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Journal of Automation and Information Sciences

Publication de 12  numéros par an

ISSN Imprimer: 1064-2315

ISSN En ligne: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

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Modeling of Credit Risks on the Basis of the Theory of Survival

Volume 49, Numéro 11, 2017, pp. 11-24
DOI: 10.1615/JAutomatInfScien.v49.i11.30
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RÉSUMÉ

The basic principles of the theory of survival analysis are described, step by step the construction of models of assessment of the clients by the methods of logistic regression and survival analysis are shown. The following concepts as a function of risk, the Cox proportional risk model and the Kaplan–Meier statistics are introduced. Experimental studies have been carried out, that have shown the expediency of using the proposed models for solving the problems of behavioural scoring, since Cox's proportional risks allow one to include the variables depending on time in a set of regressors. Recommendations for improving the qualities of models are given, as well as the prospects for further application of proportional risk models for other types of financial risks, where it is also necessary to assess the whole group (population) in time, are described.

CITÉ PAR
  1. Kuznietsova Nataliia V., Bidyuk Petro I. , Identification of the Fraud Risk During Tender Purchaser by Survival Theory Methods, Upravlâûŝie sistemy i mašiny, 2(274), 2018. Crossref

  2. Doyle Casey, Herga Zala, Dipple Stephen, Szymanski Boleslaw K., Korniss Gyorgy, Mladenić Dunja, Predicting complex user behavior from CDR based social networks, Information Sciences, 500, 2019. Crossref

  3. Kuznietsova Nataliia, Bidyuk Petro, Heteroskedasticity Models for Financial Processes Modelling and Forecasting, 2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP), 2020. Crossref

  4. Bidyuk Petro, Kuznietsova Nataliia, Integrated Approach to Financial Data Analysis, Modeling and Forecasting, in System Analysis & Intelligent Computing, 1022, 2022. Crossref

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