Application of data mining methods to solving the problems of actuarial modeling and estimation of financial risks

Authors

  • S. V. Dubinina The Institute for Applied System Analysis at the Igor Sikorsky Kyiv Polytechnic Institute, Kyiv
  • Petro I. Bidyuk The Institute for Applied System Analysis at the Igor Sikorsky Kyiv Polytechnic Institute, Kyiv http://orcid.org/0000-0002-7421-3565

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2017.1.04

Keywords:

actuarial processes, insurance risks, generalized linear models, Bayesian approach, data mining, group method for data handling, fuzzy GMDH

Abstract

Results of application of the data mining to solving the problem of actuarial processes modeling and risk estimation for insurance companies are presented. As a mathematical modeling tool the following approaches were used: generalized linear models, Bayesian networks, the group method for data handling, fuzzy GMDH, and Bayesian parameter estimation techniques. Using actual statistical data from the insurance industry, new generalized linear models were constructed that were used for estimation of a possible loss by an insurance company. Also, a model in the form of a Bayesian network was constructed that was applied to estimate the bankruptcy risk in a case of insurance losses. The best model constructed in this case turned out to be the gamma distribution based model and logarithmic link function whose parameters were estimated within four iterations of the estimation algorithm. A substantial computed value of the insurance company bankruptcy risk reflects the fact that the company under consideration does not possess an effective mechanism for managing its own capital and the payments from clients. Thus, an application of data mining is an effective approach to solving the problems of short-term forecasting financial processes and estimation of actuarial risks.

Author Biographies

S. V. Dubinina, The Institute for Applied System Analysis at the Igor Sikorsky Kyiv Polytechnic Institute, Kyiv

Svitlana Dubinina,

a Ph.D. student at the Institute for Applied System Analysis at the Igor Sikorsky Kyiv Polytechnic Institute.

 

Petro I. Bidyuk, The Institute for Applied System Analysis at the Igor Sikorsky Kyiv Polytechnic Institute, Kyiv

Bidyuk Petro,

Doctor of Engineering Sci, professor at the Institute for Applied System  Analysis NTUU "KPI". Graduated from the Kyiv Polytechnic Institute in 1972. He got his PhD (Candidate of Sciences) degree in Control Engineering in 1986, and Doctor of Engineering Sci.  in 1996.

Current areas of interest: Time Series Analysis, Forecasting and Control, Bayesian  Data Analysis, and Decision Support Systems (design and implementation).

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Published

2017-03-21

Issue

Section

Decision making and control in economic, technical, ecological and social systems