The effectiveness of positive data sharing in controlling the growth of indebtedness in Hong Kong credit card industry

Vincent To Yee Ng, Wai Tak Yim, Stephen Chi Fai Chan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

In order to cut down on soaring personal loan bankruptcies, the Hong Kong government had unveiled a plan in early of 2002 to allow banks to share more credit information about their customers. This paper analyses how effective the positive data sharing scheme will be and examines whether any other personal credit attributes can serve the same purpose. In our work, a survey was conducted to verify industry's perception on what attributes was essential for credit risk assessment. The result was compared with the implication from the neuro-fuzzy data mining on real transaction data. The comparison suggests that the perception on positive data is not absolutely correct and the positive data sharing cannot always achieve its purposes.
Original languageEnglish
Title of host publicationData Mining
Subtitle of host publicationTheory, Methodology, Techniques, and Applications
Pages319-329
Number of pages11
Publication statusPublished - 1 Dec 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3755 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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