:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies
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FEATURE PEER-REVIEWED ARTICLE
Vol.12(11) (2021) |
Trends and Forecasts Analysis of Insurance Industry in Russia
Alfira Kumratova, Elena Popova (Department of Information Systems, Kuban State Agrarian University named after I.T. Trubilin, Krasnodar, RUSSIA),
Elena Khudyakova (Department of Applied Informatics, Russian State Agrarian University Moscow Agricultural Academy named after K. A. Timiryazev, Moscow, RUSSIA),
Igor Vasilenko (Department of Computer Technologies and Systems, Kuban State Agrarian University named after I.T. Trubilin, Krasnodar, RUSSIA),
Natalya Orlyanskaya (Department of Information Systems and Programming, Kuban State Technological University , Krasnodar, RUSSIA).
Disciplinary: Computer technologies, Information Systems.
doi: 10.14456/ITJEMAST.2021.228
Keywords: Time series; Predictive models; Life insurance; Quasi-cycles length; Memory depth; Insurance business.
AbstractThe best solution is the complex use of analysis and forecast for making management decisions in the insurance business. The basis of any insurance activity is the presence, first of all, of a client interested in purchasing an insurance product. Therefore, the number of insured clients is the primary indicator of the effectiveness of the insurance company. Preparing data for analysis and then using this data as input data for predictive models is a separate preparatory stage of the study. In work, had prepared the basic time series (TS): TS data of men and women daily insured, separate daily TS by gender, and aggregated weekly TS, as well as their increments. Using the research theory of time series shows that a specific ordering of data in time makes it possible to determine or predict the subsequent value of these TS.Paper ID: 12A11R
Cite this article:
Kumratova, A., Popova, E., Khudyakova, E., Vasilenko, I., and Orlyanskaya, N. (2021). Trends and Forecasts Analysis of Insurance Industry in Russia. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 12(11), 12A11R, 1-8. http://doi.org/10.14456/ITJEMAST.2021.228
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