Assessment of micro loan payment using structured data mining techniques: the case of Indonesian People' credit bank
Providing financial service to Micro, Small and Medium Enterprises (MSMEs) in Indonesia presents a challenge for small rural banks such as People’ Credit Banks. These banks are required to infer risks about customers’ loan repayment from structured (quantitative, financial) and unstructured (qualita...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference Paper |
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Newswood Ltd
2012
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| Online Access: | http://www.iaeng.org/publication/WCE2012/ http://hdl.handle.net/20.500.11937/32536 |
| _version_ | 1848753690854293504 |
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| author | Ikasari, Novita Hadzic, Fedja |
| author2 | Ao, S. I. |
| author_facet | Ao, S. I. Ikasari, Novita Hadzic, Fedja |
| author_sort | Ikasari, Novita |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Providing financial service to Micro, Small and Medium Enterprises (MSMEs) in Indonesia presents a challenge for small rural banks such as People’ Credit Banks. These banks are required to infer risks about customers’ loan repayment from structured (quantitative, financial) and unstructured (qualitative, non-financial) type of credit information. In this study, the complex nature of credit related information is contextualised and represented in domain specific way using the eXtensible Markup Language (XML). An approach that enables the application of wider selections of data mining techniques on XML data is utilized. Experiments are performed using real world credit data obtained from an Indonesian bank. The results demonstrate the potential of the approach to generate reliable and valid patterns useful for evaluation of existing lending policy. |
| first_indexed | 2025-11-14T08:28:32Z |
| format | Conference Paper |
| id | curtin-20.500.11937-32536 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:28:32Z |
| publishDate | 2012 |
| publisher | Newswood Ltd |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-325362023-02-07T08:01:19Z Assessment of micro loan payment using structured data mining techniques: the case of Indonesian People' credit bank Ikasari, Novita Hadzic, Fedja Ao, S. I. Gelman, L. Hukins, D.W.L. Hunter, A. Korsunsky, A.M. Providing financial service to Micro, Small and Medium Enterprises (MSMEs) in Indonesia presents a challenge for small rural banks such as People’ Credit Banks. These banks are required to infer risks about customers’ loan repayment from structured (quantitative, financial) and unstructured (qualitative, non-financial) type of credit information. In this study, the complex nature of credit related information is contextualised and represented in domain specific way using the eXtensible Markup Language (XML). An approach that enables the application of wider selections of data mining techniques on XML data is utilized. Experiments are performed using real world credit data obtained from an Indonesian bank. The results demonstrate the potential of the approach to generate reliable and valid patterns useful for evaluation of existing lending policy. 2012 Conference Paper http://hdl.handle.net/20.500.11937/32536 http://www.iaeng.org/publication/WCE2012/ Newswood Ltd restricted |
| spellingShingle | Ikasari, Novita Hadzic, Fedja Assessment of micro loan payment using structured data mining techniques: the case of Indonesian People' credit bank |
| title | Assessment of micro loan payment using structured data mining techniques: the case of Indonesian People' credit bank |
| title_full | Assessment of micro loan payment using structured data mining techniques: the case of Indonesian People' credit bank |
| title_fullStr | Assessment of micro loan payment using structured data mining techniques: the case of Indonesian People' credit bank |
| title_full_unstemmed | Assessment of micro loan payment using structured data mining techniques: the case of Indonesian People' credit bank |
| title_short | Assessment of micro loan payment using structured data mining techniques: the case of Indonesian People' credit bank |
| title_sort | assessment of micro loan payment using structured data mining techniques: the case of indonesian people' credit bank |
| url | http://www.iaeng.org/publication/WCE2012/ http://hdl.handle.net/20.500.11937/32536 |