Results 21 to 30 of about 32,796 (305)
The Fairness of Credit Scoring Models
Management Science, 2021 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
openaire +2 more sources
Credit Risk Assessment Model Based Using Principal component Analysis And Artificial Neural Network
MATEC Web of Conferences, 2016 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.
doaj +1 more source
Time will tell: behavioural scoring and the dynamics of consumer credit assessment [PDF]
, 2001 This paper discusses the use of dynamic modelling in consumer credit risk assessment. It surveys the approaches and objectives of behavioural scoring, customer scoring and profit scoring.
Scherer, W.T. +6 more
core +1 more source
tripleC: Communication, Capitalism & Critique, 2010 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
doaj +1 more source
Predicting Credit Scores with Boosted Decision Trees
Forecasting, 2022 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
doaj +1 more source
A Soft Intelligent Risk Evaluation Model for Credit Scoring Classification
International Journal of Financial Studies, 2015 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
doaj +1 more source
Remarks on Statistical Measures for Assessing Quality of Scoring Models
Acta Universitatis Lodziensis. Folia Oeconomica, 2019 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
doaj +1 more source
Internet Financial Credit Scoring Models Based on Deep Forest and Resampling Methods
IEEE Access, 2023 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
doaj +1 more source
Credit Scoring and Loan Default [PDF]
International Review of Finance, 2011 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
openaire +2 more sources
An optimised credit scorecard to enhance cut-off score determination
South African Journal of Economic and Management Sciences, 2018 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
doaj +1 more source