Results 21 to 30 of about 27,113 (158)
The Fairness of Credit Scoring Models
In credit markets, screening algorithms aim to discriminate between good-type and bad-type borrowers. However, when doing so, they can also discriminate between individuals sharing a protected attribute (e.g., gender, age, racial origin) and the rest of the population. This can be unintentional and originate from the training data set or from the model
Hurlin, Christophe +2 more
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Credit Risk Assessment Model Based Using Principal component Analysis And Artificial Neural Network
Credit risk assessment for bank customers has gained increasing attention in recent years. Several models for credit scoring have been proposed in the literature for this purpose.
Hamdy Abeer, Hussein Walid B.
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The system of credit scoring has been built up in recent times on the basis of a compromise struck between individuality and surveillance in ways that boosted consumption through consumer debt.
Thomas Fay Ruddy
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Remarks on Statistical Measures for Assessing Quality of Scoring Models
Granting a credit product has always been at the heart of banking. Simultaneously, banks are obligated to assess the borrower’s credit risk. Apart from creditworthiness, to grant a credit product, banks are using credit scoring more and more often ...
Adam Piotr Idczak
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Predicting Credit Scores with Boosted Decision Trees
Credit scoring models help lenders decide whether to grant or reject credit to applicants. This paper proposes a credit scoring model based on boosted decision trees, a powerful learning technique that aggregates several decision trees to form a ...
João A. Bastos
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A Soft Intelligent Risk Evaluation Model for Credit Scoring Classification
Risk management is one of the most important branches of business and finance. Classification models are the most popular and widely used analytical group of data mining approaches that can greatly help financial decision makers and managers to tackle ...
Mehdi Khashei, Akram Mirahmadi
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Internet Financial Credit Scoring Models Based on Deep Forest and Resampling Methods
In recent years, deep learning credit scoring models have become a hot research topic in Internet finance. However, most of the existing studies are based on deep neural network models, whose structure is difficult to design.
Yu Zhong, Huiling Wang
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An optimised credit scorecard to enhance cut-off score determination
Background: Credit scoring is a statistical tool allowing banks to distinguish between good and bad clients. However, literature in the world of credit scoring is limited. In this article parametric and non-parametric statistical techniques that are used
Nico Kritzinger, Gary W. van Vuuren
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Credit Card Fraud Detection Using LSTM Algorithm
With the rapid growth of consumer credit and the huge amount of financial data developing effective credit scoring models is very crucial. Researchers have developed complex credit scoring models using statistical and artificial intelligence (AI ...
Yanash Azwin Mohmad
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Credit Scoring and Loan Default [PDF]
AbstractA metric of credit score performance is developed to study the usage and performance of credit scoring in the loan origination process. We examine the performance of originationFICOscores as measures ofex anteborrower creditworthiness using loan‐level data onex postperformance of subprime mortgages.
Sengupta, Rajdeep, Bhardwaj, Geetesh
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