مدل‌سازی و شناسایی متغیرهای غیرشکننده مؤثر بر ریسک اعتباری در بانک تجارت با تأکید بر فناوری‌های فین‌تک

الموضوعات :

رحمان رحیمی ¹ , فاطمه صراف ² , محبوبه جعفری ³ , بیژن صفوی ⁴

1 - گروه حسابداری، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.
2 - گروه حسابداری، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.
3 - گروه حسابداری، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.
4 - گروه اقتصاد، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.

تاريخ الإرسال : 15 الأحد , صفر, 1444 تاريخ التأكيد : 02 الإثنين , جمادى الثانية, 1444 تاريخ الإصدار : 28 الخميس , جمادى الأولى, 1444

الکلمات المفتاحية: مدیریت ریسک, ریسک اعتباری, بانک تجارت, فین‌تک, مدل‌های بیزین,

ملخص المقالة :

هدف: ارزیابی ریسک اعتباری یکی از موضوعات چالش‌برانگیز در بخش بانکی است؛ مشکل اصلی مدل‌سازی صحیح این نوع ریسک می‌باشد. تنوع متغیرهای اثرگذار بر ریسک اعتباری و نبود یک مدل مشخص از مهم‌ترین علل شکست مدل‌های سنتی می‌باشد. براین‌اساس هدف تحقیق حاضر مدل‌سازی ریسک اعتباری بانک تجارت در رژیم‌های مختلف اقتصادی است.روش‌شناسی پژوهش: این تحقیق کاربردی است. بازه زمانی تحقیق پنج سال (1400-1396) و از بین 105 هزار مشتری بانک تجارت انتخاب شده است. برای این منظور، اطلاعات شاخص‌های 33 عامل مؤثر بر ریسک اعتباری در بانک تجارت وارد مدل‌های BMA، TVP-DMA و TVP-DMS شد. پس از برآورد مدل، 8 متغیر اصلی شناسایی گردید.یافته‌ها: تأثیر متغیرهای غیرشکننده در مدل مارکوف سویچینگ بر ریسک اعتباری مورد تجزیه‌وتحلیل قرار گرفت. اکثریت متغیرها به‌جز متغیر مشتریان حقوقی تأثیر منفی و معناداری بر سطح ریسک اعتباری دارند و با حرکت از سمت رونق بالا به‌ سمت رکود عمیق میزان تأثیرگذار متغیرها بر ریسک اعتباری افزایش یافته ‌است.اصالت / ارزش‌افزوده علمی: نتایج نشان داد مدل بهینه ریسک اعتباری در هر بانک متفاوت است. براین‌اساس اقدام به طراحی یک مدل بهینه صرفاً برای ریسک اعتباری در بانک تجارت بر اساس الگوهای میانگین‌گیری بیزین گردید. بر اساس رویکرد مارکوف سویچینگ نیز این نتیجه حاصل شد که ریسک اعتباری در حالت رکود اقتصادی حساسیت بالاتری نسبت به متغیرهای توضیح‌دهنده خود دارد. همچنین بر اساس نتایج مشخص گردید که شاخص‌های مرتبط با فین‌تک بر سطح ریسک اعتباری در بانک تجارت تأثیر معناداری دارند.

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