Financial Innovation Test in Banking: Providing a Hybrid Model for Forecasting and Assessing Credit Risk of Medium and Small Enterprises (SMEs) in Commercial Banks

Subject Areas : Financial engineering

Kokab Sharifi ¹ , Amir Mohammadzadeh ^{2 *} , Hashem Nikoumaram ³ , Naser Hamidi ⁴

1 - Department of Financial Management , Qazvin Branch, Islamic Azad University, Qazvin, Iran
2 - Department of Financial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran
3 - Department of Financial Management, Research and Sciesnce Branch, Islamic Azad University, Tehran , Iran
4 - Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran.

Received: 2021-01-04 Accepted : 2021-03-07 Published : 2021-06-22

Keywords: ", "Neural Network", "Credit risk, "Logit", "Fuzzy expert system", "Small and Medium Enterprises",

Abstract :

We live in an age characterized by the very rapid rate of financial innovation. The study of the historical evolution of progress and economic development of developed and industrialized countries shows that one of the main factors in the emergence of rapid and massive growth has been the existence of financial reforms in these countries. There are different incentives for individuals and active enterprises in the financial system to perform financial innovation, which is one of the most important incentives, the introduction of tools and methods to reduce, eliminate or manage existing risks. One of the most important tools the current situation that can help banks in the optimal management of consumption and prevention of claims. Designing and applying credit risk assessment models in granting facilities. The purpose of this study is to provide a suitable model for financial innovation based on credit risk measurement of SMEs in commercial banks. In this regard, effective indicators on the credit risk of SMEs were identified by using the genetic algorithm method and logit, neural network and fuzzy expert system were evaluated. The results show that the using the hybrid model has more accurate results in the assessment the credit risk of SMEs.