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Journal of Industrial and Systems Engineering، جلد ۱۵، شماره ۱، صفحات ۳۰۶-۳۲۷
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عنوان انگلیسی A review of Credit Rating models: A combined analysis and suggestions for future research.
چکیده انگلیسی مقاله The key to solving the problem of obtaining complex facilities is to create a suitable credit rating model that can provide technical support for the approval of granting facilities provided by small and micro enterprises. Credit rating agencies perform assessment to support financial institutions in processing debts. Added literature in the field of credit rating from January 2015 to Aguest 2023 was analyzed to discover opportunities for further research. Bibliometric analysis was used to understand the existing literature. Subsequently, through structured review theories, the methods used by researchers and credit rating agencies were examined. A hybrid literature review was developed by integrating bibliometric and structured review of research articles from widely recognized databases. A sample of 72 articles has been made and studied to identify the gaps in the field of credit rating and create a suitable solution to fill such gaps. The results showed that most studies appeared as post-financial crisis effects reported in 2016 and 2023. It contributes to the existing literature by encouraging researchers and credit rating agencies to develop a specific credit rating system by evaluating existing models and improvising them by adopting advanced techniques such as multiple regression, neural networks, aggregate learning, and machine learning.
کلیدواژه‌های انگلیسی مقاله credit rating,credit rating models,Ensemble Learning,Machine Learning,Statistical method
نویسندگان مقاله Seyed Farid Mousavi |
Department of Information Technology and Operations Management, Kharazmi University, Tehran, Iran

Arezoo Gazori-Nishabori |
Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

نشانی اینترنتی https://www.jise.ir/article_178167_069cf47c2c8816b5b9586667b50b59e1.pdf
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