부동산정보 기반 개인 및 개인사업자 대안신용평가모형 개발 (Development of Alternative Credit Rating Model for Individual and Sole Proprietor Based on Real Estate Information)

서지정보

· 발행기관 : 한국금융학회
· 수록지 정보 : 금융연구 / 38권 / 4호 / 1 ~ 45페이지
· 저자명 : 손승현, 김동구

초록

최근 개인 및 개인사업자에 대한 신용평가에서는 신용정보 이외에 다양한 비금융정보를 활용한 대안신용평가모형 개발이 활발히 이루어지고 있다. 이러한 비금융정보를 이용하여 기존 신용평가모형에서 반영하지 못했던 요인을 반영함으로써 금융이력이 부족한 개인이나 개인사업자의 보다 정확한 평가가 이루어질 수 있다. 특히 최근 사회적 이슈가 되고 있는 부동산 전세사기 등 서민들에게 많은 피해를 주고 있는 다양한 부동산 사고를 사전에 예방할 수 있는 대안모형의 필요성이 증가하고 있는 상황이다. 이에 본 연구에서는 부동산을 소유한 개인 및 개인사업자를 대상으로 소유한 부동산수, 공시가 및 예측시세, 다양한 권리정보(가등기, 가압류, 전세권, 저당권 등) 및 부동산 사고정보(경매, 공매, 임차권등기명령) 등 부동산정보에 기반을 둔 대안신용평가 모형을 제안한다. 제안모형은 하부모형으로 부동산모형, 소유자모형으로 구성되며, 개인사업자의 경우는 사업장모형이 추가된다. 검증결과, 제안모형의 안정성 및 변별력이 매우 우수하였으며, 특히 기존 모형과의 결합을 통하여 매우 높은 변별력 성능 향상 효과를 나타내었다. 또한 제안하는 대안신용평가모형을 통해 개인 및 개인사업자에 대한 좀 더 세밀하고 정교한 마케팅 및 리스크 관리가 가능할 것으로 기대한다.

영어초록

Recently, in credit ratings of individual and sole proprietor, alternative credit rating models that utilize various non-financial information in addition to credit information are being actively developed. By using this non-financial information to reflect factors that were not reflected in the existing credit rating model, an individual or sole proprietor with insufficient financial history can make a more accurate evaluation. In particular, there is a growing need for an alternative model that can prevent various real estate accidents that are causing a lot of damage to ordinary citizens, such as real estate lease fraud, which has recently become a social issue.
In this study, we propose an alternative credit rating model based on real estate information, such as the number of real estate properties owned, publicly announced and predicted prices, various rights information (provisional registration, temporary seizure, leasehold, mortgage, etc.), and real estate accident information(auction, public auction, lease registration order), targeting individual and sole proprietor who own real estate. The proposed model consists of a real estate model and an owner model as sub-models, and in the case of sole proprietor, a workplace model is added. Factors with low frequency of occurrence but high default rates are used as filtering factors, and if they exceed the filtering factor criteria, a grade suitable for the risk level is given.
The model development process was as follows: Based on the candidate factors, univariate significance analysis through primary categorization, significance analysis through secondary categorization, correlation analysis, and multivariate analysis were conducted in order. In multivariate analysis, we applied the logistic regression analysis methodology, which shows high efficiency in model stability and good/bad discrimination ability.
As a result of the verification, the stability and discrimination power of the proposed model were very excellent, and it showed a very high discrimination performance improvement effect through combination with the existing model. In particular, it can be seen that the combination of the real estate model (including real estate filtering factors) consisting of only real estate information and the existing model alone maintains very good discrimination power. Therefore, it will be possible to operate a model with high discrimination power even if the sub-model real estate model and real estate filtering factors are applied first before applying the proposed alternative model. In addition, we expect that the proposed alternative credit rating model will enable more detailed and sophisticated marketing and risk management for individual and sole proprietor.

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