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Small Business Credit Scoring and Credit Availability [PDF]
SSRN Electronic Journal, 2005 U.S. commercial banks are increasingly using credit scoring models to underwrite small business credits. This paper discusses this technology, evaluates the research findings on the effects of this technology on small business credit availability, and links these findings to a number of research and public policy issues.
Allen N. Berger, W. Scott Frame
openaire +3 more sources
Reject inference methods in credit scoring. [PDF]
J Appl Stat, 2021 The granting process is based on the probability that the applicant will refund his/her loan given his/her characteristics. This probability, also called score, is learnt based on a dataset in which rejected applicants are excluded. Thus, the population on which the score is used is different from the learning population.
Ehrhardt A +4 more
europepmc +5 more sources
Technological and Economic Development of Economy, 2022 Conventional credit scoring models evaluated by predictive accuracy or profitability typically serve the financial institutions and can hardly reflect their contribution on financial stability.
Yufei Xia, Zijun Liao, Jun Xu, Yinguo Li
doaj +2 more sources
A credit scoring model based on the Myers–Briggs type indicator in online peer-to-peer lending [PDF]
Financial Innovation, 2022 Although psychometric features have been considered for alternative credit scoring, they have not yet been applied to peer-to-peer (P2P) lending because such information is not available on platforms.
Hyunwoo Woo, So Young Sohn
doaj +2 more sources
ANÁLISIS DEL CREDIT SCORING [PDF]
RAE: Revista de Administração de Empresas, 2013 The problem of unpaid bank debts is becoming increasingly important in developed countries. Many empirical works are being published in an attempt to find a model capable of determining as accurately as possible whether an individual requesting a loan ...
Rosa Puertas Medina +1 more
doaj +5 more sources
NOTE: non-parametric oversampling technique for explainable credit scoring [PDF]
Scientific ReportsCredit scoring models are critical for financial institutions to assess borrower risk and maintain profitability. Although machine learning models have improved credit scoring accuracy, imbalanced class distributions remain a major challenge.
Seongil Han +4 more
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Extreme Learning Machine Enhanced Gradient Boosting for Credit Scoring
Algorithms, 2022 Credit scoring is an effective tool for banks and lending companies to manage the potential credit risk of borrowers. Machine learning algorithms have made grand progress in automatic and accurate discrimination of good and bad borrowers.
Yao Zou, Changchun Gao
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IMPROVING CREDIT SCORING MODEL OF MORTGAGE FINANCING WITH SMOTE METHODS IN SHARIA BANKING [PDF]
Russian Journal of Agricultural and Socio-Economic Sciences, 2019 Credit scoring is a feasibility test system to provide financing with the aim of reducing the risk of default on mortgage financing (KPR). This study analyze the characteristics of customers of PT Bank XYZ and design a credit scoring model for mortgage ...
Wibowo H.E., Mulyati H., Saptono I.T.
doaj +1 more source
Assessing Creditworthiness in the Age of Big Data
Journal of Extreme Anthropology, 2021 The purpose of this article is twofold: first, we show how algorithms have become increasingly central to financial credit scoring; second, we draw on this to further develop the anthropological study of algorithmic governance.
Pernille Hohnen +2 more
doaj +1 more source
Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets
Financial Innovation, 2022 For the emerging peer-to-peer (P2P) lending markets to survive, they need to employ credit-risk management practices such that an investor base is profitable in the long run.
Štefan Lyócsa +3 more
doaj +1 more source