Sheptura A. Models and methods of decision-making automation in insurance company principal activity management

Research object - process of insurance company basic activity. Purpose of research - the increase of insurance company basic activity efficiency due to automation of planning processes and operative management. Research methods: system analysis, theory of sets; theory of differential equalizations; numeral methods, simulation techniques; methods of optimization; probability theory and mathematical statistics. An analytical model is first developed for the automated planning and prognosis of insurance company income as a system of coherent nonlinear stochastic differential equalizations, which, unlike existent models, describes connection between different basic insurance performance indicators taking into account the tariff policy of competitive companies and features of work of insurance agents. The methods of decision making are improved at a long-term management an insurance company, which differ from existing the account of planning and operative management functional tasks dynamics. It allowed toincrease the income of company due to an optimum insurance portfolio construction and recommended the insurer of possible decisions in case of unplanned situations occurring. Simulation, which consists in tom, that is taken into account casual character of initial conditions of task Koshi and influencing of casual processes on functional connections of insurance process descriptions, techniques got further development, that allowed to expect the complex of difficult statistical moments for the band of control system decisions realization, determining economic efficiency of insurance activity due to the increase of prognosis exactness. Level of introduction of results - applied-research. Purview: insurance companies.