية

المحتوى والصفحات

عدد الصفحات

0

ترجمة الملخص

The study aimed to demonstrate the impact of credit facility evaluation (effectiveness of creditworthiness assessment, efficiency of credit facility granting, quality of credit facility monitoring) using artificial intelligence techniques (machine learning models, predictive models, big data analysis, default prediction tools, intelligent decision support systems) as a mediator in reducing credit risk (reducing the probability of default, improving credit portfolio quality, increasing returns while controlling risk, and enhancing credit operation efficiency). The descriptive analytical approach was adopted, and the study population included employees working in risk management, credit management, and banking systems management in Syrian private banks. A questionnaire was used to collect data, distributed electronically. The number of distributed questionnaires valid for analysis was (87). These questionnaires were statistically analyzed using the SPSS, AMONS statistical program, and hypotheses were tested using multiple linear regression. The study found a significant positive impact on credit facility assessment (effectiveness of creditworthiness assessment, efficiency of credit facility granting, quality of credit facility monitoring) with the use of artificial intelligence technologies (machine learning models, predictive models, big data analysis, default prediction tools, intelligent decision support systems) as a mediator in reducing credit risk (reducing the probability of default, improving credit portfolio quality, increasing returns while controlling risk, and enhancing credit operation efficiency). The study recommended that Syrian Private Islamic Banks invest in AI-powered creditworthiness assessment systems and ensure that human analysts are trained on how to use these tools and interpret their outputs. It also recommended focusing on the quality and diversity of data input to these systems to ensure the highest levels of accuracy and effectiveness in assessment. It also recommended reviewing current credit processes and identifying key opportunities for automation and AI-enhanced processes, starting with processes that require processing large amounts of data or are routine.

إشراف وإعداد

الإشراف

شادي بيطار

الإعداد

ياسمين مصطفى أنبوشة

الاقتباسات الببليوغرافية