• 한국벤처창업학회:학술대회논문집
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• 2020.11a
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• pp.127-130
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• 2020

금융시장 환경이 점차 변화하고 있다. 흔히 지점이라 불리는 오프라인 환경에서 애플리케이션을 이용하거나 웹페이지를 이용하는 온라인 비대면 환경으로 이동함에 따라 기존의 정형 정보를 중심으로 한 소비자 행동 예측 방법보다 더 나은 방법을 모색하기 이르렀다. 이에 따라 주관적 비정형 정보의 중요하게 된 것이다. 본 연구는 비대면 대출시장에서 주관적 비정형 정보의 하나인 SNS 프로필 사진과 대출상환에 영향을 미치는 변인을 파악하는 것을 목표로 한다. SNS 프로필 사진은 자신의 감정이나 상태를 표현하는 도구로 떠오르고 있으며, 이러한 차입자의 SNS 프로필사진을 분석함으로써 정보비대칭의 최소화로, 대출심사를 위한 신용평가에 유의적 요소들을 규명하는데 목적이 있다. 본 연구에서는 대출자들이 차입자에 대한 평가의 중요 고려 요소들을 규명하고 탐색하는데 초점을 맞춰 SNS 대안 신용평가만을 심사기준으로 이용한 대출인 텐스페이스의 AI LOAN 대출자중에서 2020년 2월부터 2020년 2월까지 대출자료를 확보할 예정이다. 이러한 자료 중에서 2020년 12월 30일을 기준으로 상환기일이 도래한 대출상환 자료 중 SNS사진을 순서형 로짓회귀모형을 이용해 분석하고자 한다.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.183-188
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• 2019

This study analyzes whether Income Contingent Loan achieves the policy goal of reducing the burden on higher education expenses with the emphasis on the repayment structure of the loan system and suggest ways to improve the incumbent policy. The study found that the voluntary repayment amount of the loan is much higher than the mandatory repayment amount. Therefore, various policy improvement measures are needed to activate the original purpose of the loan. We proposes improvements to the repayment, such as diversification of the repayment base rate, introduction of the loan integration, and analysis of loan default probability. In addition, this study has policy and academic implications in that it has suggested policy improvement measures by analyzing various overseas cases.

• Journal of Labour Economics
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• v.40 no.2
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• pp.69-87
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• 2017

This paper examined the impact of student loan on job search duration, explicitly considering the type of student loan. The data was collected from Korean Education & Employment Panel (KEEP) study released by KRIVET. The survival analysis shows the following two patterns. First, the students who used the student loan with guarantee tended to have longer job search duration of job search. Second, the students with the income contingent loan tended to have shorter job search duration to end up with lower wage.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.77-90
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• 2023

This study aims to investigate the potential of alternative credit assessment through Social Networking Sites (SNS) as a complementary tool to conventional loan review processes. It seeks to discern the impact of SNS usage characteristics and loan product attributes on credit loan repayment. To achieve this objective, we conducted a binomial logistic regression analysis examining the influence of SNS usage patterns, loan characteristics, and personal attributes on credit loan conditions, utilizing data from Company A's credit loan program, which integrates SNS data into its actual loan review processes. Our findings reveal several noteworthy insights. Firstly, with respect to profile photos that reflect users' personalities and individual characteristics, individuals who choose to upload photos directly connected to their personal lives, such as images of themselves, their private circles (e.g., family and friends), and photos depicting social activities like hobbies, which tend to be favored by individuals with extroverted tendencies, as well as character and humor-themed photos, which are typically favored by individuals with conscientious traits, demonstrate a higher propensity for diligently repaying credit loans. Conversely, the utilization of photos like landscapes or images concealing one's identity did not exhibit a statistically significant causal relationship with loan repayment. Furthermore, a positive correlation was observed between the extent of SNS usage and the likelihood of loan repayment. However, the level of SNS interaction did not exert a significant effect on the probability of loan repayment. This observation may be attributed to the passive nature of the interaction variable, which primarily involves expressing sympathy for other users' comments rather than generating original content. The study also unveiled the statistical significance of loan duration and the number of loans, representing key characteristics of loan portfolios, in influencing credit loan repayment. This underscores the importance of considering loan duration and the quantity of loans as crucial determinants in the design of microcredit products. Among the personal characteristic variables examined, only gender emerged as a significant factor. This implies that the loan program scrutinized in this analysis does not exhibit substantial discrimination based on age and credit scores, as its customer base predominantly consists of individuals in their twenties and thirties with low credit scores, who encounter challenges in securing loans from traditional financial institutions. This research stands out from prior studies by empirically exploring the relationship between SNS usage and credit loan repayment while incorporating variables not typically addressed in existing credit rating research, such as profile pictures. It underscores the significance of harnessing subjective, unstructured information from SNS for loan screening, offering the potential to mitigate the financial disadvantages faced by borrowers with low credit scores or those ensnared in short-term liquidity constraints due to limited credit history a group often referred to as "thin filers." By utilizing such information, these individuals can potentially reduce their credit costs, whereas they are supposed to accrue a more substantial financial history through credit transactions under conventional credit assessment system.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.453-455
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• 2023

본 연구는 은행에서 리스크 관리 자동화를 위해 고객의 대출 상환 여부 예측 모델을 제안하고자 한다. 예측 모델로 금융 데이터 같은 정형데이터에서 전통적으로 높은 성능을 보인 의사결정나무기반 모델 LightGBM, CatBoost, XGB 와 최근 제안된 정형데이터에서 사용할 수 있는 설명 가능한 딥러닝 기반 모델 TabNet 간의 성능 비교를 진행한다. 다만, 대출 상환 여부 데이터는 불균형 클래스 데이터로 구성되어있어 샘플링을 진행한다. SMOTE, Random Under Sampling, 혼합 방식을 비교해 가장 높은 성능의 샘플링 기법을 제안한다. 대출 상환 여부 예측 결과 TabNet 모델이 의사결정나무모델들보다 좋은 성능을 보여 정형데이터에서 의사결정나무 기반 모델을 딥러닝 모델이 대체 할 수 있는 가능성을 확인했다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.229-238
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• 2019

Before the scholarship loan system was implemented at the Korea Scholarship Foundation, the government's role was strengthened by the direct lending of student funds to banks and other financial institutions. However, the low repayment performance of student loans has raised concerns over the future of student loans and the government's financial burden. Moreover, since student loans are repaid even after graduating from college to support low-income families, it is highly unlikely that the repayment rate of student loans will improve unless the employment rate and income level of the borrower improve. In this paper, the final visualization graph is presented of the repayment amount of the student loan through the collection, storage, processing and analysis phase in the Big Data-based system. This could be the basis for visually checking the amount of student loans to come up with various ways to reduce the burden on the current student loan system.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.145-158
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• 2017

Lately, rapid increase of household debt and economic change has affected cash flow of household, insolvent risk has increased by high repayment burden of the principal and interest. Previous researches was progressing various discussion, composed objective repayment burden index about household debt. But it was relatively insufficient about perception of consumer. This research compare and analysis determinants of subjective repayment burden in household debt by income quintile, using 2016 Household Financial Welfare Survey. The research result is follows. The income 1 and 2 quartile groups have the higher monthly rent and credit card loan and the housing preparation loan ratio, the higher burden on repayment of the principal and interest. The Income 3 and 4 quartile groups have the higher 60s or older and member of household and real estate mortgage loan, the higher burden on repayment of the principal and interest. The Income 5 quartile group has the higher loan ratio for debt repayment preparation, the higher burden on repayment of the principal and interest.

• 주택과사람들
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• s.202
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• pp.18-19
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• 2007

DTI 규제 총부채상환비율(DTI)적용 여신 심사 기준이 시행되면서 주택 담보 대출은 더욱 위축될 전망이다. 대출 규제 내용과 이에 따라 달라질 수 있는 향후 부동산 시장을 전망해보자.

• Journal of Labour Economics
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• v.30 no.1
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• pp.55-83
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• 2007

This paper examines the welfare aspects of loan-based self-insurance against unemployment, and discusses the scope of government intervention in its provision. This paper deals with these issues in a model where the individuals may experience unemployment shocks frequently to leave little savings for retirement, so that the government may have to provide them with unemployment and retirement insurance benefits during their unemployment and retirement, respectively. We identify the two interesting features in the model: the externality that the self-insurance exerts, upon other social insurances, and the incentive of private sector to provide loans that exerts the externality upon other social insurances. In particular, this paper shows that, although the inefficiency associated with private loan warrants the government provision of loans to unemployed workers, the over-incentive of the private sector to offer loans may reduce the scope of the government intervention. This paper also shows that, unless the inefficiency associated with private loans is high, the private incentive for loans would reduce welfare because of the externality generated by private loans.

• 주택과사람들
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• s.208
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• pp.42-47
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• 2007

일시적 2주택자의 '대출 갈아타기(대환 대출)'가 막히면서 처분 조건부 아파트가 올 하반기 집값의 새로운 변수로 떠오르고 있다, 앞으로는 금융기관의 빚을 갚기 위해 대출을 받을 수 없게 되는 만큼, 올해 안에 기존 주택을 처분해 상환해야 하는 4만 6000건(5조 2600억 원)중 절반만 매물로 나와도 부동산 시장에 커다란 영향을 미칠 것으로 보인다.