Are we modelling the right thing? The impact of incorrect problem specification in credit scoring

Finlay, Steven

doi:10.1016/j.eswa.2008.12.016

Cited by 21 publications

(12 citation statements)

References 14 publications

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“…Computational approaches facilitating feature selection have been widely used to address this challenge, usually through metaheuristics (Marqu es, Garc ıa, & S anchez, 2013; Serrano-Silva, Villuendas-Rey, & Y añez-M arquez, 2018). Similar algorithms have also been used to optimize the parameters of fitting algorithms or to enable the consideration of complex performance measures (Finlay, 2009;Kozeny, 2015;Li, Wei, Li, & Xu, 2011;Martens et al, 2010;Zhang, Dai, & Ma, 2015; Zong-Chang, Hong, Ji-sheng, & Hong, 2015), as well as for calibrating credit ratings (Lyra, Paha, Paterlini, & Winker, 2010).…”

Section: Study Methodology Assetmentioning

confidence: 99%

Computational approaches and data analytics in financial services: A literature review

Andriosopoulos

Doumpos

Pardalos

et al. 2019

Journal of the Operational Research Society

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The level of modeling sophistication in financial services has increased considerably over the years. Nowadays, the complexity of financial problems and the vast amount of data require an engineering approach based on analytical modeling tools for planning, decision making, reporting, and supervisory control. This article provides an overview of the main financial applications of computational and data analytics approaches, focusing on the coverage of the recent developments and trends. The overview covers different methodological tools and their uses in areas, such as portfolio management, credit analysis, banking, and insurance.

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Section: Study Methodology Assetmentioning

confidence: 99%

Computational approaches and data analytics in financial services: A literature review

Andriosopoulos

Doumpos

Pardalos

et al. 2019

Journal of the Operational Research Society

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“…Uspokojivé výsledky dosiahla takisto štúdia Finlay (2009), ktorý porovnal výkonnosť logit modelu a klasického regresného lineárneho modelu s GA modelom. Gordini (2014)…”

Section: Prehľad Literatúry a Predikčných Modelov úPadkuunclassified

Applicability of Scoring Models in Firms' Default Prediction. The Case of Slovakia

Mihalovič¹

2018

Politicka ekonomie

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Applicability of Scoring Models in Firms' Default Prediction. The Case of Slovakia Bankruptcy prediction has long been regarded as a critical topic within the academic and banking community. To the best of our knowledge, no previous study in the Slovak Republic has attempted to develop a bankruptcy prediction model putting together statistical and artificial intelligence approaches performed on a such an amount of data. This paper seeks to fill this gap. Our aim is to develop a hybrid bankruptcy prediction model using a genetic algorithm in the process of training a neural network (GA-NN). The research data set comprises a balanced sample of both healthy and bankrupt firms operating in Slovakia in the period from 2014 to 2017. Financial information regarding a firm's financial situation are acquired from the Finstat database, which stores annual reports. For the purpose of comparing the classification accuracy of the proposed GA-NN model, two more models are constructed, namely BP-NN (back-propagation neural network model) as well as MDA (multiple discrimination model). The results gained by utilizing these models suggest the superiority of the developed GA-NN model to both BP-NN and MDA models in terms of prediction performance.

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“…There are also other works that have used data gathered from different sources, such as a bankruptcy data set from a Benelux financial institution (Martens et al, 2007), a data set provided by a subsidiary of the Construction Bank of China (Zhou and Bai, 2008), a loan portfolio of the Commercial Bank of Greece (Marinakis et al, 2008), personal loan data sets from banks in Egypt (Abdou, 2009), data supplied by Experian UK (Finlay, 2006(Finlay, , 2009, a consumer loan database from Jordanian banks (Eletter et al, 2010), data from a US commercial bank (Li et al, 2012), or a credit data set provided by a Croatian bank (Oreski et al, 2012). These papers mainly focus on a single database, converting their models into ad-hoc solutions that can become hard to use under other different conditions.…”

Section: Credit Databasesmentioning

confidence: 99%

“…The new technique produces an approximation to the set of Pareto-optimal solutions, which may increase the decision flexibility available to the bank manager, and is also computationally efficient when compared with the traditional multi-objective method of epsilon-constraints. Finlay (2006Finlay ( , 2009 introduces an evolutionary approach to the implementation of credit scoring models, demonstrating that genetic algorithms can perform as well as, if not marginally better than, competing models constructed using neural networks, OLS regression, and logistic regression. For the experiments, data are supplied by Experian UK and contain details of credit applications made in a time period.…”

Section: Classificationmentioning

confidence: 99%

A literature review on the application of evolutionary computing to credit scoring

Marqués

García

Sánchez

2013

Journal of the Operational Research Society

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The last years have seen the development of many credit scoring models for assessing the creditworthiness of loan applicants. Traditional credit scoring methodology has involved the use of statistical and mathematical programming techniques such as discriminant analysis, linear and logistic regression, linear and quadratic programming, or decision trees. However, the importance of credit grant decisions for financial institutions has caused growing interest in using a variety of computational intelligence techniques. This paper concentrates on evolutionary computing, which is viewed as one of the most promising paradigms of computational intelligence. Taking into account the synergistic relationship between the communities of Economics and Computer Science, the aim of this paper is to summarize the most recent developments in the application of evolutionary algorithms to credit scoring by means of a thorough review of scientific articles published during the period 2000-2012.

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Are we modelling the right thing? The impact of incorrect problem specification in credit scoring

Cited by 21 publications

References 14 publications

Computational approaches and data analytics in financial services: A literature review

Computational approaches and data analytics in financial services: A literature review

Applicability of Scoring Models in Firms' Default Prediction. The Case of Slovakia

A literature review on the application of evolutionary computing to credit scoring

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