Results 11 to 20 of about 25,439 (153)
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
SSRN Electronic Journal, 2020 We study how the existence of cutoffs in credit scores affects the behavior of homebuyers. Borrowers are more likely to purchase houses after their credit scores cross over a cutoff to qualify them for a higher credit score bin. However, the credit accounts of these individuals (crossover group) are more likely to become delinquent within four years ...
Hu, Luojia, Huang, Xing, Simonov, Andrei
openaire +2 more sources
Estimating credit and profit scoring of a Brazilian credit union with logistic regression and machine-learning techniques [PDF]
RAUSP Management Journal, 2019 Purpose – Although credit unions are nonprofit organizations, their objectives depend on the efficient management of their resources and credit risk aligned with the principles of the cooperative doctrine.
Daniel Abreu Vasconcellos de Paula +3 more
doaj +1 more source
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 +4 more sources
Making Deep Learning-Based Predictions for Credit Scoring Explainable
IEEE Access, 2021 Credit scoring has become an important risk management tool for money lending institutions. Over the years, statistical and classical machine learning models have been the most researched risk management tools in credit scoring literature, and recently ...
Xolani Dastile, Turgay Celik
doaj +1 more source
Hybrid credit scoring model using genetic algorithms and fuzzy expert systems Case study: Ghavvamin financial and credit institution [PDF]
Journal of Information Technology Management, 2014 expert systems can help to build banks customers' credit scoring models. Here, selection of key features of the credit scoring is important. Also, it is possible to express the features values as fuzzy. The problem is how to improve features selection by
MohammadTaghi Taghavifard +2 more
doaj +1 more source
Technological and Economic Development of Economy, 2020 Credit scoring is an important process for peer-to-peer (P2P) lending companies as it determines whether loan applicants are likely to default. The aim of most credit scoring models is to minimize the classification error rate, which implies that all ...
Feng Shen, Run Wang, Yu Shen
doaj +1 more source
Mathematics, 2022 A great challenge for credit-scoring models in online peer-to-peer (P2P) lending platforms is that credit-scoring models simply discard rejected applicants.
Dong-Her Shih +4 more
doaj +1 more source
A Deep Learning Based Online Credit Scoring Model for P2P Lending
IEEE Access, 2020 Credit scoring models have been widely used in traditional financial institutions for many years. Using these models in P2P Lending have limitations. First, the credit data of P2P usually contains dense numerical features and sparse categorical features.
Zaimei Zhang, Kun Niu, Yan Liu
doaj +1 more source