CREDIT SCORING, STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE
Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & managementPublished 1 April 2011Open access
Hussein A. Abdou, John Pointon
Citations402
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TL;DR
There is no overall best statistical technique used in building scoring models and the best technique for all circumstances does not yet exist, but the applications of the scoring methodologies have been widely extended to include different areas and this subsequently can help decision makers, particularly in banking, to predict their clients' behaviour.
Abstract
SUMMARY Credit scoring has been regarded as a core appraisal tool of different institutions during the last few decades and has been widely investigated in different areas, such as finance and accounting. Different scoring techniques are being used in areas of classification and prediction, where statistical techniques have conventionally been used. Both sophisticated and traditional techniques, as well as performance evaluation criteria, are investigated in the literature. The principal aim of this paper, in general, is to carry out a comprehensive review of 214 articles/books/theses that involve credit scoring applications in various areas but in particular primarily in finance and banking. This paper also aims to investigate how credit scoring has developed in importance and to identify the key determinants in the construction of a scoring model, by means of a widespread review of different statistical techniques and performance evaluation criteria. Our review of literature revealed that there is no overall best statistical technique used in building scoring models and the best technique for all circumstances does not yet exist. Also, the applications of the scoring methodologies have been widely extended to include different areas, and this subsequently can help decision makers, particularly in banking, to predict their clients' behaviour. Finally, this paper also suggests a number of directions for future research. Copyright © 2011 John Wiley & Sons, Ltd.
Keywords
Computer ScienceEconomics, Econometrics and FinanceBusiness, Management and Accounting
Choice Reviews OnlineGenetic algorithms in search, optimization, and machine learning
49,278 Citations1989
This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Neural Networks: A Comprehensive Foundation
29,816 Citations1998Simon Haykin
Thorough, well-organized, and completely up to date, this book examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.
BiometricsClassification and Regression Trees.
23,841 Citations1984Alexander Gordon, Leo Breiman +3 more
Choice Reviews OnlineNeural networks for pattern recognition
18,687 Citations1994
This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition, and is designed as a text, with over 100 exercises, to benefit anyone involved in the fields of neural computation and pattern recognition.
Annals of EugenicsTHE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS
14,727 Citations1936Ronald Aylmer Fisher
Medical Entomology and ZoologyGenetic Programming: On the Programming of Computers by Means of Natural Selection
13,257 Citations1992John R. Koza
This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming.
Neural Networks for Pattern Recognition
12,198 Citations1995Chris Bishop
Journal of Business and Economic StatisticsAn Introduction to Multivariate Statistical Analysis
9,232 Citations1986Robb J. Muirhead, T. W. Anderson
Econometric Models and Economic Forecasts
5,027 Citations1990Robert S. Pindyck, Daniel L. Rubinfeld
Introduction to Econometrics
1,789 Citations2002James H. Stock, Mark W. Watson
Artificial Intelligence in MedicinePredicting breast cancer survivability: a comparison of three data mining methods
1,216 Citations2004Dursun Delen, Glenn Walker +1 more
The comparative study of multiple prediction models for breast cancer survivability using a large dataset along with a 10-fold cross-validation provided us with an insight into the relative prediction ability of different data mining methods.
Management ScienceManagerial Applications of Neural Networks: The Case of Bank Failure Predictions
1,124 Citations1992Kar Yan Tam, Melody Y. Kiang
Empirical results show that neural nets is a promising method of evaluating bank conditions in terms of predictive accuracy, adaptability, and robustness.
Journal of Banking & FinanceCorporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)
1,063 Citations1994Edward I. Altman, Giancarlo Marco +1 more
This study analyzes the comparison between traditional statistical methodologies for distress classification and prediction, i.e., linear discriminant (LDA) or logit analyses, with an artificial intelligence algorithm known as neural networks (NN), and suggests a combined approach for predictive reinforcement.
Computers & Operations ResearchNeural network credit scoring models
1,011 Citations2000David West
Results demonstrate that the multilayer perceptron may not be the most accurate neural network model, and that both the mixture-of-experts and radial basis function neural network models should be considered for credit scoring applications.
Journal of the Royal Statistical Society Series A (Statistics in Society)Statistical Classification Methods in Consumer Credit Scoring: A Review
1,005 Citations1997David J. Hand, William Henley
Credit scoring is the term used to describe formal statistical methods used for classifying applicants for credit into ‘good’ and ‘bad’ risk classes, and particular problems arising in the credit scoring context are examined.
Journal of the Operational Research SocietyBenchmarking state-of-the-art classification algorithms for credit scoring
882 Citations2003Bart Baesens, Tony Van Gestel +4 more
It is found that both the LS-SVM and neural network classifiers yield a very good performance, but also simple classifiers such as logistic regression and linear discriminant analysis perform very well for credit scoring.
Engineering GeologyLandslide susceptibility mapping: A comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey)
836 Citations2005Ertan Yeşilnacar, Tamer Topal
Logistic regression analysis and neural networks are applied to prepare landslide susceptibility map of the problematic segment of the pipeline in the Hendek region of Turkey and the result found by neural network is more realistic.
Expert Systems with ApplicationsCredit scoring with a data mining approach based on support vector machines
806 Citations2006Cheng-Lung Huang, Mu‐Chen Chen +1 more
Experimental results show that SVM is a promising addition to the existing data mining methods and achieves an identical classificatory accuracy with relatively few input features.
Expert Systems with ApplicationsNeural networks and statistical techniques: A review of applications
773 Citations2007Mukta Paliwal, Usha A. Kumar
A comprehensive review of articles that involve a comparative study of feed forward neural networks and statistical techniques used for prediction and classification problems in various areas of applications is carried out.
International Journal of ForecastingA survey of credit and behavioural scoring: forecasting financial risk of lending to consumers
735 Citations2000Lyn C. Thomas
IEEE Transactions on Neural NetworksBankruptcy prediction for credit risk using neural networks: A survey and new results
684 Citations2001Amir F. Atiya
Inspired by one of the traditional credit risk models developed by Merton (1974), it is shown that the use of novel indicators for the NN system provides a significant improvement in the (out-of-sample) prediction accuracy.
European Journal of Operational ResearchArtificial neural networks in bankruptcy prediction: General framework and cross-validation analysis
663 Citations1999Guoqiang Zhang, Michael Y. Hu +2 more
A comprehensive review of neural network applications in this area is given and the link between neural networks and traditional Bayesian classification theory is illustrated, indicating that neural networks are significantly better than logistic regression models in prediction as well as classification rate estimation.
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
651 Citations1999Russell Reed, Robert J. Marks
The Economic JournalApplied Statistical Decision Theory.
642 Citations1962A. D. Roy, H. Raiffa +1 more
TechnometricsConstruction and Assessment of Classification Rules
625 Citations1999Mark R. Wade, David J. Hand
Basic Ideas Introduction Constructing Rules Fisher's LDA and Other Methods Based on Covariance Matrices Recursive Partitioning Methods Nonparametric Smoothing Methods Practical Issues Some Special Problems Some Illustrative Applications.
Medical Entomology and ZoologyA Practical Guide to Neural Nets
604 Citations1991Marilyn McCord-Nelson, W.T. Illingworth
This book discusses how Neural Networks Relate to Other Technologies?
Decision SciencesNeural Networks: A New Tool for Predicting Thrift Failures*
534 Citations1992Linda Salchenberger, E. Mine Çinar +1 more
A neural network model that processes input data consisting of financial ratios is developed to predict the financial health of thrift institutions and its ability to discriminate between healthy and failed institutions is compared to a traditional statistical model.
European Journal of Operational ResearchA comparison of neural networks and linear scoring models in the credit union environment
517 Citations1996Vijay S. Desai, Jonathan Crook +1 more
The results indicate that customized neural networks offer a very promising avenue for building effective generic models if the measure of performance is percentage of bad loans correctly classified, but logistic regression models are comparable to the neural networks approach.
Expert Systems with ApplicationsUsing neural network ensembles for bankruptcy prediction and credit scoring
511 Citations2007Cheng‐Jung Tsai, Jyh‐Lin Wu
This paper investigates the performance of a single classifier as the baseline classifier to compare with multiple classifier and diversified multiple classifiers by using neural networks based on three datasets and suggests it is better to consider these three classifier architectures to make the optimal financial decision.
The MIT Press eBooksNeural Smithing
463 Citations1999Russell Reed, Robert J. Marks
This book presents an extensive and practical overview of almost every aspect of MLP methodology, progressing from an initial discussion of what MLPs are and how they might be used to an in-depth examination of technical factors affecting performance.
European Journal of Operational ResearchRecent developments in consumer credit risk assessment
452 Citations2007Jonathan Crook, David B. Edelman +1 more
Consumer credit risk assessment involves the use of risk assessment tools to manage a borrower’s account from the time of pre-screening a potential application through to the management of the account during its life and possible write-off.
Information & ManagementForecasting with neural networks
432 Citations1993Desmond Fletcher, Ernie Goss
A back-propagation neural network methodology has been applied to a sample of bankrupt and non-bankrupt firms and results indicate that this technique more accurately predicts bankruptcy than the logit model.
Journal of money credit and bankingThe Effect of Credit Scoring on Small-Business Lending
397 Citations2001W. Scott Frame, Aruna Srinivasan +1 more
Expert Systems with ApplicationsA two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines
395 Citations2005TL Lee, I-Fei Chen
The proposed hybrid approach outperforms the results using discriminant analysis, logistic regression, artificial neural networks and MARS and hence provides an alternative in handling credit scoring tasks.
TechnometricsRegression Analysis: Statistical Modeling of a Response Variable
395 Citations1999Henry W. Altland
This paper presents a meta-modelling procedure called Estimation Procedures, which automates the very labor-intensive and therefore time-heavy and expensive process of manually estimating the coefficients of linear regression in a discrete-time model.
Credit Risk Scorecards: Developing and Implementing Intelligent Credit Scoring
385 Citations2005Naeem Siddiqi
This chapter discusses Scorecard Development and Implementation Process, the People and the Process, and the people and the process, as well as data collection and construction, which led to the creation of the Scorecard.
International Journal of Machine Tools and ManufactureOn-line metal cutting tool condition monitoring.
377 Citations2000Eric Dimla, P.M. Lister
Expert Systems with ApplicationsCredit scoring using the hybrid neural discriminant technique
357 Citations2002Tian‐Shyug Lee, Chih‐Chou Chiu +2 more
The objective of the proposed study is to explore the performance of credit scoring by integrating the backpropagation neural networks with traditional discriminant analysis approach, and the proposed hybrid approach converges much faster than the conventional neural networks model.
Expert Systems with ApplicationsBuilding credit scoring models using genetic programming
357 Citations2005Choon Nam Ong, Jih‐Jeng Huang +1 more
In this paper, genetic programming (GP) is used to build credit scoring models and it is concluded that GP can provide better performance than other models.
Expert Systems with ApplicationsSupport vector machines for credit scoring and discovery of significant features
333 Citations2008Tony Bellotti, Jonathan Crook
Support vector machines are found to be competitive and can be used as the basis of a feature selection method to discover those features that are most significant in determining risk of default.
Computers & Operations ResearchNeural network ensemble strategies for financial decision applications
330 Citations2004David West, Scott Dellana +1 more
The generalization ability of the neural network ensemble is found to be superior to the single best model for three real world financial decision applications.
Expert Systems with ApplicationsReal-time credit card fraud detection using computational intelligence
327 Citations2007Jon T.S. Quah, M. Sriganesh
A new and innovative approach in understanding spending patterns to decipher potential fraud cases is presented and makes use of Self Organization Map to decipher, filter and analyze customer behavior for detection of fraud.
CERN Document Server (European Organization for Nuclear Research)Advanced algorithms for neural networks: a C++ sourcebook
315 Citations1995Timothy Masters
Deterministic Optimization Stochastic Optimization Hybrid Training Algorithms Probabilistic Neural Networks I: Introduction Probabilist Neural Networks II: Advanced Techniques Generalized Regression The Gram-Charlier Neural Network Dimension Reduction and Orthogonalization Assessing Generalization Ability Using the PNN Program.
Medical Entomology and ZoologyManaging Credit Risk:The Next Great Financial Challenge
313 Citations1998John B. Caouette, Edward I. Altman +1 more
Journal of EconometricsAn econometric analysis of the bank credit scoring problem
293 Citations1989William J. Boyes, Dennis L. Hoffman +1 more
Expert Systems with ApplicationsAn experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
289 Citations2008Loris Nanni, Alessandra Lumini
It is shown that the method ''Random Subspace'' outperforms the other ensemble methods tested in this paper, and the best stand-alone method is the multi-layer perceptron neural net, while the best method tested is the Random Subspace of Levenberg-Marquardt neural net.
Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real-World Performance
286 Citations1992Robert R. Trippi, Efraim Turban
Information and Software TechnologyComparison of artificial neural network and regression models for estimating software development effort
286 Citations2002Abbas Heiat
The results of the study indicate that when a combined third generation and fourth generation languages data set were used, the neural network produced improved performance over conventional regression analysis in terms of mean absolute percentage error.
Journal of the Royal Statistical Society Series D (The Statistician)A k-Nearest-Neighbour Classifier for Assessing Consumer Credit Risk
284 Citations1996William Henley, David J. Hand
An adjusted version of the Euclidean distance metric is proposed which attempts to incorporate knowledge of class separation contained in the data and the selection of optimal values of the parameters k and D included in the k-NN method is discussed.
Expert Systems with ApplicationsBankruptcy prediction using case-based reasoning, neural networks, and discriminant analysis
272 Citations1997Hongkyu Jo, Ingoo Han +1 more
Three different techniques are used: Multivariate discriminant analysis, case-based forecasting, and neural network to predict Korean bankrupt and nonbankrupt firms, with good results.
Emerging Markets ReviewAn emerging market credit scoring system for corporate bonds
245 Citations2005Edward I. Altman
Operations ResearchQuantitative Methods in Credit Management: A Survey
244 Citations1994Eric Rosenberg, Alan Gleit
The use of discriminant analysis, decision trees, and expert systems for static decisions, and dynamic programming, linear programming, and Markov chains for dynamic decision models are surveyed.
Expert Systems with ApplicationsAn integrated data mining and behavioral scoring model for analyzing bank customers
231 Citations2004Nan-Chen Hsieh
It is demonstrated that identifying customers by a behavioral scoring model is helpful characteristics of customer and facilitates marketing strategy development.
Journal of the Operational Research SocietyA Comparison of Discriminant Analysis versus Artificial Neural Networks
227 Citations1993Youngohc Yoon, George Swales +1 more
The purpose of this paper is to compare the ANN method with the Discriminant Analysis (DA) method in order to understand the merits of ANN that are responsible for the higher level of performance.
Expert Systems with ApplicationsCredit scoring and rejected instances reassigning through evolutionary computation techniques
226 Citations2003Mu‐Chen Chen, Shih-Hsien Huang
From the computational results, NNs have emerged as a computational tool that is well-matched to the problem of credit classification, and creditors can suggest the conditional acceptance, and further explain the conditions to rejected applicants.
European Journal of Operational ResearchGenetic programming and rough sets: A hybrid approach to bankruptcy classification
220 Citations2002Thomas E. McKee, Terje Lensberg
Findings indicate that genetic programming coupled with rough sets theory can be an efficient and effective hybrid modeling approach both for developing a robust bankruptcy prediction model and for offering additional theoretical insights.
The Engineering EconomistCOST ESTIMATION PREDICTIVE MODELING: REGRESSION VERSUS NEURAL NETWORK
218 Citations1997Alice E. Smith, Anthony K. Mason
Results show that neural networks have advantages when dealing with data that does not adhere to the generally chosen low order polynomial forms, or data for which there is little a priori knowledge of the appropriate CER to select for regression modeling.
Expert Systems with ApplicationsA comparison of supervised and unsupervised neural networks in predicting bankruptcy of Korean firms
216 Citations2005Ki Bong Lee, David Booth +1 more
The findings suggest that the BP network is a better choice when a target vector is available than the Kohonen self-organizing feature map in the area of bankruptcy prediction.
European Journal of Operational ResearchSubagging for credit scoring models
214 Citations2009Giuseppe Paleologo, André Elisseeff +1 more
A missing data imputation method is defined and an ensemble classification technique, subagging, is proposed, particularly suitable for highly unbalanced data, such as credit scoring data, to build and validate robust models, able to handle missing information, class unbalancedness and non-iid data points.
Decision Support SystemsPredicting and explaining patronage behavior toward web and traditional stores using neural networks: a comparative analysis with logistic regression
203 Citations2004Wei–yu Kevin Chiang, Dongsong Zhang +1 more
Neural network models are developed, which are known for their capability of modeling noncompensatory decision processes, to predict and explain consumer choice between web and traditional stores, and indicate that the influential factors are different across product categories.
Expert Systems with ApplicationsEffectiveness of neural network types for prediction of business failure
201 Citations1995J. Efrim Boritz, Duane B. Kennedy
The study examines the effectiveness of different neural networks in predicting bankruptcy filing and demonstrates that the performance of the neural networks tested is sensitive to the choice of variables selected and that the networks cannot be relied upon to “sift through” variables and focus on the most important variables.
European Journal of Operational ResearchAn intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring
197 Citations2007Lean Yu, Shouyang Wang +1 more
A novel intelligent-agent-based fuzzy group decision making (GDM) model is proposed as an effective multicriteria decision analysis (MCDA) tool for credit risk evaluation.
Journal of money credit and bankingA Credit Scoring Model for Commercial Loans
197 Citations1970Yair E. Orgler
The Credit Scoring Toolkit
194 Citations2007Raymond Anderson
Computers & Operations ResearchA model for portfolio selection with order of expected returns
184 Citations2000Yusen Xia, Baoding Liu +2 more
A new model for portfolio selection is proposed in which the expected returns of securities are considered as variables rather than as the arithmetic means of securities, to describe the return and risk of a portfolio more accurately.
European Journal of Operational ResearchBayesian kernel based classification for financial distress detection
177 Citations2005Tony Van Gestel, Bart Baesens +4 more
Expert Systems with ApplicationsNeural nets versus conventional techniques in credit scoring in Egyptian banking
168 Citations2007Hussein A. Abdou, John Pointon +1 more
Investigation of the ability of neural nets, such as probabilistic neural nets and multi-layer feed-forward nets, and conventional techniques, in evaluating credit risk in Egyptian banks applying credit scoring models revealed that the neural nets-models gave a better average correct classification rate than the other techniques.
Applied Mathematics and ComputationTwo-stage genetic programming (2SGP) for the credit scoring model
168 Citations2005Jih‐Jeng Huang, Gwo‐Hshiung Tzeng +1 more
Two-stage genetic programming (2SGP) is proposed to deal with the credit scoring problem by incorporating the advantages of the IF–THEN rules and the discriminant function and it is concluded that 2SGP can provide the better accuracy than other models.
European Journal of Operational ResearchBankruptcy theory development and classification via genetic programming
163 Citations2004Terje Lensberg, Aasmund Eilifsen +1 more
The genetic programming model relationships developed in this study support prior bankruptcy research, including the finding that company size decreases bankruptcy risk when profits are positive and that very high profit levels are associated with increased bankruptcy risk even for large companies an association that may be reflecting the potential for management to be “Cooking the Books”.
Socio-Economic Planning SciencesA credit scoring approach for the commercial banking sector
156 Citations2003Ahmet Burak Emel, Muhittin Oral +2 more
Decision SciencesThe Application of Neural Networks and a Qualitative Response Model to the Auditor's Going Concern Uncertainty Decision*
154 Citations1995Mary Jane Lenard, Pervaiz Alam +1 more
The generalized reduced gradient (GRG2) optimizer for neural network learning, a backpropagation neural network, and a logit model are used to predict which firms would receive audit reports reflecting a going concern uncertainty modification.
Journal of Banking & FinanceMultiple banking relationships and the fragility of corporate borrowers
154 Citations1998Antonella Foglia, Sebastiano Laviola +1 more
Computers & Operations ResearchA threshold-varying artificial neural network approach for classification and its application to bankruptcy prediction problem
150 Citations2004Parag C. Pendharkar
It is illustrated that the proposed TV-ANN fares well, both for training and holdout samples, when compared to the traditional backpropagation artificial neural network (ANN) and the statistical linear discriminant analysis.
IMA Journal of Management MathematicsCredit-scoring models in the credit-union environment using neural networks and genetic algorithms
149 Citations1997Vijay S. Desai
Insurance Mathematics and EconomicsA credit scoring model for personal loans
148 Citations1989A. Steenackers, Marc Goovaerts
NeurocomputingNeural network prediction analysis: The bankruptcy case
146 Citations1996Moshe Leshno, Yishay Spector
The prediction capability of various neural network models is improved by using enhanced learning techniques, but if the enhancement learning technique is too ‘strong’, the model becomes too specific for the training data set and thus loses its prediction capabilities.
Economics LettersInflation forecasting using a neural network
146 Citations2004Emi Nakamura
In a pseudo-out-of-sample forecasting experiment using recent U.S. data, neural networks outperform univariate autoregressive models on average for short horizons of one and two quarters.
Journal of the Operational Research SocietyNeural network survival analysis for personal loan data
144 Citations2005Bart Baesens, Tony Van Gestel +3 more
Journal of the American Statistical AssociationThe Development of Numerical Credit Evaluation Systems
141 Citations1963James H. Myers, Edward W. Forgy
Journal of Banking & FinanceEconomic benefit of powerful credit scoring
138 Citations2005Andreas Blöchlinger, Markus Leippold
Institution of Engineering and Technology eBooksNeural Network Applications in Control
137 Citations1995
This book discusses the development of dynamic artificial neural networks in state estimation and nonlinear process control, and the construction of nonlinear dynamical processes in these applications.
Introduction to Banking
136 Citations2006Barbara Casu, Claudia Girardone +1 more
International Journal of Bank MarketingBank lending and the environment: policies and opportunities
133 Citations1998Paul M. Thompson
International Review of Financial AnalysisA credit scoring model for Vietnam's retail banking market
132 Citations2007Thi Huyen Thanh Dinh, Stefanie Kleimeier
Journal of the Operational Research SocietySample selection bias in credit scoring models
129 Citations2003John Banasik, Jonathan Crook +1 more
The lower the risk band of the training sample, the less accurate the predictions for all applicants, and the greater the overestimate of the true performance of the model when tested on a sample of applicants within the same risk band — as a financial institution would do.
Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & managementModelling small‐business credit scoring by using logistic regression, neural networks and decision trees
127 Citations2005Mirta Benšić, Nataša Šarlija +1 more
The main purpose of this paper is to extract important features for credit scoring in small-business lending on a dataset with specific transitional economic conditions using a relatively small dataset, and to compare the accuracy of the best models extracted by different methodologies, such as logistic regression, neural networks, and CART decision trees.
Expert Systems with ApplicationsConsumer credit scoring models with limited data
127 Citations2008Maja Šušteršič, Dušan Mramor +1 more
Journal of Banking & FinanceDeregulation, technological change, and the business-lending performance of large and small banks
124 Citations2005David A. Carter, James E. McNulty
International Journal of ForecastingComparing the predictive performance of a neural network model with some traditional market response models
124 Citations1994Chanda Ghose Dasgupta, Gary S. Dispensa +1 more
This study believes that its study is one of the first applications of neural network models using individual level cross-sectional survey data for predicting market response and that its findings have opened the doors to further research about the applicability of Neural Network Modeling using Individual levelCross-sectional data, as opposed to using aggregate company level data.
Expert Systems with ApplicationsA practical approach to credit scoring
123 Citations2007Jae H. Min, Young‐Chan Lee
This paper proposes a DEA-based approach to credit scoring that solely requires ex-post information to calculate credit scores and proposes a practical credit rating method using the predicted DEA scores.
Expert Systems with ApplicationsGenetic programming for credit scoring: The case of Egyptian public sector banks
122 Citations2009Hussein A. Abdou
This paper investigates the ability of GP, which was proposed as an extension of genetic algorithms and was inspired by the Darwinian evolution theory, in the analysis of credit scoring models in Egyptian public sector banks and compares it with probit analysis (PA), a successful alternative to logistic regression and weight of evidence (WOE) measure.
Journal of Urban EconomicsJuvenile delinquent mortgages: Bad credit or bad economy?
118 Citations2008Andrew F. Haughwout, Richard Peach +1 more
Journal of Marketing ResearchArtificial Neural Network Decision Support Systems for New Product Development Project Selection
116 Citations2000R. Jeffrey Thieme, Michael Song +1 more
The authors extend and develop an artificial neural network decision support system and demonstrate how it can guide managers when they make complex new product development decisions.
Expert Systems with ApplicationsA binary classification method for bankruptcy prediction
115 Citations2008Jae H. Min, Chulwoo Jeong
It is shown that the binary classification method proposed in this paper can serve as a promising alternative to the existing methods for bankruptcy prediction.
Japan and the World EconomySample selection in credit-scoring models
113 Citations1998William H. Greene
…