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Trends and Forecasts Analysis of Insurance Industry in Russia |
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| รหัสดีโอไอ | |
| Creator | Alfira Kumratova, Elena Popova, Elena Khudyakova, Igor Vasilenko, Natalya Orlyanskaya |
| Title | Trends and Forecasts Analysis of Insurance Industry in Russia |
| Contributor | - |
| Publisher | TuEngr Group |
| Publication Year | 2564 |
| Journal Title | International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies |
| Journal Vol. | 12 |
| Journal No. | 11 |
| Page no. | 12A11R: 1-8 |
| Keyword | Time series, Predictive models, Life insurance, Quasi-cycles length, Memory depth, Insurance business. |
| URL Website | http://TuEngr.com/Vol12-11.html |
| Website title | ITJEMAST V12(11) 2021 @ TuEngr.com |
| ISSN | 2228-9860 |
| Abstract | The 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. |
