The analysis of insurance market structure and dynamics in Ukraine, Russia and European Insurance and Reinsurance Federation (ɋȿȺ) member states

Kozmenko, Olga; Merenkova, Olha; Boyko, Anton

doi:10.21511/ppm.7(1).2009.01

Cited by 11 publications

(7 citation statements)

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“…A different set of determinants defines each sphere. This approach has found a practical application for the insurance and reinsurance market in the work of Kozmenko et al (2009), where a model of their stability based on a triangle was developed. A general approach without practical implementation was proposed to analyze the business activity of companies in the article of Berzin et al (2018).…”

Section: Methodsmentioning

confidence: 99%

Country’s health profile: Social, economic, behavioral and healthcare determinants

Lyeonov¹,

Bilan²,

Yarovenko³

et al. 2021

Economics &Amp; Sociology

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The article uses the estimation method of the center of mass to model the country's health profile as an indicator for determining the prerequisites for the country's readiness to combat and prevent mass diseases. The authors identified the most relevant determinants that characterized society's social, economic, healthcare, and behavioral models. They formed a sequence of health profiles in the form of a four-pole barycentric model of balanced, composite dimensions. It was found that developed countries dominate according to the integrated value of the four dimensions. It indicates their significant economic, social, and medical opportunities for the population. According to the balance of dimension pairs, behavioral determinants influence the imbalance for developed countries, the health care determinants -for new industrial states. The pair of socio-economic development is the most critical for developing and the least developed countries. According to the resilience level, such countries as Ireland,

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Section: Methodsmentioning

confidence: 99%

Country’s health profile: Social, economic, behavioral and healthcare determinants

Lyeonov¹,

Bilan²,

Yarovenko³

et al. 2021

Economics &Amp; Sociology

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“…Saving funds outside the centralized financial sector of the economy in the form of cash savings in foreign or national currency shows erosion of trust at the institutional (to the national currency, the central bank (the National Bank of Ukraine), individual financial corporations (bank, insurance company, non-state pension fund, etc.)) and system levels (Djalilov et al, 2015;Halbusi & Tehseen, 2018;Baburina et al, 2017;Buriak et al, 2015;Merenkova & Boyko, 2009;Kuzmenko & Koibichuk, 2018, Kuzmenko & Kyrkach, 2014Onyshchenko & Chen, 2017;Luchko et al 2019;Simionescu, 2019).…”

Section: Methodsmentioning

confidence: 99%

“…Thus, the features of developmental stability in Lithuania and Ukraine are investigated in the works of Filipishyna et al (2018). The specificity of the development of the insurance market in Ukraine compared to European countries is considered in the works of scientists: Kozmenko et al, (2009). The following scientists as Horsch et al, (2018) studied the specifics of deposit insurance systems of post-Soviet countries.…”

Section: Methodsmentioning

confidence: 99%

Trust cycle of the finance sector and its determinants: The case of Ukraine

Brychko¹,

Polách²,

Kuzmenko³

et al. 2019

Journal of International Studies

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The paper presents the results of exploring the characteristics of trust cycle in the financial sector of the economy in general and across its main components (trust in banking and non-bank financial and credit systems) illustrated by the economy in transition-Ukraine-for the period 1st quarter 2009-1st quarter 2018. Determinants of nonlinear dynamics of public trust in the financial sector of the economy were also identified. For this purpose, an algorithm has been developed that enables studying the cyclical nature of public trust in the financial sector and testing the hypotheses about the determinants of its nonlinear dynamics. To highlight the cyclical component of the time series, harmonic analysis via Fourier transformations was used. In order to analyze public trust in the financial sector and its main components the following indicators were used: absolute volatility, relative volatility (in relation to financial and business cycles), the persistence of actual values and cyclic components, correlation with financial and business cycles. Our main

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“…The relevance of a reasonable determination of each of the characteristics of the process under study is associated with obtaining adequate results (Bublyk et al, 2017). Thus, regardless of what economic and mathematical tools will be used, the reliability of the results will be low if the input information does not characterize the features of the studied risk (Kozmenko et al, 2009;Vasylyeva et al, 2016). Thus, the risk of using financial institutions for money laundering is characterized through a spatial analysis of data for 105 countries in 2018.…”

Section: Formation Of Input Statistical Base Of the Study Verificatimentioning

confidence: 99%

Data mining and bifurcation analysis of the risk of money laundering with the involvement of financial institutions

Kuzmenko

Šuleř

Lyeonov

et al. 2020

Journal of International Studies

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The current trends of globalization, the integration of banks and insurance companies worldwide into a single financial conglomerate, as well as the emergence of new electronic payment instruments, force governments of different countries to search for new approaches to analyse the risks of involvement of financial institutions in money laundering. The research explains how to use the data mining and bifurcation analysis based on the limited information on general indices of a country's characteristics to evaluate the state's resilience to the involvement of its financial institutions in money laundering. The purpose of the article is to develop a scientific and methodological approach to assessing the risk of using financial institutions in money laundering. It is based on the study of the dynamic stability of this risk on the basis of bifurcation theory. Empirical calculations show that for a group of countries, to which Ukraine belongs, the dynamic system is in a non-equilibrium state and is described as a phase portrait "saddle". Therefore, the risk of using financial institutions for money laundering is high in Ukraine, although it is under certain control by the state. However, the calculations show that under conditions of the partial reform of the anti-money laundering system in Ukraine, the system will lose its conditional stability and the corresponding risk will increase even more

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The analysis of insurance market structure and dynamics in Ukraine, Russia and European Insurance and Reinsurance Federation (ɋȿȺ) member states

Cited by 11 publications

References 0 publications

Country’s health profile: Social, economic, behavioral and healthcare determinants

Country’s health profile: Social, economic, behavioral and healthcare determinants

Trust cycle of the finance sector and its determinants: The case of Ukraine

Data mining and bifurcation analysis of the risk of money laundering with the involvement of financial institutions

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