Bank Customer Credit Scoring by Using Fuzzy Expert System
نویسندگان
چکیده
منابع مشابه
Domain Driven Classification of Customer Credit Data for Intelligent Credit Scoring using Fuzzy set and MC2
Credit scoring or credit risk assessment is an important research issue in the banking industry. The major challenge of credit scoring is to recruit the profitable customers by predicting the bankrupts. The credit scoring carried out by traditional data driven approaches resulted only in an imprecise solution. Also the domain-driven based multiple criteria and multiple constraint (MC2) level pr...
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expert systems can help to build banks customers' credit scoring models. here, selection of key features of the credit scoring is important. also, it is possible to express the features values as fuzzy. the problem is how to improve features selection by genetic algorithm, in way that these features can be employed as input in fuzzy expert system. this paper presents a hybrid credit scorin...
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Customer credit is an important concept in the banking industry, which reflects a customer’s non-monetary value. Using credit scoring methods, customers can be assigned to different credit levels. Many classification tools, such as Support Vector Machines (SVMs), Decision Trees, Genetic Algorithms can deal with high-dimensional data. However, from the point of view of a customer manager, the cl...
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In any country, commercial banks lay the groundwork for economic growth by collecting national resources and capitals and allocating them to different economic sectors. Optimal allocation of resources is especially important in achieving this goal. Banks with an effective and dynamic system of customer assessment can efficiently allocate their resources to customers regardless of their geograph...
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ژورنال
عنوان ژورنال: International Journal of Intelligent Systems and Applications
سال: 2014
ISSN: 2074-904X,2074-9058
DOI: 10.5815/ijisa.2014.11.04