The purpose of this study is to develop a Pandemic Risk Exposure Measurement (PREM) model to determine the factors that affect a country's prospective vulnerability to a pandemic risk exposure also considering the current COVID-19 pandemic. Methods: To develop the model, drew up an inventory of possible factor variables that might expose a country's vulnerability to a pandemic such as COVID-19. This model was based on the analysis of existing literature and consultations with some experts and associations. To support the inventory of selected possible factor variables, we have conducted a survey with participants sampled from people working in a risk management environment carrying out a risk management function. The data were subjected to statistical analysis, specifically exploratory factor analysis and Cronbach Alpha to determine and group these factor variables and determine their reliability, respectively. This enabled the development of the PREM model. To eliminate possible bias, hierarchical regression analysis was carried out to examine the effect of the "Level of Experienced Hazard of the Participant (LEH)" considering also the "Level of Expertise and Knowledge about Risk and Risk Management (LEK)". Results: Exploratory factor analysis loaded best on four factors from 19 variables: Demographic Features, Country's Activity Features, Economic Exposure and Societal Vulnerability (i.e. the PREM Model). This model explains 65.5% of the variance in the level of experienced hazard (LEH). Additionally, we determined that LEK explains only about 2% of the variance in LEH. Conclusion: The developed PREM model shows that monitoring of Demographic Features, Country's Activity Features, Economic Exposure and Societal Vulnerability can help a country to identify the possible impact of pandemic risk exposure and develop policies, strategies, regulations, etc., to help a country strengthen its capacity to meet the economic, social and in turn healthcare demands due to pandemic hazards such as COVID-19.
Changing regulation and business environment as well as development of information technologies in finance is rapidly modifying the financial services industry. This consequently puts the financial services industry under additional pressure and constant growing competition from the financial sector participants, from large technology companies such as Google, Apple, Facebook, Amazon, from large FinTech companies such as PayPal, Moven, TransferWise, mobile network operators and other existing and potential market players. The implementation of the new EU Payment Service Directive (PSD2), which allows non-financial companies to provide access to financial services for bank customers, is expected to disrupt the financial services industry as we know it, and make traditional financial services providers and banks, in particular, think of new creative business models to remain competitive. In the process of doing this, changing the landscape of payments and creating new risks for banking business. With this study we aim to assess the new EU Payment Service regulation in the context of industry competitiveness. The study is based on the examination of the PSD2 Directive exploring the opportunities as well as the risks that it will bring to this industry in the near future, and the possibilities of cooperation of the financial services industry with financial technology developers. Moreover, we analyse structured data, collected from a questionnaire based on 4 themes of perception of techs on the importance they have on ensuring competitiveness, conducted with European tech companies. Most of the questionnaire participants believe that the Payment Services Directive 2 will promote competitiveness, innovations and development. Moreover, findings show that comparativeness is related mainly to low costs and customer satisfaction. However, it is also shown that high quality of products/services as well as relatively high speed of transactions and security, privacy and risk are also perceived as important.
Although there is a large volume of literature on the relationship between Environmental, Social and Governance (ESG) and firm performance, only a limited number of studies have focused on the banking sector. In addition, most of them used linear models. Therefore, in this study, we examined the impact of ESG and ESG pillar scores (environmental, social, and governance) on the market value of U.S. commercial banks by using linear and non-linear panel regression models over the period of 2016–2020. Moreover, we used the market value as a bank value indicator and included the effect of COVID-19. Results show an inverted U-shaped relationship between market value and ESG and The Social Pillar Score (SPS) and a U-shaped relationship between market value and The Environment Pillar Score (EPS). Findings from this study are important indicators for investment managers and policymakers who want to maximise bank market value while complying with ESG standards.
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