Risks, Volume 9, Issue 6 (June 2021) – 20 articles

The aim of this study is to present the trends and effectiveness of money laundering countermeasures from the perspective of a number of suspicious transactions reported to the Financial Intelligence Units (FIUs), a number of analysis results submitted to law enforcement authorities, and the typologies of cases in European Union Member States. In order to determine the impact of the joint effort in the fight against money laundering, we used descriptive statistics to process the data and case studies from annual reports of the European FIUs for 2018 and 2019. The results of our study highlight the increase in the number of suspicious transactions notices, as well as in their quality level. There is an increasing tendency towards information exchange between European Union countries regarding the suspicion of money laundering, but there is no stable trend for referring cases to law enforcement and other responsible institutions. Based on the available data, it can be concluded that the EU anti money laundering measures are efficient, but further steps are needed to achieve higher international coordination and cooperation. Full article

Fraud is one of the most harmful phenomena, because it leads to collapse of organizations, causes economic downfall of countries, and destroys faith in a country’s capital markets. The impact of fraud is complex and has varying degrees depending on political and financial institutional structures of a country. In this paper, we investigate the combined effect of economic and non-economic variables on fraud using a sample of 41 developed, in transition, and developing European countries. The data cover the period July 2014–December 2020. Panel data techniques of pooled estimation and the dynamic panel data/generalized method of moments (DPD/GMM) is used, keeping in view the endogeneity perspective. Nevertheless, two-way impacts of fixed effect model estimation—cross-sectional and time-based (panel) effects (alternatively)—are used for analyzing the relationship among the given variables, based on Hausman specification test results. Empirical results of panel data extended REM and FEM approaches with country-specific cross-sectional effects showing that political stability, economic freedom, poverty, and GDP significantly affect fraud proliferation. Political stability is appraised to be the most scoring determinant of fraud incidence in a country. Full article

Innovation risk in banks, a formalized instrument that is part of banks’ financial and innovative strategies, influences the assessment of innovative activity, demonstrating the importance of forecasting and assessment models of potential innovation risks. Our research into general scientific and specific methods allowed us to: (1) distinguish hierarchical concepts and their order—namely, “banking innovation”, “economic effects of innovational activities”, “financial and innovative strategy”, and “innovation risk”; (2) identify links between innovative and strategic bank management, since bank innovations are carried out in conjunction with strategies and imply positive strategic economic effects, making the assessment of potential innovation risk necessary for the current moment and the future; (3) note that the launching and use of new technologies on economic cycles and phases involving a necessary correlation between innovative profit and these phases; (4) provide preferable measurements of banks’ innovative activity and financial performance against commission income; (5) assess the potential financial performance of banks’ financial and innovative strategies within economic cycles and phases and in accordance with the nature of income; (6) present general areas for the practical application of an adapted data mining–Monte Carlo method, based on a proprietary software product. The model’s application in the “open innovation” system exhibits its multipurpose nature and allows for the selection of alternative strategic innovative solutions within economic cycle phases. It also serves in the promotion of Big Data technology in relation to finance and innovation, which is a promising area, and determines the values of the desired indicators for the “bank of the future” concept. Full article

The aim of the present study is to examine the sustainability reports of cooperatives, which may play an important role in achieving the sustainable development goals and help to identify which economic, environmental, and social sustainability indicators cooperatives are currently reporting. For this purpose, a total of 168 sustainability reports were examined for cooperatives that use the Global Reporting Initiative (GRI) G4 reporting, and that are included in the Sustainability Disclosure Database (SDD-GRI). As a result of this study, it was determined that the economic performance indicator disclosure levels of cooperatives that are active in the financial services sector are higher compared with those of cooperatives that are active in other sectors. In addition, it was also observed that the labor practices and decent work sub-category indicator disclosure levels of cooperatives active in the agriculture sector are lower compared to those of cooperatives that are active in the healthcare services and financial services sectors. Another outcome of this study was the finding that the social performance indicator disclosure levels for large-scale cooperatives are greater than those of small- and medium-sized (SME) cooperatives. Full article

Tax avoidance is one of the most frequent reasons for which companies tend to resort to creative accounting techniques. The purpose of the study is to identify which of the eight-variables from the Beneish influences the most or least the outcome of the final score, as a percent, by developing a statistical model. The sample was selected from the Bucharest Stock Exchange and consists of 66 companies traded on the main market, for the years 2015–2019. The results show that from the total of the eight variables, GMI (Gross Margin Index), AQI (Asset Quality Index), DEPI (Depreciation Index) and TATA (Total Accruals to Total Assets) are significantly influencing the probability to commit fraud. The developed model is validated with only 10% of the non-fraud companies being mistakenly considered as fraud based on our model and vice versa. Full article

The key purpose of this paper is to present an alternative viewpoint for combining expert opinions based on finite mixture models. Moreover, we consider that the components of the mixture are not necessarily assumed to be from the same parametric family. This approach can enable the agent to make informed decisions about the uncertain quantity of interest in a flexible manner that accounts for multiple sources of heterogeneity involved in the opinions expressed by the experts in terms of the parametric family, the parameters of each component density, and also the mixing weights. Finally, the proposed models are employed for numerically computing quantile-based risk measures in a collective decision-making context. Full article

The paper introduces a novel approach to ensemble modeling as a weighted model average technique. The proposed idea is prudent, simple to understand, and easy to implement compared to the Bayesian and frequentist approach. The paper provides both theoretical and empirical contributions for assessing credit risk (probability of default) effectively in a new way by creating an ensemble model as a weighted linear combination of machine learning models. The idea can be generalized to any classification problems in other domains where ensemble-type modeling is a subject of interest and is not limited to an unbalanced dataset or credit risk assessment. The results suggest a better forecasting performance compared to the single best well-known machine learning of parametric, non-parametric, and other ensemble models. The scope of our approach can be extended to any further improvement in estimating weights differently that may be beneficial to enhance the performance of the model average as a future research direction. Full article

The emergence of smart technologies in homes comes with various services and functions for everyday life. While a smart home (SH) is associated with great potential in terms of comfort and risk treatment, it also introduces new and alters existing risks. Despite a growing number of academic studies on SH risks, research is fragmented with regard to its focus on certain disciplines and is still rather technology-focused. In this paper, we fill this gap by providing a comprehensive understanding of relevant risks through a systematic literature review. Following the guidelines of the PRISMA reporting protocol, we search 1196 academic and practitioners’ publications related to household risks or risk perceptions of SH users. A final set of 59 records results in three main themes. They include (1) a synthesis of pre-existing and emerging risks sketching the new risk landscape of SH households, (2) a discussion of the prevailing risk evaluation methods, and (3) a presentation of SH-related risk treatment options with a particular emphasis on insurance. We specify the influence of SH on risks and risk perception, and highlight the relevance of analyzing the interconnection of risks in complex systems, such as SH. Our review lays the basis for assessing SH risks and for enabling more comprehensive and effective risk management optimization. Full article

In stochastic claims reserving, state space models have been used for almost 40 years to forecast loss reserves and to compute their mean squared error of prediction. Although state space models and the associated Kalman filter learning algorithms are very powerful and flexible tools, comparatively few articles on this topic were published during this period. Most recently, several articles have been published which highlight the benefits of state space models in stochastic claims reserving and may lead to a significant increase in its popularity for applications in actuarial practice. To further emphasize the merits of these papers, this commentary highlights various additional aspects that are useful for practical applications and offer some fruitful directions for future research. Full article

This paper examines the relative contribution of regular and e-mini futures market to price discovery of EUR/USD futures contracts on the Chicago Mercantile Exchange (CME), using intraday data in 2010.The relative contribution to price discovery is estimated using the information share approach proposed by Hasbrouck and Gonzalo-Granger. Empirical findings indicate that regular futures market contributes significantly to the price discovery, accounting for approximately 66.5% of price discovery in the EURO/USD market. This study also examines if the regular future’s information share (IS) can be explained by the positioning of commercial and non-commercial traders. We find a positive significant relationship between IS and both the speculative trade position and hedgers trade position. The results support the conclusion that the IS of regular futures can be better explained by speculators than hedgers. Full article

Organizational strategic programs are continuously evolving and gaining the attention of policy makers in order to construct organizations’ ecological and socioeconomic systems. The purpose of this study is to examine the relationship between the balanced scorecard (BSC) and sustainable development involving the mediated effect of political and regulatory influence. To achieve the core objectives of the research, the quantitative (positivism) research method is applied. The goal of the current research is made possible through the quantitative method because of its objective nature of reality. A total of 320 questionnaires were distributed among the different levels of managers; 280 respondents returned the questionnaire. The data are analyzed through a modern statistical tool called Smart-PLS, Partial Least Squares (PLS) is high graphical user interference software that is used to calculate Structural Equation Modeling (SEM) through PLS path modeling. Factor analysis is conducted to eliminate the variables that have no contribution and to reduce the variables to obtain better results in regression. The implications are for energy organizations that are struggling to deal with sustainable development and these tools can help them to achieve their sustainability goals. The study concludes that the adoption of BSC is essential to ensure sustainable development regardless of its challenges. Moreover, consideration of meta-constitutional rules as political influence is important to understand and address in order to mitigate financial loss. In nutshell, the use of BSC is highly recommended to eliminate the routine problems and to ensure environmental sustainability. Full article

The widely used Poisson count process in insurance claims modeling is no longer valid if the claims occurrences exhibit dispersion. In this paper, we consider the aggregate discounted claims of an insurance risk portfolio under Weibull counting process to allow for dispersed datasets. A copula is used to define the dependence structure between the interwaiting time and its subsequent claims amount. We use a Monte Carlo simulation to compute the higher-order moments of the risk portfolio, the premiums and the value-at-risk based on the New Zealand catastrophe historical data. The simulation outcomes under the negative dependence parameter $\theta$, shows the highest value of moments when claims experience exhibit overdispersion. Conversely, the underdispersed scenario yields the highest value of moments when $\theta$ is positive. These results lead to higher premiums being charged and more capital requirements to be set aside to cope with unfavorable events borne by the insurers. Full article

We show how to solve Merton optimal investment stochastic control problem for Hawkes-based models in finance and insurance (Propositions 1 and 2), i.e., for a wealth portfolio $X\left(t\right)$ consisting of a bond and a stock price described by general compound Hawkes process (GCHP), and for a capital $R\left(t\right)$ (risk process) of an insurance company with the amount of claims described by the risk model based on GCHP. The main approach in both cases is to use functional central limit theorem for the GCHP to approximate it with a diffusion process. Then we construct and solve Hamilton–Jacobi–Bellman (HJB) equation for the expected utility function. The novelty of the results consists of the new Hawkes-based models and in the new optimal investment results in finance and insurance for those models. Full article

The occurrence of the COVID-19 pandemic revealed many weaknesses in the functioning of businesses. It turns out that managers are not prepared to manage the enterprise’s resources in a high-risk environment. Considering risk managers’ issues requires reaching for theoretical and practical knowledge about competencies shaped in unpredictable conditions. This study attempts to determine the importance of the company’s resource management risk among the managerial staff. For the research carried out in 2019–2020, a questionnaire, interview, and literature studies were used. The questionnaire was addressed to 282 managers from western Poland. Particular attention was paid to establishing the crucial components of the company’s resource management competence. Moreover, the regular self-assessment of risk competence made it possible to present preferences in managing strategic resources, depending on the type of position held. The competence of human resources management risk was also examined according to biographical variables (i.e., age, sex, seniority, and total seniority). Full article

The economic crisis of 2008 has highlighted the ineffectiveness of the banks in their disbursement of mortgages which caused the spread of Non-Performing Loans (NPLs) with underlying real estate. With the methods stated by the Basel III agreements, aimed at improving the capital requirements of banks and determining an adequate regulatory capital, the banks without the skills required have difficulties in applying the rigid weighting coefficients structures. The aim of the work is to identify a synthetic risk index through the participatory process, in order to support the restructuring debt operations to benefit smaller banks and small and medium-sized enterprises (SME), by analyzing the real estate credit risk. The proposed synthetic risk index aims at overcoming the complexity of Basel III methodologies through the implementation of three different multi-criteria techniques. In particular, the integration of objective financial variables with subjective expert judgments into a participatory process is not that common in the reference literature and brings its benefits for reaching more approved and shared results in the debt restructuring operations procedure. Moreover, the main findings derived by the application to a real case study have demonstrated how important it is for the credit manager to have an adequate synthetic index that could lead to the avoidance of risky scenarios where several modalities to repair the credit debt occur. Full article

This conceptual paper focuses on the relationship between insolvency, capital structure, and value creation. The aim is twofold: to define risk-based capital measures able to absorb the effects of financial distress and avoid corporate default; and to verify conditions and limits of use of these measures in corporate financial policies. The capital measures based on insolvency risk will be defined by recalling the concepts of Cash Flow-at-Risk and Capital-at-Risk. A first check on the usefulness of these risk-based measures and their consistency with the principle of value maximization is carried out through a simulation model. The scenario analysis allows us to examine how financial and risk policies oriented by insolvency avoidance affect the firm value. According to evidence from the simulation model, these measures appear to be useful in lowering the default risk, but they require a continuous assessment of their impact on the firm value. Full article

Specialty literature and solutions in the market have been focusing in the last decade on collecting and aggregating significant amounts of data about transactions (and user behavior) and on refining the algorithms used to identify fraud. At the same time, legislation in the European Union has been adopted in the same direction (e.g., PSD2) in order to impose obligations on stakeholders to identify fraud. However, on the one hand, the legislation provides a high-level description of this legal obligation, and on the other hand, the solutions in the market are diversifying in terms of data collected and, especially, attempts to aggregate data in order to generate more accurate results. This leads to an issue that has not been analyzed yet deeply in specialty literature or by legislators, respectively, the privacy concerns in case of profile building and aggregation of data for fraud identification purposes and responsibility of stakeholders in the identification of frauds in the context of their obligations under data protection legislation. This article comes as a building block in this direction of research, as it contains (i) an analysis of existing fraud detection methods and approaches, together with their impact from a data protection legislation perspective and (ii) an analysis of respondents’ views toward privacy in case of fraud identification in transactions based on a questionnaire in this respect having 425 respondents. Consequently, this article assists in bridging the gap between data protection legislation and implementation of fraud detection obligations under the law, as it provides recommendations for compliance with the latter legal obligation while also complying with data protection aspects. Full article

Survival analysis is one of the techniques that could be used to predict loss given default (LGD) for regulatory capital (Basel) purposes. When using survival analysis to model LGD, a proposed methodology is the default weighted survival analysis (DWSA) method. This paper is aimed at adapting the DWSA method (used to model Basel LGD) to estimate the LGD for International Financial Reporting Standard (IFRS) 9 impairment requirements. The DWSA methodology allows for over recoveries, default weighting and negative cashflows. For IFRS 9, this methodology should be adapted, as the estimated LGD is a function of in the expected credit losses (ECL). Our proposed IFRS 9 LGD methodology makes use of survival analysis to estimate the LGD. The Cox proportional hazards model allows for a baseline survival curve to be adjusted to produce survival curves for different segments of the portfolio. The forward-looking LGD values are adjusted for different macro-economic scenarios and the ECL is calculated for each scenario. These ECL values are probability weighted to produce a final ECL estimate. We illustrate our proposed IFRS 9 LGD methodology and ECL estimation on a dataset from a retail portfolio of a South African bank. Full article

The economic crisis triggered by the COVID-19 outbreak has severely affected the global economy. The ultimate scale of the recession is yet to be determined, but it is likely to be the most dramatic slump since World War II. The impact of the crisis on the financial sector, especially consumer finance, could almost instantly be observed. The article shows how determination and consistency in regulatory actions counteracts the effects of the pandemic crisis for the banking sector and consumer finance. The conducted research has shown the existence of a number of social phenomena typical of this type of global crisis, such as shopping panic, reduced creditworthiness of households related to loss of income, unemployment and increased crime. At the same time, the actions of financial market regulators turned out to be very effective (no negative structural phenomena occurred in the financial market). The accuracy of the selection of instruments and the speed of action limited the social and financial effects of the pandemic, including a loan repayment memorandum, limiting the cost of consumer loans and supporting the banking sector, which will limit the scale of excessive household debt and consumer bankruptcies, and companies were also supported. The research was conducted on the basis of available literature on the subject, market analyses and a review of regulations implemented at the central level and in individual EU member states. Full article

Old-age retirement benefits are a major concern among the Swiss population but estimating one’s revenue after retirement is challenging due to the Swiss social system’s complexity. In Switzerland, as with many other countries, the risk of poverty for retiree people is high, especially for women who often work part-time. The research presented in this paper proposes a methodology to enable the development of a digital platform to provide Swiss citizens the means to verify that their retirement income will allow them to live decently when retired. The aim of the platform will be to allow insured people to plan for retirement in a simplified manner. The methodology used was both qualitative (focus group) and quantitative (surveys). The main results are recommendations for the scope and functionality for a digital platform to be developed. A main conclusion is the need to limit the platform’s scope to old-age pension only (e.g., excluding survivors’ or disability pensions). Moreover, an outcome regarding the functionalities is the proposition of scenarios such as postponed retirement, additional purchases in pension fund, or changes to individual status. The development of the platform is not included in the article. Full article