Document Type : Research Paper
Authors
1 Instructor of Entrepreneurship, Faculty of Tourism and Hospitality Management, Higher Education Complex of Bam, Bam, Iran, Corresponding Author: s.ghanbari@bam.ac.ir
2 Professor of Elec Eng(EE), Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
3 Professor of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman Iran.
Abstract
With the importance of lending in the banking industry, it is very important to use the indicators affecting credit to decide on lending. The purpose of the present study is to identify and prioritize the effective features in customer accreditation using the viewpoints of bank experts in Kerman and to compare them with existing indicators in models extracted from Meta-Heuristic and Artificial Intelligence methods. The aim is to find out whether there is a match between the human views that arise from knowledge and experience and the views of artificial intelligence that look at the problem as black-box modeling. Required data were collected by questionnaire method and Quantum Binary particle swarm optimization algorithm and analyzed by Delphi. The results show that the selected indices have 80% overlap between the two methods. Due to the results of research and high accuracy of artificial intelligence techniques, it is suggested that in order to give credit to customers in banks and financial and credit institutions, to consider a higher weight for these indicators.
Keywords
آذر، عادل.، فرجی، حجت. (1381). علم مدیریت فازی، تهران، اجتماع.
تقوی فرد، محمدتقی.، نادعلی، احمد. (1391). طبقه‌بندی متقاضیان تسهیلات اعتباری بانکی با استفاده از داده‌کاوی و منطق فازی، فصلنامه مطالعات مدیریت صنعتی، 25، 85 - 108.
جلیلی، محمد.، خدایی وله زاقرد، محمد.، کنشلو، مهدیه. (1389). اعتبارسنجی مشتریان حقیقی در سیستم بانکی کشور، مطالعات کمی در مدیریت، 1 (3)، 127-148.
راعی، رضا.، فلاح‌پور، سعید (1387). کاربرد ماشین بردار پشتیبان در پیش‌بینی درماندگی مالی شرکت‌ها با استفاده از نسبت‌های مالی، بررسی‌های حسابداری و حسابرسی، 15 (53)، 17-34.
رجب‌زاده قطری، علی.، میرزایی آرش، بهرام.، احمدی، پرویز. (1388). طراحی سیستم هوشمند ترکیبی رتبه‌بندی اعتباری مشتریان بانک‌ها با استفاده از مدل‌های استدلالی فازی ترکیبی، پژوهشنامه بازرگانی، 14 (53)، 159 - 201.
صالحی، مجتبی.، کرد کتولی، علیرضا. (1396). انتخاب ویژگی‌های بهینه به‌منظور تعیین ریسک اعتباری مشتریان بانکی. مطالعات مدیریت کسب‌وکار هوشمند،6 (22)، 129-154. https://doi.org/10.22054/ims.2018.8523
قدسی پور، حسن.، سالاری، میثم .، دلاوری، وحید. (1391). ارزیابی ریسک اعتباری شرکت‌های وام‌گیرنده از بانک با استفاده از تحلیل سلسله مراتبی فازی و شبکه عصبی ترکیبی درجه بالا، نشریه بین‌المللی مهندسی صنایع و مدیریت تولید، 23 (1)، 43- 54.
نظام‌آبادی‌پور، حسین. (1392). الگوریتم وراثتی: مفاهیم پایه و مباحث پیشرفته، انتشارات دانشگاه شهید باهنر کرمان.
هاشمی تیله نویی، مصطفی.، حسین‌زاده، صبا. (1399). بررسی برتری مدل هیبریدی نسبت به سایر مدل‌ها در فرایند اعتبارسنجی بانک‌های کشور (مورد مطالعاتی برخی شرکت‌های پذیرفته‌شده در بورس اوراق بهادار تهران). نشریه اقتصاد و بانکداری اسلامی، 9 (31)، 173-204.
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استناد به این مقاله: قنبری، سلیمه.، نظام‌آبادی‌پور، حسین.، جلایی، سید عبدالمجید. (1401). بررسی شاخص‌های اعتبارسنجی مشتریان بانکی با استفاده از روش هوش مصنوعی و دلفی، مطالعات مدیریت کسب وکار هوشمند، 11(42)، 237-265.
DOI: 10.22054/IMS.2021.49698.1669
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