• 제목/요약/키워드: Lending data

검색결과 89건 처리시간 0.02초

Internal Company Factors as Determining Variables for Improving Bank Lending

  • PRAWITASARI, Dian;KADARNINGSIH, Ana;MACHMUDDAH, Zaky;UD-DIN, Maaz
    • The Journal of Asian Finance, Economics and Business
    • /
    • 제7권8호
    • /
    • pp.205-212
    • /
    • 2020
  • This study seeks to examine the main factors, external and internal to the bank, that enhance bank lending. Bank lending is one of the connecting bridges in sustaining society. Internal factors consist of ROA, DPK, and CAR. External factors are economic growth and interest rate of Bank Indonesia. The population of this research consists of traditional commercial banks listed on the IDX over the 2014-2017 period. Samples were chosen by purposive sampling method. This study uses secondary data with 56 samples; data analysis uses multiple linear regression. The findings of the study show that internal factors have a greater impact on increasing bank lending than external factors. The main variable among internal factors that influences increase in bank lending is ROA. DPK is the internal factor with the smallest impact on increasing bank lending. The implication of the study is that determining the bank lending should take more account of CAR, DPK, ROA, BI interest rates, and economic growth in making decisions about the amount of lending. These variables can only have a slight effect on increasing lending, though. Besides, internal factors such as NPL, LDR or non-economic factors also need to be considered in channeling bank credit.

P2P 대부 우수 대출자 예측을 위한 합성 소수집단 오버샘플링 기법 성과에 관한 탐색적 연구 (Exploring the Performance of Synthetic Minority Over-sampling Technique (SMOTE) to Predict Good Borrowers in P2P Lending)

  • 프란시스 조셉 코스텔로;이건창
    • 디지털융복합연구
    • /
    • 제17권9호
    • /
    • pp.71-78
    • /
    • 2019
  • 본 연구는 P2P 대부 플랫폼에서 우수 대출자를 예측시 유용한 합성 소수집단 오버샘플링 기법을 제안하고 그 성과를 실증적으로 검증하고자 한다. P2P 대부 관련 우수 대출자를 추정할 때 일어나는 문제점중의 하나는 클래스 간 불균형이 심하여 이를 해결하지 않고서는 우수 대출자 예측이 쉽지 않다는 점이다. 이러한 문제를 해결하기 위하여 본 연구에서는 SMOTE, 즉 합성 소수집단 오버샘플링 기법을 제안하고 LendingClub 데이터셋에 적용하여 성과를 검증하였다. 검증결과 SMOTE 방법은 서포트 벡터머신, k-최근접이웃, 로지스틱 회귀, 랜덤 포레스트, 그리고 딥 뉴럴네트워크 분류기와 비교하여 통계적으로 우수한 성과를 보였다.

Non-Bank Lending to Firms: Evidence from Korean Firm-Level Data

  • Lee, Mihye
    • 산경연구논집
    • /
    • 제9권9호
    • /
    • pp.15-23
    • /
    • 2018
  • Purpose - The purpose of this paper is to examine the determinants of non-bank depository institutions (non-bank financial corporations) lending to firms. The paper aims to contribute to the existing literature by providing empirical evidence from firm-level data and unveiling factors related to access to non-bank financial corporations by firms. Research design, data, and methodology - We used the data on borrowing by firms from CRETOP from years 2008 to 2011. Using the manufacturing industry, we examined what firm-level characteristics explained the increase in borrowing from non-bank financial corporations rather than the banks. Results - Analyzing the firm-level data from 2008 to 2011, we found that firms were more likely to borrow from non-bank financial insti­tutions as the size of the firm increases, implying that large firms have more access to non-bank financing than small and medium-sized firms. In addition, it also showed that small and medium-sized firms moved to non-bank financial corporations for loans. Conclusion - Non-bank depository institutions are not a sub­stitute for bank lending to firms. More specifically, they replace bank lending to firms mostly for large firms rather than small and medium-sized firms. Also, collateral and other firm-level characteristics do not matter in accounting for non-bank lending to firms.

Do Firm and Bank Level Characteristics Matter for Lending to Firms during the Financial Crisis?

  • Lee, Mihye
    • 산경연구논집
    • /
    • 제9권5호
    • /
    • pp.37-46
    • /
    • 2018
  • Purpose - This paper explores the determinants of bank lending to firms during and after the global financial crisis using firm- and bank-level data to answer the questions what caused the contraction of lending to firms despite the loosening monetary policy during this crisis period. Research design, data, and methodology - We investigate the effects of the monetary policy that followed the global financial crisis on firms borrowing. We use a dynamic panel model to address how firms lending respond to monetary policy. The data are obtained from CRETOP and we consider the manufacturing sector for the analysis to control for unobserved heterogeneity such as industry-specific shocks. Results - The findings from the empirical analysis suggest that both bank- and firm-level characteristics are significant determinants of bank lending. Especially, we find that corporate risk, measured by default risk, is one of the key factors that led to a decline in lending during the crisis. Conclusions - This paper shows that companies borrow more from liquid banks, and high bank capital can also contribute to an increase in a firm's borrowing from banks. Especially, the results confirm that the default rate measured at the firm level has increased during and after the global financial crisis, which implies that default risk interplays with other firm and bank-level characteristics.

Related Loan on Real Estate Firm Performance in an Emerging Market

  • PURWANTO, Purwanto
    • The Journal of Asian Finance, Economics and Business
    • /
    • 제7권10호
    • /
    • pp.697-706
    • /
    • 2020
  • This study investigates the relationship between related loan, ownership concentration and real estate firm performance. The data was collected from 35 real estate firms listed on Indonesia Stock Exchange from 2007 to 2012. Related loans are viewed from the angle of related lending and loan. Related lending and loan is measured by the related lending on total lending ratio and related loan on total loan ratio. Firm performance is measured by the asset turnover ratio and return on assets ratio. Ownership concentration is measured by the right cash flow. The data analysis was done with regression analysis and panel data. The results of the study found that related loans had a positive effect on sales but had no effect on profits. This supports the efficient transaction hypothesis. On the other hand, related lending has a positive effect on profits that supports opportunistic transactions. Ownership concentration moderates the effect of related loan on company's performance. The related lending are beneficial for mutually supporting activities in the real estate sector business group in Indonesia, but related loans have the potential to be used in tunneling activities. The paper contributes to the related party transaction in benefits-risks of related lending and related loan in uncertainty context.

The Effect of Lending Structure Concentration on Credit Risk: The Evidence of Vietnamese Commercial Banks

  • LE, Thi Thu Diem;DIEP, Thanh Tung
    • The Journal of Asian Finance, Economics and Business
    • /
    • 제7권7호
    • /
    • pp.59-72
    • /
    • 2020
  • This paper examines whether lending structure can lower credit risk by employing econometric techniques of panel data for the Vietnamese banking system at the bank level used by economic sectors from 2011 to 2016. New light is being shed on assessing the impact of each industry's debt outstanding on credit risk. Adopting findings from previous studies, we assess credit risk from two different sources, including loan loss provision and non-performing loan. Moreover, we also focus on observing lending structure in many different aspects, from concentrative levels to the short-term and long-term stability levels of lending structure. The Generalized Method of Moments (GMM) estimator was applied to analyze the relationship between concentration and banking risks. In general, the results show that lending concentration may decrease credit risk. It is interesting to observe that the Vietnamese commercial bank lending portfolios have, on average, higher levels of diversity across different sectors. In particular, the increase in hotel and restaurant lending contributes to decrease credit risk while the lending portfolios of banks in agriculture, electricity, gas and water increase credit risk. This study suggests the need for further analysis and research about portfolio risks in lending activities for maintaining efficiency and stability in the commercial banking system.

Factors Determining Adoption of Fintech Peer-to-Peer Lending Platform: An Empirical Study in Indonesia

  • SUNARDI, Rudy;HAMIDAH, Hamidah;BUCHDADI, Agung Dharmawan;PURWANA, Dedi
    • The Journal of Asian Finance, Economics and Business
    • /
    • 제9권1호
    • /
    • pp.43-51
    • /
    • 2022
  • Platform lending or online lending, sometimes called peer-to-peer (P2P) lending, arose due to the digital revolution to meet people's requirements for simple fund borrowing. It quickly became an alternative to other traditional lending techniques, for example, loans banks. Along with the growth of P2P lending, several academics have investigated how information technology is used in financial services, emphasizing extended application methods. This study proposes an enhanced technology acceptance model (TAM) that investigates how consumers embrace P2P lending platforms by using quality of service and perceived risk as drivers of trust, relative advantage and compatibility as drivers of perceived usefulness. For the purpose of this study, we created a questionnaire, distributed it to clients of P2P lending platforms and fintech services in general in cities in Java, Indonesia. We received 290 replies to our questionnaire. The data was analyzed to test the hypotheses using structural equation modeling (SEM). The findings show that consumers' trust, relative advantage, perceived usefulness, and perceived ease of use in P2P lending platforms substantially affect their views toward adoption. The research's findings are useful for fine-tuning platform marketing strategies and putting strategic goals into action.

The Determinants of Potential Failure of Islamic Peer-to-Peer Lending: Perceptions of Stakeholders in Indonesia

  • MUHAMMAD, Rifqi;FAKHRUNNAS, Faaza;HANUN, Amalia Khairina
    • The Journal of Asian Finance, Economics and Business
    • /
    • 제8권2호
    • /
    • pp.981-992
    • /
    • 2021
  • This study identifies the determinants of potential failure of Islamic Peer-to-Peer (P2P) lending in Indonesia, and the mediating effect of Islamic ethics on reducing the potential for failure of Islamic P2P lending. This study uses primary data retrieved through questionnaires from the perspective of 152 stakeholders in Islamic P2P lending. Using a structural equation model (SEM), the study found that indebtedness, financing size, and governance have positive and significant relationships with the potential failure of Islamic P2P lending. This study provides evidence that the customer's internal conditions and the governance structure applied can increase the potential failure of Islamic P2P lending. Further, Islamic ethics is evidently able to partially reduce the potential failure of Islamic P2P lending by lessening risk management exposure, but it fails to address failure through Ponzi scheme exposure. As an implication, this study suggest that Islamic P2P lending must implement Islamic ethics more comprehensively by optimizing the advisory and supervisory role of the shariah board within their overall boards of directors also in their operational activities. Finally, it also adds to the existing knowledge on financial technology literature, particularly on the determinants of potential failure of financial technology from the perspective of stakeholders.

공공대출보상권 제도 논의를 위한 공공도서관 대출 통계 분석 (Analysis of the Loan Statistics of Public Libraries for Discussion of the Introduction of Public Lending Right)

  • 이흥용;김영석
    • 한국도서관정보학회지
    • /
    • 제50권3호
    • /
    • pp.217-238
    • /
    • 2019
  • 최근 들어 우리나라에서 공공대출보상권 제도에 관한 관심이 커지고 있다. 본 연구는 2014년부터 2018년까지 5년간 전국 820개 공공도서관의 대출통계를 분석하여 공공대출보상권 제도의 보상금 산정 논의에 필요한 기초자료를 수집하는 데 그 목적이 있다. 우리나라 공공도서관의 대출 분석을 위해 국립중앙도서관이 관리 운영하고 있는 '도서관 정보나루'가 제공하는 11억 7,830만건의 대출데이터를 사용하였다. 공공도서관 대출 통계 분석을 통해 지난 5년간 가장 많이 대출된 도서 상위 125권을 파악하였다. 그리고 그 도서들을 대상으로 저자별 현황, 저자의 국별 현황, 일본 저자의 현황, 출판사별 현황, 학습만화의 대출 현황 등을 분석하였다.

Determining Personal Credit Rating through Voice Analysis: Case of P2P loan borrowers

  • Lee, Sangmin
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제15권10호
    • /
    • pp.3627-3641
    • /
    • 2021
  • Fintech, which stands for financial technology, is growing fast globally since the economic crisis hit the United States in 2008. Fintech companies are striving to secure a competitive advantage over existing financial services by providing efficient financial services utilizing the latest technologies. Fintech companies can be classified into several areas according to their business solutions. Among the Fintech sector, peer-to-peer (P2P) lending companies are leading the domestic Fintech industry. P2P lending is a method of lending funds directly to individuals or businesses without an official financial institution participating as an intermediary in the transaction. The rapid growth of P2P lending companies has now reached a level that threatens secondary financial markets. However, as the growth rate increases, so does the potential risk factor. In addition to government laws to protect and regulate P2P lending, further measures to reduce the risk of P2P lending accidents have yet to keep up with the pace of market growth. Since most P2P lenders do not implement their own credit rating system, they rely on personal credit scores provided by credit rating agencies such as the NICE credit information service in Korea. However, it is hard for P2P lending companies to figure out the intentional loan default of the borrower since most borrowers' credit scores are not excellent. This study analyzed the voices of telephone conversation between the loan consultant and the borrower in order to verify if it is applicable to determine the personal credit score. Experimental results show that the change in pitch frequency and change in voice pitch frequency can be reliably identified, and this difference can be used to predict the loan defaults or use it to determine the underlying default risk. It has also been shown that parameters extracted from sample voice data can be used as a determinant for classifying the level of personal credit ratings.