Journal ArticleDOI
A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers
TLDR
In this paper, the authors survey the techniques used to support credit scoring and behavioural scoring and discuss the need to incorporate economic conditions into the scoring systems and the way the systems could change from estimating the probability of a consumer defaulting to estimating the profit a consumer will bring to the lending organisation.About:
This article is published in International Journal of Forecasting.The article was published on 2000-04-01. It has received 770 citations till now. The article focuses on the topics: Credit history & Financial risk.read more
Citations
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Journal ArticleDOI
Benchmarking state-of-the-art classification algorithms for credit scoring
TL;DR: 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.
Journal ArticleDOI
Credit scoring with a data mining approach based on support vector machines
TL;DR: Experimental results show that SVM is a promising addition to the existing data mining methods and three strategies to construct the hybrid SVM-based credit scoring models are used.
Journal ArticleDOI
The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients
I-Cheng Yeh,Che-hui Lien +1 more
TL;DR: Among the six data mining techniques, artificial neural network is the only one that can accurately estimate the real probability of default, and its regression intercept is close to zero, and regression coefficient to one.
Journal ArticleDOI
Classifier Technology and the Illusion of Progress
TL;DR: This paper argues that simple methods typically yield performance almost as good as more sophisticated methods, to the extent that the di!erence in performance may be swamped by other sources of uncertainty that generally are not considered in the classical supervised classification paradigm.
Journal ArticleDOI
Classifier Technology and the Illusion of Progress
TL;DR: The authors argued that simple methods typically yield performance almost as good as more sophisticated methods, to the extent that the difference in performance may be swamped by other sources of uncertainty that generally are not considered in the classical supervised classification paradigm.
References
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Journal ArticleDOI
The Pricing of Options and Corporate Liabilities
Fischer Black,Myron S. Scholes +1 more
TL;DR: In this paper, a theoretical valuation formula for options is derived, based on the assumption that options are correctly priced in the market and it should not be possible to make sure profits by creating portfolios of long and short positions in options and their underlying stocks.
Journal ArticleDOI
Classification and Regression Trees.
Book
C4.5: Programs for Machine Learning
TL;DR: A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
Book
Classification and regression trees
TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.