Credit Risk Prediction Using Fuzzy Immune Learning
The use of credit has grown considerably in recent years. Banks and financial institutions confront credit risks to conduct their business. Good management of these risks is a key factor to increase profitability. Therefore, every bank needs to predict the credit risks of its customers. Credit risk...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2014/651324 |
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| _version_ | 1832562016467812352 |
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| author | Ehsan Kamalloo Mohammad Saniee Abadeh |
| author_facet | Ehsan Kamalloo Mohammad Saniee Abadeh |
| author_sort | Ehsan Kamalloo |
| collection | DOAJ |
| description | The use of credit has grown considerably in recent years. Banks and financial institutions confront credit risks to conduct their business. Good management of these risks is a key factor to increase profitability. Therefore, every bank needs to predict the credit risks of its customers. Credit risk prediction has been widely studied in the field of data mining as a classification problem. This paper proposes a new classifier using immune principles and fuzzy rules to predict quality factors of individuals in banks. The proposed model is combined with fuzzy pattern classification to extract accurate fuzzy if-then rules. In our proposed model, we have used immune memory to remember good B cells during the cloning process. We have designed two forms of memory: simple memory and k-layer memory. Two real world credit data sets in UCI machine learning repository are selected as experimental data to show the accuracy of the proposed classifier. We compare the performance of our immune-based learning system with results obtained by several well-known classifiers. Results indicate that the proposed immune-based classification system is accurate in detecting credit risks. |
| format | Article |
| id | doaj-art-e077266af1974494ba17e9b128585a86 |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-e077266af1974494ba17e9b128585a862025-02-03T01:23:41ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2014-01-01201410.1155/2014/651324651324Credit Risk Prediction Using Fuzzy Immune LearningEhsan Kamalloo0Mohammad Saniee Abadeh1Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran 14115-143, IranFaculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran 14115-143, IranThe use of credit has grown considerably in recent years. Banks and financial institutions confront credit risks to conduct their business. Good management of these risks is a key factor to increase profitability. Therefore, every bank needs to predict the credit risks of its customers. Credit risk prediction has been widely studied in the field of data mining as a classification problem. This paper proposes a new classifier using immune principles and fuzzy rules to predict quality factors of individuals in banks. The proposed model is combined with fuzzy pattern classification to extract accurate fuzzy if-then rules. In our proposed model, we have used immune memory to remember good B cells during the cloning process. We have designed two forms of memory: simple memory and k-layer memory. Two real world credit data sets in UCI machine learning repository are selected as experimental data to show the accuracy of the proposed classifier. We compare the performance of our immune-based learning system with results obtained by several well-known classifiers. Results indicate that the proposed immune-based classification system is accurate in detecting credit risks.http://dx.doi.org/10.1155/2014/651324 |
| spellingShingle | Ehsan Kamalloo Mohammad Saniee Abadeh Credit Risk Prediction Using Fuzzy Immune Learning Advances in Fuzzy Systems |
| title | Credit Risk Prediction Using Fuzzy Immune Learning |
| title_full | Credit Risk Prediction Using Fuzzy Immune Learning |
| title_fullStr | Credit Risk Prediction Using Fuzzy Immune Learning |
| title_full_unstemmed | Credit Risk Prediction Using Fuzzy Immune Learning |
| title_short | Credit Risk Prediction Using Fuzzy Immune Learning |
| title_sort | credit risk prediction using fuzzy immune learning |
| url | http://dx.doi.org/10.1155/2014/651324 |
| work_keys_str_mv | AT ehsankamalloo creditriskpredictionusingfuzzyimmunelearning AT mohammadsanieeabadeh creditriskpredictionusingfuzzyimmunelearning |