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
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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
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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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NATE: Non-pArameTric approach for Explainable credit scoring on imbalanced class. [PDF]
PLoS ONECredit scoring models play a crucial role for financial institutions in evaluating borrower risk and sustaining profitability. Logistic regression is widely used in credit scoring due to its robustness, interpretability, and computational efficiency ...
Seongil Han, Haemin Jung
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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.
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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
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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
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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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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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