Risks, Volume 10, Issue 5 (May 2022) – 22 articles

The purpose of this paper is to propose a methodology that enables researchers to identify relevant search terms when conducting a literature review. This methodology requires an analysis of existing literature review articles on the topic under study to form keywords. The objective of this methodology is to reduce bias from keyword selection, to provide assurance on comprehensiveness and transparency of the review process, and to open up opportunities for interdisciplinary studies. In this paper, we tested our proposed methodology by exploring the field of operational risk management (ORM) in banks. Major issues in this literature exist that include controversy on the effectiveness of ORM measurement models and ORM data problems. We described how our methodology facilitated the development of keywords for a potential interdisciplinary approach that has the capacity to appropriately capture the complexity of ORM, thereby enhancing the understanding and ability to resolve the problem of operational risk effectively. Full article

In this study, we explore the research published from 2009 to 2021 and summarize what extant literature has contributed in the last decade to the analysis of volatility and risk management in cryptocurrency investment. Our samples include papers published in journals ranked across different fields in ABS ranked journals. We conduct a bibliometric analysis using VOSviewer software and perform a literature review. Our findings are presented in terms of methodologies used to model cryptocurrencies’ volatility and also according to their main findings pertaining to volatility and risk management in those assets and using them in portfolio management. Our research indicates that the models that consider the Markov-switching regime seem to be more consensual among the authors, and that the best machine learning technique performances are hybrid models that consider the support vector machines (SVM). We also argue that the predictability of volatility, risk reduction, and level of speculation in the cryptocurrency market are improved by the leverage effects and the volatility persistence. Full article

Using the example of the COVID-19 global crisis (2020), we prove the low effectiveness of the existing approach to managing the financial risks of investments based on commercial investments. For this, we performed an applied quantitative study based on the statistics from the World Bank for 2020 and the Forbes Global 2000 ranking in 2021, using as an example 17 developing countries with lower-middle and upper-middle incomes from different regions of the world. As an alternative, we suggest a new approach for managing the financial risks of investments, which is based on corporate social responsibility. It implies the placement of long-term, large-scale investments in social and ecological innovations based on the mechanism of public-private partnership. We substantiated the high effectiveness and advantages of the new approach. The new approach to financial risk management amid a crisis was more effective (in comparison with the existing approach) for businesses (ensures higher return on investments, allows avoiding losses), the government (contributes more to economic growth, the probability of which achievement is higher), and for society (supports SDGs to a larger extent and contributes to sustainable development). This paper contributes to the development of the Theory of Investments (Neo-Keynesianism) and fills a gap in the literature, bridging the gap between the Theory of Investments and the Theory of Sustainable Development—outlining the perspectives of the simultaneous overcoming of economic crises and supporting sustainable development during the management of financial investment risks based on corporate social responsibility. Full article

In this paper, we present a new family of bivariate mixed exponential regression models for taking into account the positive correlation between the cost of claims from motor third party liability bodily injury and property damage in a versatile manner. Furthermore, we demonstrate how maximum likelihood estimation of the model parameters can be achieved via a novel Expectation-Maximization algorithm. The implementation of two members of this family, namely the bivariate Pareto or, Exponential-Inverse Gamma, and bivariate Exponential-Inverse Gaussian regression models is illustrated by a real data application which involves fitting motor insurance data from a European motor insurance company. Full article

The life expectancy rate of individuals worldwide has risen, and Saudi Arabia is not excluded. Rising long-life expectancy may jeopardize employees’ pensions and reduce the chances of adequate earnings and a decent life after retirement. Moreover, the number of employees, who have paid into pension funds and are now retired, has increased, indicating that pension funds are expected to decrease. Apart from the above, the level of financial literacy in Saudi Arabia was substandard. Therefore, the ultimate objective of this research is to examine the measurable factors that could impact employees in their financial planning for retirement (FPR). These factors comprise the employee’s financial literacy (FL), financial risk tolerance (FRT), and cultural factors based on the CWO model. Moreover, this study aims to investigate the mediating roles of culture in their relationship with financial planning for retirement. Primary data was collected during the COVID-19 pandemic from mid-July 2020 until the end of January 2021 using a non-probability convenience sampling approach involving 525 participants. The Structural Equation Modelling (SEM) technique was used to analyze the data. To determine the type of study variables, either a formative or reflective model of Confirmatory Tetrad Analysis (CTA-PLS) was used. The results show the significant influence of basic FL, FRT, and culture on FPR. Moreover, it shows the critical role of culture among those with advanced FL and FRT. Previous studies have examined FL and FRT in FPR without considering the effect of culture as a mediator. Full article

The article aims to appraise the role of Corporate Social Responsibility (CSR) and innovation strategies as leverages of a company’s financial performance. The theoretical and empirical statement of this link aims to reinforce the importance of these strategical options in both the managerial and the public policy domain. Shedding light on the economic return of these practices will help managers make better strategic decisions. Policy makers will also grasp the required evidence to encompass CSR in policy packages. To address the research question, data were collected from the Thomson Reuters Eikon Datastream covering the 1000 largest companies listed on the stock exchange worldwide. Thereafter, hierarchical linear regressions were performed to produce the econometric results. Two time frames (2015–2019) were compared to address time–space trends. Enrolling in CSR activities entails additional costs which can undermine the company’s financial performance if not properly supported by public policies. Combining CSR and innovation appears to be the best strategy for companies seeking improvements in their financial performance while being socially responsible. The contribution of this study is threefold: first, the analysis covers the largest thousand firms in operation worldwide; secondly, the econometric results demonstrate that combining CSR with innovation positively impacts financial performance; and lastly, the time comparison evidences a positive but slow evolution in CSR adoption. The article provides an applied perspective, of use both for managers and policy makers, as to how they should approach and disseminate involvement in these types of activities. Full article

Corporate misconduct is a huge and widespread problem in the economy. Many companies make mistakes that result in them having to pay penalties or compensation to other businesses. Some of these cases are so serious that they take a toll on a company’s financial condition. The purpose of this paper was to create and evaluate an algorithm which can predict whether a company will have to pay a penalty and to discover what financial indicators may signal it. The author addresses these questions by applying several supervised machine learning methods. This algorithm may help financial institutions such as banks decide whether to lend money to companies which are not in good financial standing. The research is based on information contained in the financial statements of companies listed on the Warsaw Stock Exchange and NewConnect. Finally, different methods are compared, and methods which are based on gradient boosting are shown to have a higher accuracy than others. The conclusion is that the values of financial ratios can signal which companies are likely to pay a penalty next year. Full article

Heavy tailedness and interconnectedness widely exist in stock returns and large insurance claims, which contributes to huge losses for financial institutions. Diversification ratio (DR) measures the degree of diversification using the Value-at-Risk, which is known to capture extreme risks better than variance. The portfolio optimization strategy based on DR maximizes the effect of diversification for extreme risks. In this paper, we empirically examine the DR strategy by using more than 350 S&P 500 stocks under the assumption that the stock losses are modeled with a flexible multivariate heavy-tailed model. This assumption is verified empirically. The performance of DR strategy is compared with four benchmark strategies: equally weighted portfolio, minimum-variance portfolio, extreme risk index portfolio, and most diversified portfolio. The performance of comparison includes annualized portfolio return, modified Sharpe ratio, maximum drawdown, portfolio concentration, portfolio turnover, and the degree of diversification. DR outperforms other strategies. In particular, DR shows the highest return and maintains the highest level of diversification during the global financial crisis of 2007–2009. Full article

The aim of this article is to identify the risk and the likelihood of potential consequences of the COVID-19 pandemic on the business insurance market in the medium- and long-term horizon. The first section of this elaboration presents the theoretical approach connected with the nature of the pandemic. The second section outlines the presentation of the COVID-19 measurement rules and the third describes the potential effects of COVID-19 on the insurance market. Contrary to other elaborations on this topic which have appeared so far (these are mostly reports describing the financial market in short- and long-term horizons), here, the authors present the medium-term horizon as well. The possible consequences of COVID-19 are outlined both in relation to the insurance company client, e.g., change in the amount of the insurance premium under the insurance agreement, as well as in relation to the insurer, e.g., appearance of innovative and competitive offers (Trott’s concept Special attention has been paid to the way in which the insurer’s strategy (scenario analysis) may be used to build resilience to other crises as well as to the planning of emergency solutions. Actual events confirm the hypothesis that changes in the business insurance market dominated the losses in the aftermath of the pandemic. Full article

Actuaries utilize demographic features such as mortality and longevity rates for pricing, valuation, and reserving life insurance and pension contracts. Capturing accurate mortality estimates requires factual mortality assumptions in mortality models. However, the dynamic and uncertain nature of mortality improvements and deteriorations necessitates better approaches in tracking mortality changes, for instance, using the causes of deaths features. This paper aims to determine temporal homogeneous clusters using unsupervised learning, a clustering approach to group causes of death based on (dis)similarity measures to set representative clusters in detection and monitoring death trends. The causes of death dataset were derived from the World Health Organization, Global Health Estimates for males and females, from 2000 to 2019, for Kenya. A hierarchical agglomerative clustering technique was implemented with modified Dynamic Time Warping distance criteria. Between 6 and 14 clusters were optimally achieved for both males and females. Using visualisations, principal clusters were detected. Over time, the causes of death trends of these clusters have demonstrated a correlated association with mortality and longevity rates, rationalizing why insurance and pension offices may include this approach as a preliminary step to undertake mortality and longevity modelling. Full article

This work analyses whether financial information quality is relevant to explaining firms’ probability of default. A financial default prediction model for SMEs (Small and Medium Enterprises) is presented, which includes not only traditional measures but also financial reporting quality (FRQ) measures. FRQ influences the decision-making due to its impact on financial information, which has repercussions on the accounting ratios’ informativeness. A panel data of 1560 Portuguese SMEs in the construction sector, from 2012 to 2018, is analysed. First, firms are classified as default or compliant using an ex-ante criterion which allows us to identify signs of financial constraints in advance. Then, the stepwise method is employed to identify which variables are more relevant to explain the default probability. Results show that FRQ measures, namely accruals quality and timeliness, impact firms’ defaulting, supporting their relevance in predicting financial difficulties. Finally, using a logit approach, the accuracy of the model increased when FRQ variables were included. Results are confirmed using “new age” classifiers, namely the random forest methodology. This work is not only relevant to the extant financial distress literature but has also relevant implications for practice since stakeholders can understand the impact of financial reporting quality to prevent additional risks. Full article

A lapsed policy is an insurance policy that has become inactive due to non-payment of premiums. The word “lapse” is an insurance topic that constantly evolves, proven by the recent increase in publications on this topic. The study explores the life insurance lapse decision through a comprehensive bibliometric analysis throughout the years, concentrating on publication trends; co-authorship networks among countries, authors, and scientific journals; and the field’s evolution. The research is based on the Scopus database. Ultimately, 178 documents were retrieved and analysed, demonstrating increased literature on insurance lapse from 1971 to 2021. The authors’ keyword co-occurrence network was also analysed for possible future directions of the field. Journals originating from the United Kingdom dominate the publication on life insurance lapsation. In contrast, an author from the United States is at the first rank in terms of the co-authorship network’s total link strength. The results may help researchers define the research objective and determine the aspects of the life insurance lapse for future research. Full article

For annuity providers, a higher life expectancy is not always positive news, as it potentially implies increased future costs, since benefits must be provided over a longer period of time. The underlying risk behind the unexpected improvement in life expectancy is called longevity risk. One way to hedge this risk can be attained with the process of securitization through mortality risk securities. This process requires an accurate prediction of the future mortality dynamics with an appropriate mortality model. However, a major issue in mortality modeling is the limited number of available data for a given population. The purpose of this paper is to present a mortality model under the credibility regression framework, aiming to capture the future mortality trends, especially for population datasets of limited available observations. Then, we show how this approach can be incorporated into pricing longevity bonds with the Wang transform. To ensure transparency and applicability in our illustration, the longevity bond pricing is based on the mortality data of Greece. Full article

The economy is in a state of transformation into a new system, and it is quite realistic that economic entities will be under the influence of certain risky moments. The process of risk analysis and management should be considered by an enterprise as an integral part of enterprise management in extreme conditions of the economic development trajectory and be a guarantor of financial insurance. The goal of this study is the formation of a process approach in enterprise management—the creation of a universal risk management system based on the proposed risk management model to minimize the financial risks of an enterprise. We propose a risk management system that influences the forecasting of financial stability of an enterprise. To form the risk management system, we propose a model of an organisational system, the structural elements of which correspond to the principles of completeness, information capacity and consistency. We identified the diversity of direct and inverse relationships between factorial and productive characteristics, which indicates the complexity of the organisational system management process. The presence of “bottlenecks” in the implementation of expert systems tools was also noted. This was expressed in the difficulty of acquiring the knowledge necessary for the development of meaningful systems and structuring the knowledge gained in a form that is convenient for use. We used the method of qualitative modelling using the apparatus of weighted directed graphs. The study allowed us to formulate a list of factors that characterize the main activities of an enterprise in order to form a mathematical model of enterprise risk management. The developed predictive model is used to simulate extreme events and risks in the process of enterprise development, as one of the foundations of the enterprise management system in the conditions of economic transformation. Full article

The exchange market pressure index has proven to be a major indicator in identifying exchange rate crises in economies; however, due to the complexities surrounding developing economies, the efficacy of the index has been called to question. Specifically, the selection of an appropriate index and the problem of selecting the appropriate threshold for identifying exchange market pressure. To investigate this issue, this study identifies exchange rate crisis episodes in South Africa and Ghana using ridge regression, a discrete threshold regression, and Dynamic Ordinary Least Square (DOLS) models. The results are robust in resolving the problems with an exchange market pressure index. They also point to uneven implementation of the inflation targeting policy framework in the studied countries. Full article

The purpose of this publication is to quantify and compare the market risk on the external government debt of Kazakhstan and Bulgaria in the conditions of COVID-19, the emerging energy crisis, and the coup attempt in the first country. In particular, the authors invest the market risk of sovereign bonds issued on global financial markets. Market risk is assessed both as a single issue and at a portfolio level using the Value-at-risk approach. Sixteen samples with historical observations of all issues of Kazakhstan’s and Bulgarian Sovereign Bonds issued on the international financial markets were formed. The duration method was used in the calculation of Delta normal bond VaR and CVaR. It was found that with the same credit rating, similar portfolio duration levels, similar GDP per capita, Debt (% of GDP), and Debt Per Capita, the market risk on their portfolio differed significantly. The comparison of risk levels between the two portfolios was made by six indicators–two indicators measuring linearly the sensitivity of bond prices to changes in market interest rates (Weighted average Macaulay duration and Weighted average modified duration) and four downside indicators (Undiversified VaR, Diversified VaR, Undiversified CVaR, amd Diversified CVaR). The return/risk performance of both portfolios was assessed by the Sharpe ratio in three variants (SR Undiversified VaR, SR Diversified VaR, and SR Diversified CVaR). When evaluating the bond portfolio VaR and CVaR, a practical version of the Duration method was proposed, which allows the use of an unlimited number of assets, taking into account the correlations between yield returns and historical price volatility. Full article

Goal: To perform monitoring of the modern experience of CSR (corporate social responsibility) manifestation in Russia and to differentiate and quantitatively measure the contribution of the support of SDGs (Sustainable Development Goals) and responsible HRM (human resources management) to managing businesses’ financial risks. For this, a sample of the 11 largest companies of one sphere—the extracting industry—which are included in the ranking of Global 2000 Forbes for 2020 are used. Based on the sample, the authors determine the level of the financial risks of Russian companies in the 2020–2021 period and the impact of CSR (in terms of its distinguished indicators) on it. The authors model and measure the contribution of CSR (in terms of its distinguished directions) to the reduction in the financial risks of Russian companies in 2020 and assess the perspective of the decrease in the financial risks of Russian companies for the 2022–2024 period based on CSR. The novelty of this paper lies in the development of a proprietary classification of the directions of CSR by the criterion of contribution to financial risk management. According to the proprietary classification, the following aspects are distinguished: (1) support of SDGs and (2) responsible HRM. The uniqueness and originality of this paper are due to the fact that for the first time the authors perform quantitative measuring of the contribution of CSR (in terms of the distinguished directions—each in isolation) to managing businesses’ financial risks in developing countries based on the example of Russia. Full article

Intelligent Transport Systems (ITSs) are part of road transportation sector evolution and constitute one of the main steps towards vehicle automation. These systems use technologies that allow vehicles to communicate with each other or with road infrastructure. By increasing information quality and reliability, ITSs can improve road safety and traffic efficiency, but only if cybersecurity and data protection is ensured. With the increase in the number of cyberattacks around the world, cybersecurity is receiving increased attention, especially in the area of transportation security. However, it is equally important to examine and analyze security in depth when it concerns connected vehicles. In this paper, we propose a qualitative risk analysis of ITSs based on Threat, Risk, Vulnerability Analysis (TVRA) methodology, and we focus on ETSI ITS communication architecture. We present a review of solutions and countermeasures for identified critical attacks. Full article

Organizational transformation for digitalization is a daily challenge for organizations. Successful change can be defined as the combined result of a number of factors, in which the attitude, trust and/or distrust of employees towards technology is of paramount importance. The aim of this study was to explore which factors most influence employees’ trust in technology and how the risk they pose can be mitigated. The quantitative research analyzed 473 respondents (Smart PLS3, using SEM model) and came to the following conclusions. Employees’ trust in technology depends primarily on the supportive role of management, and to a lesser extent on the digital readiness of the company and the training provided in the organization. The supportive role of management is a key element in the model, as it affects trust not only in a direct way, but also indirectly, through several pathways in the model. This means that the supportive role of leadership is clearly a decisive influence and its importance helps to assess the risk of trust or lack of trust. Full article

The link between climate change and growing poverty levels makes communities more vulnerable to catastrophes, reducing community resilience to disaster consequences. Development practitioners, planners, and researchers must find novel techniques to build community resilience in the face of an ever-growing hazard in such a circumstance with a spectrum of risk and catastrophe. As a result, the focus of this study was on how school systems, as significant social institutions, might effectively minimize disaster risk in communities. People’s standards, beliefs, and behaviors are greatly influenced by societal institutions. After the family, the school is the second most significant socializing institution, in charge of shaping people’s attitudes, knowledge, behaviors, specialized skills, and values in order to ensure social conformity. The prospect of using school systems to increase catastrophe risk reduction in poor areas of Greece was specifically addressed in this study. The study confirmed that the school curriculum has a positive and significant relationship with disaster risk management. Many advantages are realized, according to the research, if catastrophe risk mitigation is made a priority in Greece’s educational systems. Learning about ideas such as civil protection and incorporating disaster risk management into school curricula are both viewed as vital in enhancing disaster risk management. Full article

The present study analyses BRICS (Brazil, Russia, India, China, South Africa) capital markets in both time and frequency domain using wavelets. We used artificial neural network techniques to forecast the co-movement among BRICS capital markets. Wavelet coherence and clustering estimates uncover the interesting dynamics among the BRICS capital markets co-movement. A wavelet coherence diagram shows a clear contagion effect among BRICS nations, and it favors short period investments over longer period investments. Overall study estimates indicate that co-movement among BRICS nations significantly differs statistically at different levels. Except for China during the great financial crisis period, significant levels of co-movement were observed between other BRICS nations and that lasted for a longer period of time. A wavelet clustering diagram demonstrates that investors would not get any substantial benefits of diversification by investing only in the ‘Russia and China’ or ‘India and South Africa’ capital markets. Lastly, the study attempts to forecast the BRICS capital market co-movement using two different types of neural networks. Further, RMSE (Root Mean Square Error) values confirm the correctness of the forecasting model. The present study answers the key question, “What kind of integration and globalization framework do we need for sustainable development?”. Full article

The problem studied in this paper consists in the fact that the social and financial risks of investments in innovations are managed in isolation, which leads to limited results (reduces certain risks but raises other risks). This paper is devoted to the search for a new strategy of managing the risks of investments in innovations, which would allow balancing the financial interests of business and the interests of employees and is aimed at developing a framework strategy of the systemic management of all risks based on corporate social responsibility. The methodology of this research is based on regression analysis. The research sample comprises data from 80 countries of the world in 2021. The social and financial risks of investments in innovations are identified, systematized, and quantitatively measured and reconsidered from the positions of the UN SDGs. The paper’s contribution consists in substantiating a systemic interconnection between the social and financial risks of investments in innovations and the possibility of complex management of all these risks based on corporate social responsibility. The theoretical value of this paper consists in overcoming the gap in studying the social and financial risks of investments in innovations. The practical value of the authors’ conclusions and recommendations consists in the developed framework strategy being a practical guide for the systemic management of the risks of investments based on corporate social responsibility. Full article