Assessment of micro loan payment using structured data mining techniques: The case of Indonesian people’ credit bank

Novita Ikasari; Fedja Hadzic

Assessment of micro loan payment using structured data mining techniques: The case of Indonesian people’ credit bank

Novita Ikasari, Fedja Hadzic

Department of Business Administration

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings of the World Congress on Engineering 2012, WCE 2012
Editors	Len Gelman, Andrew Hunter, A. M. Korsunsky, S. I. Ao, David WL Hukins
Publisher	Newswood Limited
Pages	511-517
Number of pages	7
ISBN (Print)	9789881925138
Publication status	Published - 2012
Event	2012 World Congress on Engineering, WCE 2012 - London, United Kingdom Duration: 4 Jul 2012 → 6 Jul 2012

Publication series

Name	Lecture Notes in Engineering and Computer Science
Volume	2197
ISSN (Print)	2078-0958

Conference

Conference	2012 World Congress on Engineering, WCE 2012
Country/Territory	United Kingdom
City	London
Period	4/07/12 → 6/07/12

Keywords

Credit risk assessment
Data mining techniques
Database structure model
Indonesian people’ credit bank
XML

Cite this

Ikasari, N., & Hadzic, F. (2012). Assessment of micro loan payment using structured data mining techniques: The case of Indonesian people’ credit bank. In L. Gelman, A. Hunter, A. M. Korsunsky, S. I. Ao, & D. WL. Hukins (Eds.), Proceedings of the World Congress on Engineering 2012, WCE 2012 (pp. 511-517). (Lecture Notes in Engineering and Computer Science; Vol. 2197). Newswood Limited.

Ikasari, Novita ; Hadzic, Fedja. / Assessment of micro loan payment using structured data mining techniques : The case of Indonesian people’ credit bank. Proceedings of the World Congress on Engineering 2012, WCE 2012. editor / Len Gelman ; Andrew Hunter ; A. M. Korsunsky ; S. I. Ao ; David WL Hukins. Newswood Limited, 2012. pp. 511-517 (Lecture Notes in Engineering and Computer Science).

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abstract = "Providing financial service to Micro, Small and Medium Enterprises (MSMEs) in Indonesia presents a challenge for small rural banks such as People{\textquoteright} Credit Banks. These banks are required to infer risks about customers{\textquoteright} 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.",

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Ikasari, N & Hadzic, F 2012, Assessment of micro loan payment using structured data mining techniques: The case of Indonesian people’ credit bank. in L Gelman, A Hunter, AM Korsunsky, SI Ao & DWL Hukins (eds), Proceedings of the World Congress on Engineering 2012, WCE 2012. Lecture Notes in Engineering and Computer Science, vol. 2197, Newswood Limited, pp. 511-517, 2012 World Congress on Engineering, WCE 2012, London, United Kingdom, 4/07/12.

Assessment of micro loan payment using structured data mining techniques: The case of Indonesian people’ credit bank. / Ikasari, Novita; Hadzic, Fedja.
Proceedings of the World Congress on Engineering 2012, WCE 2012. ed. / Len Gelman; Andrew Hunter; A. M. Korsunsky; S. I. Ao; David WL Hukins. Newswood Limited, 2012. p. 511-517 (Lecture Notes in Engineering and Computer Science; Vol. 2197).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Assessment of micro loan payment using structured data mining techniques: The case of Indonesian people’ credit bank

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Keywords

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