• Title/Summary/Keyword: 대출연체

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Study on the Estimating Pattern for Rate of Arrearage in Domestic Bank (국내 시중은행의 연체율 패턴 분석에 관한 연구)

  • Park, Hyoung-Keun;Kim, Hee-Cheul
    • Proceedings of the KAIS Fall Conference
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    • 2009.12a
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    • pp.727-730
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    • 2009
  • 국내일반은행 연체율은 그룹(대출형태)별로 다양한 원인에 의해서 연체율 결정이 이루어지고 있어 복잡성을 띠고 있다. 본 연구에서는 복잡성을 띠고 있는 연체율의 제 변인들을 파악하기 위해 패널 데이터 모형를 이용한 연구 모형을 설정하고 이를 통해 연체율에 결정적으로 영향을 미치는 제 변인에 대하여 조사, 분석, 검증한다. 본 연구는 3 그룹(기업대출, 가계대출, 신용카드 대출)을 분석대상으로 하였다. 분석기간은 2005년 1월부터 2009년 6월까지의 자료를 이용하였고. 국내은행 연체율을 종속변수로 설정하고 소비자물가지수, 종합주가지수, 환율, 동행(경기)종합지수, 국민주택채권, 고용률을 독립 변수로 투입하였다. 국내일반은행 연체율 요인을 추정한 결과 소비자물가지수는 정(+)의 영향을 미치는 유의한 변수로 나타나고 동행(경기)종합지수와 종합주가지수는 음(-)의 영행을 나타내는 유의적인 변수이지만 환율, 국민주택채권 그리고 고용률은 각각 유의적인 음(-)의 영행을 나타내는 비유의적인 변수로서 연체율에 큰 영향으로 주지는 않은 것으로 나타났다.

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A Study on the Effect of Delinquency Rate of Real Estate PF on Macroeconomic Variables (거시경제변수에 따른 부동산PF 연체율에 관한 연구)

  • Roh, Chi-Young;Kim, Hyung-Joo
    • The Journal of the Korea Contents Association
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    • v.18 no.4
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    • pp.416-427
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    • 2018
  • As the loan size of real estate PF is huge, its market ripple effect gets bigger when overdue occurs. Accordingly, the management of the delinquency rate and macroeconomic analysis are required. As the preceding research mainly proceeded with microeconomic analysis through the real estate PF data of individual banks to evaluate importance of list or analyzed core factors for delinquency, it lacked research on comprehensive real estate PF size. In order to overcome the limitations of such data, this research studied real estate PF delinquency rate of the entire market and effect relationship by the size. The research utilized the size of real estate PF loans, money supply, interest rate, consumer price index(CPI), and GDP data. Also, it applied the first model of VECM as linear relationship between at least two or more variables, following the result of co-integration test. As a result of Granger-causality test, the real estate PF loans delinquency rate is influenced by their loan size, and as a result of impulse response analysis, the interest rate is shown to be affecting delinquency rate the most. Interest rate could risesomeday and aggravate the delinquency rate of real estate PF. Also, risk exposure could be serious as the loan size increases.Therefore, the management of real estate PF delinquency rate requires continuous monitoring, tracking and observing issued loans from a macro point of view. The plans to prevent delinquency will be necessary.

Developing the credit risk scoring model for overdue student direct loan (학자금 대출 연체의 신용위험 평점 모형 개발)

  • Han, Jun-Tae;Jeong, Jina
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1293-1305
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    • 2016
  • In this paper, we develop debt collection predictive models for the person in arrears by utilizing the direct loan data of the Korea Student Aid Foundation. We suggest credit risk scorecards for overdue student direct loan using the developed 3 models. Model 1 is designed for 1 month overdue, Model 2 is designed for 2 months overdue, and Model 3 is designed for overdue over 2 months. Model 1 shows that the major influencing factors for the delinquency are overdue account, due data for payment, balance, household income. Model 2 shows that the major influencing factors for delinquency loan are days in arrears, balance, due date for payment, arrears. Model 3 shows that the major influencing factors for delinquency are the number of overdue in recent 3 months, due data for payment, overdue account, arrears. The debt collection predictive models and credit risk scorecards in this study will be the basis for segmented management service and the call & collection strategies for preventing delinquency.

A Systematic Analysis on Default Risk Based on Delinquency Probability

  • Kim, Gyoung Sun;Shin, Seung Woo
    • Korea Real Estate Review
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    • v.28 no.3
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    • pp.21-35
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    • 2018
  • The recent performance of residential mortgages demonstrated how default risk operated separately from prepayment risk. In this study, we investigated the determinants of the borrowers' decisions pertaining to early termination through default from the mortgage performance data released by Freddie Mac, involving securitized mortgage loans from January 2011 to September 2013. We estimated a Cox-type, proportional hazard model with a single risk on fundamental factors associated with default options for individual mortgages. We proposed a mortgage default model that included two specifications of delinquency: one using a delinquency binary variable, while the other using a delinquency probability. We also compared the results obtained from two specifications with respect to goodness-of-fit proposed in the spirit of Vuong (1989) in both overlapping and nested models' cases. We found that a model with our proposed delinquency probability variable showed a statistically significant advantage compared to a benchmark model with delinquency dummy variables. We performed a default prediction power test based on the method proposed in Shumway (2001), and found a much stronger performance from the proposed model.

A Study on the Factors of Normal Repayment of Financial Debt Delinquents (국내 연체경험자의 정상변제 요인에 관한 연구)

  • Sungmin Choi;Hoyoung Kim
    • Information Systems Review
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    • v.23 no.1
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    • pp.69-91
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    • 2021
  • Credit Bureaus in Korea commonly use financial transaction information of the past and present time for calculating an individual's credit scores. Compared to other rating factors, the repayment history information accounts for a larger weights on credit scores. Accordingly, despite full redemption of overdue payments, late payment history is reflected negatively for the assessment of credit scores for certain period of the time. An individual with debt delinquency can be classified into two groups; (1) the individuals who have faithfully paid off theirs overdue debts(Normal Repayment), and (2) those who have not and as differences of creditworthiness between these two groups do exist, it needs to grant relatively higher credit scores to the former individuals with normal repayment. This study is designed to analyze the factors of normal repayment of Korean financial debt delinquents based on credit information of personal loan, overdue payments, redemption from Korea Credit Information Services. As a result of the analysis, the number of overdue and the type of personal loan and delinquency were identified as significant variables affecting normal repayment and among applied methodologies, neural network models suggested the highest classification accuracy. The findings of this study are expected to improve the performance of individual credit scoring model by identifying the factors affecting normal repayment of a financial debt delinquent.

A Study of Policy Direction by City and Province through the Prediction of Household Loan Delinquency Rate (가계대출 연체율 예측을 통한 시도별 정책 방향성 연구)

  • Su-jin Lee;Jeong-in Won;Hee-yong Kang;In-seong Lee;Gun Kim;Jin Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.380-381
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    • 2023
  • 최근 경제침체로 인해 지속되는 연체율 상승의 원인을 지역별 및 시차별로 분석하였다. 독립변수를 가계대출변수, 부동산지수변수, 경제지표변수로 나누었고 통계적 모델링을 통해 총 19 가지 변수로 연체율을 예측하였다. 각 지역마다 상이한 결과가 도출되었는데 이를 바탕으로 지역별 연체율 감소 정책을 제안한다.

A Study on the Book Circulation Rules of Public Library in Korea (전국 공공도서관 대출규정 조사 연구)

  • Yoon, Hee-Yoon
    • Journal of Korean Library and Information Science Society
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    • v.51 no.1
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    • pp.349-372
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    • 2020
  • Regardless of East and West, public libraries provide various services to their communities based on collections. The decisive reason for local residents to visit public libraries is to access and borro w collections. An important condition maintenance to support these activities and services is the library circulation(usage) rules. Therefore, this study compared and analyzed the library membership, maximum loan items, loan period, loan reserve and renewal, overdue fines, disposal of lost and damaged items, loan of non-book materials, loan regulations for the disabled. And after checking the relative deviations in connection with the library cases of major developed countries, this study proposed the improvement of circulation rules. In order to minimize public complaints about circulation services and to relieve the burden of practitioners such as personnel disadvantage due to administrative audit for non-recoverable ite ms, public libraries must faithfully rearrange the circulation rules and regulations.

Estimating the Determinants for Rate of Arrearage in Domestic Bank: A Panel Data Model Approach (패널 데이터모형을 적용한 국내일반은행 연체율 결정요인 추정에 관한 연구)

  • Kim, Hee-Cheu;Park, Hyoung-Keun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.1
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    • pp.272-277
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    • 2010
  • In respect complication of group, rate of arrearage in domestic bank is composed of various factors. This paper studies focus on estimating the determinants of the rate of arrearage in domestic bank using panel data model. The volume of analysis consist of 3 groups(loaned patterns of enterprise, housekeeping, credit card). Analyzing period be formed over a 54 point(2005. 1~ 2009. 06). In this paper dependent variable setting up rate of arrearage in domestic bank, explanatory(independent) variables composed of the consumer price index, composite stock price index, rate of exchange, the coincident composite index, national housing bonds and employment rate. The result of estimating the rate of arrearage in domestic bank provides empirical evidences of significance positive relationships between the consumer price index However this study provides empirical evidences of significance negative relationships between the coincident composite index and the composite stock price index. The explanatory variables, that is, rate of exchange, national housing bonds and the employment rate are non-significance variables of negative factor. Implication of these findings are discussed for content research and practices.

Artificial Intelligence Techniques for Predicting Online Peer-to-Peer(P2P) Loan Default (인공지능기법을 이용한 온라인 P2P 대출거래의 채무불이행 예측에 관한 실증연구)

  • Bae, Jae Kwon;Lee, Seung Yeon;Seo, Hee Jin
    • The Journal of Society for e-Business Studies
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    • v.23 no.3
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    • pp.207-224
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    • 2018
  • In this article, an empirical study was conducted by using public dataset from Lending Club Corporation, the largest online peer-to-peer (P2P) lending in the world. We explore significant predictor variables related to P2P lending default that housing situation, length of employment, average current balance, debt-to-income ratio, loan amount, loan purpose, interest rate, public records, number of finance trades, total credit/credit limit, number of delinquent accounts, number of mortgage accounts, and number of bank card accounts are significant factors to loan funded successful on Lending Club platform. We developed online P2P lending default prediction models using discriminant analysis, logistic regression, neural networks, and decision trees (i.e., CART and C5.0) in order to predict P2P loan default. To verify the feasibility and effectiveness of P2P lending default prediction models, borrower loan data and credit data used in this study. Empirical results indicated that neural networks outperforms other classifiers such as discriminant analysis, logistic regression, CART, and C5.0. Neural networks always outperforms other classifiers in P2P loan default prediction.

Estimating the Determinants of Loan Amount of Housing Mortgage : A Panel Data Model Approach (주택 담보 가계 대출액 결정요인 추정에 관한 패널 데이터 모형 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.7
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    • pp.183-190
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    • 2011
  • Loan amount of housing mortgage is composed of various factors. This study paper studies focuses on estimating the determinants of a loan amount of housing mortgage. The region for analysis consist of seven groups, that is, metropolitan city (such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 45 time points(2007. 01.~ 2010. 09). In this paper the dependent variable setting up loan amount of housing mortgage, explanatory(independent) variables are composed of the consumer price index, unemployment rate, average monthly household income per household, expenditure rate of health care, composite stock price index and overdue rate of household loans for commercial bank. In looking at the factors which determine loan amount of housing mortgage, evidence was produced supporting the hypothesis that there is a significant positive relationship between the consumer price index and unemployment rate. The study also produced evidence supporting the view that there is a significant negative relationship between expenditure rate of health care. The study found that average monthly household income per household, expenditure, composite stock price index and overdue rate of household loans for commercial bank were not significant variables. The implications of these findings are discussed for further research.