The effectiveness of the internal control system in Vietnamese credit institutions

The article analyzes the regulatory framework in the insurance market in connection with the advent of Big Data, such as information collected from different sources that can be manipulated by new technologies. The use of Big Data offers significant opportunities to the insurance companies in terms of digitization of the distribution channels and greater knowledge of the customers, which is instrumental to a more effective identification of the individual’s risk profile, as well as improvement of the competitiveness. However, regulatory measures are needed for a proper use of Big Data in terms of respect of the individual privacy, potential discrimination and constraint on competition.

A model for estimating the likelihood value of residual risk (Y) is introduced. The model consists of three independent variables: the likelihood value of risk before risk treatment (X1), the quality of risk treatment (X2), and the appropriateness of risk treatment (X3). An experimental research design with a multiple linear regression analysis was used in the estimation. All independent variables, the likelihood value of risk before treatment, the quality of risk treatment, and the appropriateness of risk treatment, can be significantly used to estimate the likelihood value of residual risk. Since no model of estimating residual risk of likelihood had been introduced yet, the findings of this study provide significant contribution to firms or organizations that need to assess the likelihood value of residual risks.

This paper explores the influence of the ESG disclosure regulation (government corporate ESG disclosure and non-government corporate ESG disclosure) on the ranking in 50 largest economies. Applying various statistical methods and techniques, including both parametrical (Student’s t-test, ANOVA analysis) and non-parametrical (Mann-Whitney U test) tests, simple average analysis, OLS with dummy variables method and multiple linear regression analysis, as well as correlation analysis and Granger causality test, several hypotheses are tested. The hypotheses stipulate whether or not ESG disclosure regulation differs in developed and emerging countries and whether or not ESG disclosure regulation influences the country’s SDGI ranking, as well as the ranking of the country among 50 largest economies. According to the results, the differences in ESG disclosure regulation are statistically significant in developed and emerging countries. The level of ESG disclosure compliance is higher in developed countries. ESG disclosure regulation influences the position of the country in SDGI and 50 largest economies rankings. The more country complies with ESG disclosure criteria, the better position in rankings is. Incorporation of ESG criteria is an important evolutionary step in economic development of the country. It allows increasing position of the country in 50 largest economies and SDGI ranking. Thus, ESG disclosure regulation is vital for the development of the country in the modern world.

Acknowledgment
Comments from the Editor and anonymous referees have been gratefully acknowledged. Alex Plastun gratefully acknowledges financial support from the Ministry of Education and Science of Ukraine (0117U003936). Inna Makarenko gratefully acknowledges financial support from the Ministry of Education and Science of Ukraine (0117U003933).