Designing a proper model and software program to evaluate and predict credit risk of small and medium‑sized enterprises in commercial banks

Article Type:
Research/Original Article (دارای رتبه معتبر)

Globalization and, consequently, intensifying the competition between banks and financial institutions in domestic and foreign financial markets increase significantly the importance and requirement of strengthening and modifying systems in financial enterprises. Banks are no exception. Credit risk assessment is one of the most significant components of the granted facilities process. Small and medium enterprises are the majority of customers of commercial banks; hence, it is possible that designing a credit risk system considerably helps banks to manage credit risk.This study aims to introduce a new approach to predict and assess the credit risk of small and medium-sized enterprises. To this end, we identified the indices effective on the credit risk of medium and small-sized enterprises and determined significant indices by selecting the feature. We selected 98 cases of medium and small-sized legal clients in the industrial sector for research data from one of the commercial banks during the years 2018-2020. We then implemented the logit regression models, artificial neural network, and hybrid model (fuzzy expert system, logit, and artificial neural network) in order to predict and assess customers' credit risk and also calculated the accuracy of the models. Ultimately, we have designed the program applying visual studio software. We calculated the customer using logit regression models, artificial neural network, and hybrid model according to the designed program by inserting each customer's information and we also determined credit rating and type of collateral of each customer based on customer risk.

International Journal of Finance and Managerial Accounting, Volume:8 Issue: 31, Autumn 2023
1 to 11  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!