Results 11 to 20 of about 32,796 (305)
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
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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
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A Quantitative Theory of the Credit Score [PDF]
SSRN Electronic Journal, 2020 What is the role of credit scores in credit markets? We argue that it is, in part, the market's assessment of a person's unobservable type, which here we take to be patience. We postulate a model of persistent hidden types where observable actions shape the public assessment of a person's type via Bayesian updating.
Chatterjee, Satyajit +3 more
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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
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Would credit scoring work for Islamic finance? A neural network approach [PDF]
, 2014 Purpose – The main aim of this paper is to distinguish whether the decision making process of the Islamic financial houses in the UK can be improved through the use of credit scoring modeling techniques as opposed to the currently used judgmental ...
Mulkeen, James +8 more
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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
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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
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A practical approach to credit scoring
Expert Systems with Applications, 2008 This paper proposes a DEA-based approach to credit scoring. Compared with conventional models such as multiple discriminant analysis, logistic regression analysis, and neural networks for business failure prediction, which require extra a priori information, this new approach solely requires ex-post information to calculate credit scores.
Jae H. Min, Young-Chan Lee
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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
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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
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