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    이단계 일반화 선형모형을 이용한 은행 고객의 연체성향 분석 = Analysis of Household Overdue Loans by Using a Two-stage Generalized Linear Model

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    https://www.riss.kr/link?id=A105149878

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    In this paper, we analyze household overdue loans in Korea which has been causing serious social and economical problems. We consider customers of Bank A in Korea and focus on overdue cash services which have been snowballing in the past few years. From analysis of overdue loans, one can predict possible delays for current customers as well as build a credit evaluation and risk management system for future customers. As a statistical analytical tool, we propose a two-stage Generalized Linear regression Model (GLM) which assumes a logistic model for presence/non-presence of overdue and a gamma model for the amount of overdue in the case of overdue. We perform goodness of fit test for the two-stage model and select significant explanatory variables in each stage of the model. It turns out that age, the amount of credit loans from other financial companies, the amount of cash service from other companies, debit balance, the average amount of cash service, and net profit are important explanatory variables relevant to overdue credit card cash service in Korea.
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    In this paper, we analyze household overdue loans in Korea which has been causing serious social and economical problems. We consider customers of Bank A in Korea and focus on overdue cash services which have been snowballing in the past few years. Fr...

    In this paper, we analyze household overdue loans in Korea which has been causing serious social and economical problems. We consider customers of Bank A in Korea and focus on overdue cash services which have been snowballing in the past few years. From analysis of overdue loans, one can predict possible delays for current customers as well as build a credit evaluation and risk management system for future customers. As a statistical analytical tool, we propose a two-stage Generalized Linear regression Model (GLM) which assumes a logistic model for presence/non-presence of overdue and a gamma model for the amount of overdue in the case of overdue. We perform goodness of fit test for the two-stage model and select significant explanatory variables in each stage of the model. It turns out that age, the amount of credit loans from other financial companies, the amount of cash service from other companies, debit balance, the average amount of cash service, and net profit are important explanatory variables relevant to overdue credit card cash service in Korea.

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    참고문헌 (Reference)

    1 "comparisons and applications of some estimators and tests Journal of Econometrics"

    2 "Zero-in?ated Poisson and binomial regression with random e??" 56 : 1030-1039, 2000

    3 "SAS System for Windows" SAS Institute Inc. 8 : 2000

    4 "On estimation of the Poisson parameter in zero-modi?ed Poisson models" 34 : 441-451, 2000

    5 "D.(1992" . Zero-in?ated Poisson regression withanapplicationtorandomdefects

    6 "Construction of con?dence intervals for the mean of a population containing many zero values" 16 : 362-368, 1998

    7 ". Econometric models based on count data" 1986

    1 "comparisons and applications of some estimators and tests Journal of Econometrics"

    2 "Zero-in?ated Poisson and binomial regression with random e??" 56 : 1030-1039, 2000

    3 "SAS System for Windows" SAS Institute Inc. 8 : 2000

    4 "On estimation of the Poisson parameter in zero-modi?ed Poisson models" 34 : 441-451, 2000

    5 "D.(1992" . Zero-in?ated Poisson regression withanapplicationtorandomdefects

    6 "Construction of con?dence intervals for the mean of a population containing many zero values" 16 : 362-368, 1998

    7 ". Econometric models based on count data" 1986

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
    2027 평가 재인증평가 신청대상 (재인증)
    2021-01-01 등재 등재학술지 유지 (재인증) KCI등재
    2018-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2015-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2011-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2009-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2007-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2005-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2002-07-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    2000-01-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    학술지 인용정보

    학술지 인용정보
    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.38 0.38 0.38
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.35 0.34 0.565 0.17
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