Gajović, dr Vladimir
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Vladimir M. Gajović was born on September 29, 1962 in Smederevo. He acquired
his primary and secondary education in Belgrade. In 1990, he graduated from the Faculty
of Transport and Traffic Engineering, University of Belgrade, in Integrated and Industrial
Transport. He has been employed in Dunav Insurance Company a. d. o. since 1992.
He completed specialist postgraduate studies at the Actuarial Department of the Faculty of Economics, University of Belgrade in 1996, and master's studies at the same Department of the Faculty of Economics in 2000. In 2015, at the Faculty of Transport and Traffic Engineering, University of Belgrade, he defended his doctoral dissertation entitled Risk Modeling in Logistic Processes and Application in Transportation Insurance.
In his professional career he has worked as a risk analyst, head of Cargo Insurance Service, actuary for transport and credit insurance lines, underwriting supervisor, and a director of the Main Transport and Credit Insurance Office, a position he still holds.
He has attended numerous scientific and professional conferences in the field of insurance, risk theory, transport and logistics home and abroad. He has participated in the education of numerous colleagues and students in the field of transport insurance.
From 2010 to 2013 he was a Company representative in an international organization representing the interests of insurance companies and shipowners in inland water transport IVR (International Association for the representation of mutual interests of inland shipping and the insurance and for keeping the register of inland vessels in Europe).
He has attended numerous international courses in the field of cargo insurance, and vessel and aircraft insurance.
He has published a number of scientific papers presented at international and domestic conferences, domestic and international monographs, and scientific journals in the field of risk theory, logistics and insurance, three of which are included in the list of SCI journals (Journal of Risk Research; Simulation: Transactions of the Society for Modeling and Simulation International and Mathematical Problems in Engineering).
He is one of the founders of the Serbian Association of Actuaries.
He speaks English.
ADJUSTMENT OF MORTALITY TABLES BY LIMITED FLUCTUATION METHOD
Credibility theory provides tools to deal with the randomness of data that is used for predicting future events. The credibility procedure is used to improve the statistical signifi cance of parameter estimates in a given task. Because it has been used since the very beginnings of actuarial practice, it is one of the most productive actuarial techniques, and is still being developed and adapted to solve contemporary problems. In this paper, the credibility procedure will be used to modify the standard population mortality table, more specifi cally the Serbian mortality table for females (Mortality Tables of the Republic Statistical Offi ce 2010-2012), to refl ect the experience with a particular subset of population and thus establish a more reliable estimate of mortality by including into analysis the experiential data and subgroups. Key words: mortality tables, mortality rates, credibility
APPLYING FUZZY MATHEMATICS TO RISK ASSESSMENT IN INSURANCE INDUSTRY
As system structures are complex, and non-linearity, uncertainty, coincidence,
variability, etc. occur, most dynamic systems are extremely difficult to model according
to accurate and precise mathematical relations. Fuzzy mathematics (fuzzy logic, theory of
fuzzy sets, etc.) can provide an appropriate alternative to exact mathematical modelling
of systems or processes that are largely vague or too complex to be described by simple
and clear mathematical formulas. Methods of the fuzzy system have been widely used
in risk assessment and other segments of the theory and practice of insurance, such
as classification, underwriting, projected liabilities, future and present value, pricing,
asset allocation, cash flows, investments, and more. This paper gives an overview of the
research and the possibility to apply fuzzy mathematics in insurance industry.
Key words: risk, fuzzy mathematics, insurance, actuarial, underwriting