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용어보기논문에서 용어와 풀이말을 자동 추출한 결과로, 시범 서비스 중입니다. AI-Helper

금융기관의 가계대출은 주택담보 대출과 함께 신용 대출액도 꾸준히 증가하고 있으며 , 대출금액이 증가함에 따라 연체율도 함께 증가하게 되어 금융기관의 자산건전성을 위해 채권관리 부분이 주요 이슈가 되고 있다.
본 논문은 부실채권 회수에 유의미한 요소를 분석하여 부실채권 회수율을 향상을 위한 채권회수에 유의미한 변수를 찾고자함에 있다. 이를 위해 A금융사의 B채권 1만여건과 C사의 채권추심인 250여명의 데이터를 사용, 로지스틱 회귀분석과 ...

금융기관의 가계대출은 주택담보 대출과 함께 신용 대출액도 꾸준히 증가하고 있으며 , 대출금액이 증가함에 따라 연체율도 함께 증가하게 되어 금융기관의 자산건전성을 위해 채권관리 부분이 주요 이슈가 되고 있다.
본 논문은 부실채권 회수에 유의미한 요소를 분석하여 부실채권 회수율을 향상을 위한 채권회수에 유의미한 변수를 찾고자함에 있다. 이를 위해 A금융사의 B채권 1만여건과 C사의 채권추심인 250여명의 데이터를 사용, 로지스틱 회귀분석과 다중회귀분석을 실시하여 부실채권의 회수 성공 여부와 회수 성공시 회수소요기간에 유의미한 관련 변수분석과 월 회수금액에 영향을 주는 채권추심인 변수 분석을 실시하였다.
분석 결과로 연체금액, 타사불량건수, 채무자 나이가 적을수록 회수성공 가능성이 높았으며, 사후관리건수와 채권추심인 나이는 많을수록 회수성공 가능성이 높게 나타났다. 회수소요기간 분석의 경우에는 연체금액이 클수록, 타사불량건수, 채권추심인 근무기간이 짧을수록 회수소요기간이 짧아지는 것으로 분석되었다. 월 회수금액과 채권추심인의 특성 분석에서는 채권추심인의 나이가 적을수록, 전화번호 수정건수, SMS발송건수, 서류스캔 등록건수가 많을수록 회수금액이 많았으며, 채권추심인의 주요경력이 제2금융권일 경우에 월회수금액이 상대적으로 높게 나타나는 것으로 확인되었다.
본 연구의 결과를 이용하여 채권추심 관리지표 선정, 부실채권 관리기법 개발 및 추심조직 인원관리 방안 등 채권회수 전략 구성시에 참고할 수 있는 객관적자료로 사용되어 부실채권 회수율 향상에 도움이 되기를 기대한다.

Abstract ▼ AI-Helper

Among the household loans, both the housing mortgage loans and the credit loans have been increasing steadily, and as the household loans increases, the default rate has also increased, and thus, the credit management has become a major issue for the asset soundness of the financial institutions.

Among the household loans, both the housing mortgage loans and the credit loans have been increasing steadily, and as the household loans increases, the default rate has also increased, and thus, the credit management has become a major issue for the asset soundness of the financial institutions.
The purpose of this study was to analyze the significant factors in collection of the non-performing credits and thereby, find some significant variables for improvement of the non-performing credit repayment rates. For this purpose, this study sampled about 10 thousand credits of 'B' financial institute and about 250 credit collectors of 'C' company. The data collected thus, were processed for logistic regression analysis and multiple regression analysis to check if the non-performing credits had been repaid or not. The data were also processed to analyze the relevant variables with regard to the period for collection of the credits, and with regard to the credit collectors' variables affecting the monthly credit collection.
As a result, it was found that the less the amount of the non-performing credits and the average non-performing credits were, and the older the debtors were, the possibility of collecting the credit was higher, and that the more the number of the post-service cases was and the younger the credit collectors were, the possibility of collecting the credits was higher. On the other hand, it was found in terms of the period required for the collection of the credits that the more the default credits were, the less other companies' default cases were, and the shorter the credit collectors' career was, the period for collecting the credits was shorter. Furthermore, as a result of analyzing the monthly amount of collected credits and the credit collectors' demographic variables, it was found that the younger the collectors were, and the more frequently the phone numbers had been changed, and the more frequently the SMS had been transmitted to the debtors, and the more the document scanning had been registered, the more credits were collected. In case that when the credit collectors had worked for the second financial institutions, they collected more credits every month.
Lastly, it is hoped that this study would be useful for selection of the credit collection management indices, development of the non-performing credit management techniques, effective management of the collectors' group and the designing of the credit collection strategies and thereby, would conduce to improvement of the non-performing credit repayments.

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