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Determinants of Motor Third Party Liability insurance in North Macedonia
(2022-09)
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This paper emphasizes the importance of the motor third party liability (MTPL) insurance in the Republic of North Macedonia as the dominant class in the Macedonian insurance sector. Even though underdeveloped, the Macedonian insurance market holds great potential, but obstacles such as low financial literacy, insurance culture among economic agents, and general problems in adequate risk valuation weaken serious growth. Additionally, it is confirmed in various cases that the economic development is a significant determinant of insurance market development (Ward and Zurbruegg, 2000; Skalská, 2018). The purpose of insurance is to protect risk averse individuals from suffering the full consequences of actions that affect them adversely (Spence and Zeckhauser, 1971), with insurance companies acting as risk underwriters. With the rising population, complex urban traffic and technological progress, a need for compulsory insurance of motor third-party liability emerged. Till date, a bonus-malus tariff system is employed in the case of the Macedonian insurance sector. Since the general concept is risk valuation and pooling, a meaningful approach is premium differentiation between insurers which reflects risk heterogeneity (Henckaerts et al., 2018). A liberalized formation of MTPL prices is announced in North Macedonia, but a significant challenge may be the inadequate and scarce data (Tomeski, 2012). As claims become more common, the insurance market steadily focuses on other classes such as property and voluntary health insurance but nothing significant enough to substantially change the business environment. Through the analysis of the determinants of MTPL insurance premium, we ought to find the underlying relationships between a set of variables which should help policy creators and insurance companies in formulating future business decisions. Using a simultaneous inductive and deductive techniques, we conduct the study entirely on quantitative basis. The research distances from the pure macroeconomic determinants previously treated in studies of non-life insurance demand (Poposki, Kjosevski and Stojanovski, 2015) and insurance expenditures (Trinh, Nguyen and Sgro, 2016). On contrary, we ought to depict the underlying microeconomic relationships which are idiosyncratic i.e., specific for each insurance company and the built-in consumer tendencies. Worth noting that consumer behavior can also be studied in a different manner such as through their transition between companies, as Blazheska and Ivanovski show (2021). By discussing a specific class of compulsory insurance – the MTPL, we empirically contextualize the most important class of insurance in a developing Western Balkan economy. The main research hypothesis is that MTPL gross written premium dynamics can be significantly determined by the number of contracts, gross claims liquidated, market share and share of MTPL insurance in total gross written premium (GWP).
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Is the Claims Ratio Dynamic Predictable? A Study of the Macedonian Non-Life Insurance Sector
(Faculty of Economics-Skopje, Ss. Cyril and Methodius University in Skopje, 2023-12-15)
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Insurance, simplified to a risk management concept, offers protection against unexpected losses arising from adverse events. As a financial service of structural importance in modern economies, it requires specific attention due to its risk protection component. Consequently, insurance companies devote sufficient resources towards stable, resilient, and profitable operations. However, a scarce amount of research treats the topic of financial stability maintenance and claims management with even fewer studies dealing with its prediction. This study deals with claims ratio (CR) dynamics in the Macedonian non-life insurance sector and its prediction. Utilizing a data set of 138 monthly observations between January 2012 and June 2023, this paper models the CR indicator through multiple approaches i.e., naïve, ARIMA, ETS exponential smoothing, and random forest (RF) thus making suitability and accuracy comparisons. Results suggest that the SARIMA(4,0,2)(2,1,2,12) model is superior in predicting the claims ratio in both the training and test samples. Moreover, the random forest algorithm shows good performances in the test set but is only superior to the ETS(A,N,A) model.
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PREDICTING NON-LIFE INSURANCE SEGMENTS IN THE REPUBLIC OF NORTH MACEDONIA: A COMPARATIVE MULTI-MODELLING PERSPECTIVE
(EERIA Second Annual Conference, 2023-09)
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Insurance prediction emerges as one of the fundamentals in business sustainability and rising market competitiveness, as current decisions depend on future expectations. As the available data exponentially grows, insurers face the most important decision - either focus on significant data analytics or simply lose ground to competitors which do so. This paper aims at predicting future developments in non-life gross written premiums, claims, number of contracts and technical premiums as the pure quantity of the underwritten risk in the Macedonian insurance sector. Through a multi-model univariate approach, the paper aims at uncovering forecasting capabilities of different models, which in turn can be used by the insurers to form expectations more adequately.

Faculty of Economics

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