The Use of Multi-Objective Meta-Heuristic Algorithm GENETIC-ANFIS in Rating the Loans Granted to Real Customers of Bank Melli Iran
محورهای موضوعی : Multi-Criteria Decision Analysis and its Application in Financial ManagementMasoud Rezaei Aghmashhadi 1 , GHolamreza Mahfoozi 2 , Farzad Rahimzadeh 3
1 - Department of Finance, Rasht Branch, Islamic Azad University, Rasht, Iran
2 - Department of Economics and Accounting, University of Guilan, Rasht, Iran
3 - Department of Economics and Accounting, University of Guilan, Rasht, Iran
کلید واژه: Granting Loans, Meta-heuristic Algorithm , Genetic Algorithm , Credit Risk,
چکیده مقاله :
The present study is aimed to Rating the loans granted to the real customers of Bank Melli Iran in accordance with the credit factors of the customers using the multi-objective meta-heuristic algorithm of genetics-adaptive neuro-fuzzy network system (GENETIC-ANFIS). This research is a qualitative-quantitative design and exploratory based on purpose in terms of purpose and descriptive in terms in terms of data collection and analysis method and survey. Qualitative data was collected via the research of Rezaei et al. (2022) and the decision making team of the banking field, and quantitative data was collected through 1178 real customers of Bank Melli of Mazandaran province during the years 2012 to 2021 based on 14 types of loans. According to the rating of granted loans, the risk of each loan was measured separately for 4 personal, environmental, economic and credit factors. In Mudharabah loans, Musyarakah, debt purchase, Istisna and salaf, the economic factor showed the highest sensitivity. Also, the behavior of the research meta-heuristic model has indicated 78% reliability in the accuracy and interpretability of the model compared to genetic algorithm, neural network, fuzzy logic and neural-fuzzy network models..
The present study is aimed to Rating the loans granted to the real customers of Bank Melli Iran in accordance with the credit factors of the customers using the multi-objective meta-heuristic algorithm of genetics-adaptive neuro-fuzzy network system (GENETIC-ANFIS). This research is a qualitative-quantitative design and exploratory based on purpose in terms of purpose and descriptive in terms in terms of data collection and analysis method and survey. Qualitative data was collected via the research of Rezaei et al. (2022) and the decision making team of the banking field, and quantitative data was collected through 1178 real customers of Bank Melli of Mazandaran province during the years 2012 to 2021 based on 14 types of loans. According to the rating of granted loans, the risk of each loan was measured separately for 4 personal, environmental, economic and credit factors. In Mudharabah loans, Musyarakah, debt purchase, Istisna and salaf, the economic factor showed the highest sensitivity. Also, the behavior of the research meta-heuristic model has indicated 78% reliability in the accuracy and interpretability of the model compared to genetic algorithm, neural network, fuzzy logic and neural-fuzzy network models..
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