Risks, Volume 10, Issue 4 (April 2022) – 18 articles

Cryptocurrency is gaining popularity worldwide, with some countries already starting to regulate and accept cryptocurrency in their financial services. Malaysia’s Securities Commission (SC) announced in October 2021 that over MYR 16 billion (USD 3.85 billion) involving digital assets and cryptocurrencies were traded between August 2020 and September 2021. Since cryptocurrencies are issued by private corporations and are technically beyond the federal government’s control, criminals may use them for illegal reasons such as money laundering and terrorist funding. Consequently, it is vital to examine why investors are engaged in cryptocurrency in the first place. This study aims to provide insight into Malaysian investors’ perceptions by evaluating the influence of perceived risk and perceived value on their cryptocurrency adoption decision. The retail investors’ demographic characteristics (gender, age, education, income, and investment experience) were analyzed as control variables. Data were gathered using purposive sampling, and responses from 211 respondents from various cities in Malaysia were used in the final analysis. Data were examined using Smart PLS Structural Equation Modelling (PLS-SEM). Based on the finding’s, perceived value was found to have a significant influence on cryptocurrency adoption. Meanwhile, perceived risk had no significant influence on the adoption of cryptocurrency among the Malaysian investors. Full article

The current research aims to examine the credit risk determinants in Jordan’s banks. Macroeconomic factors were included to examine credit risk in commercial banks by adopting the balanced data for the examination between 2008–2019. The result shows that credit risk relates to foreign direct investment (FDI) and the output gap. The relation existed since FDI helped the country create job opportunities, increase administrative efficiency and capacity, and work to exchange technologies, ideas, opinions, and human resources, especially in emerging economies. The output gap relates to CR by the ability that borrowers’ cash inflows are reduced when growth slows or turns negative, making it harder for them to meet the interest and principal of bank loans in exchange, especially in markets that have the potential to decrease the output gap. The result specified that as remittance (REMIT) grows, credit risk considerably accelerates, and the same effect was also recognised for public debt (DEBT). The outcomes revealed an important influence of tax on personal income (TAXINC). The examination result proves that credit risk is affected by several factors, which may relate significantly to implications as expected. Full article

This paper provides a review on machine learning methods applied to the asset management discipline. Firstly, we describe the theoretical background of both machine learning and finance that will be needed to understand the reviewed methods. Next, the main datasets and sources of data are exposed to help researchers decide which are the best ones to suit their targets. After that, the existing methods are reviewed, highlighting their contribution and significance in the analyzed financial disciplines. Furthermore, we also describe the most common performance criteria that are applied to compare such methods quantitatively. Finally, we carry out a critical analysis to discuss the current state-of-the-art and lay down a set of future research directions. Full article

In automobile insurance, it is common to adopt a Poisson regression model to predict the number of claims as part of the actuarial pricing process. The Poisson assumption can rarely be justified, often due to overdispersion, and alternative modeling is often considered, typically zero-inflated models, which are special cases of finite mixture distributions. Finite mixture regression modeling of telematics data is challenging to implement since the huge number of covariates computationally prohibits the essential variable selection needed to attain a model with desirable predictive power devoid of overfitting. This paper aims at devising an algorithm that can carry the task of variable selection in the presence of a large number of covariates. This is achieved by generating sub-samples of the data corresponding to each component of the Poisson mixture, and wherein variable selection is applied following the enhancement of the Poisson assumption by means of controlling the number of zero claims. The resulting algorithm is assessed by measuring the out-of-sample AUC (Area Under the Curve), a Machine Learning tool for quantifying predictive power. Finally, the application of the algorithm is demonstrated by using data of claim history and telematics data describing driving behavior. It transpires that unlike alternative algorithms related to Poisson regression, the proposed algorithm is both implementable and enjoys an improved AUC (0.71). The proposed algorithm allows more accurate pricing in an era where telematics data is used for automobile insurance. Full article

Recent studies uncover the lack of symmetry in COVID-19-related economic shock distributions among households. Thus, questions arise about the appropriateness of diverse risk-coping mechanisms by households. We add to this strand of research by focusing on households running a business. In particular, we analyze the role of basic legal aspects of running a business by individuals, specifically a legal form of business activity in shaping COVID-19-related business risk perception. We posit that the different legal forms allow for different risk-coping mechanisms. We incorporate analysis of variance (ANOVA) on data obtained via a survey distributed among households running a business in Poland, a country where the pandemic threatens poverty-reducing growth. We confirm that between the groups of households running a business in various legal forms, there are statistically significant differences regarding the impact of COVID-19. Thus, we conclude that the choice of business legal form affects vulnerability to COVID-19-related interruptions among households running a business. Full article

Purpose: The purpose of this article is to describe the initial concept of household bridging insurance. Design/methodology/approach: In the first part of the article, an extensive literature review is made. This is made to show the research gap of insufficient protection of households against destabilization resulting from the lost personal contribution. Data shown in the text present the scale of the loss of lost unpaid work (based on household time budgets). The existing methods of managing this loss, based on social insurance, are also shown. Findings: This paper discusses the possibility of creating a new insurance. Its need is indicated (research gap, the scale of the problem, and insufficient protection by the social insurance system) and a preliminary outline of its structure is indicated (annuities character, dynamic sum insured related to the lifecycle of the household). The article contains the theoretical background of the new product, and introduces further research on the use of multistate models in the construction and calculation of insurance premiums. Originality/value: So far, studies concerning, inter alia, personal damage indicate the lost personal contribution (unpaid work for household members) and even try to evaluate it. However, no private insurance has been proposed to mitigate the destabilization resulting from the death of an adult household member. The article therefore proposes a new life insurance (a separated policy or as an extension option) that would help the household to return to normal operation after the death of one of the household members. Full article

This paper explores the tuning and results of two-part models on rich datasets provided through the Casualty Actuarial Society (CAS). These datasets include bodily injury (BI), property damage (PD) and collision (COLL) coverage, each documenting policy characteristics and claims across a four-year period. The datasets are explored, including summaries of all variables, then the methods for modeling are set forth. Models are tuned and the tuning results are displayed, after which we train the final models and seek to explain select predictions. Data were provided by a private insurance carrier to the CAS after anonymizing the dataset. These data are available to actuarial researchers for well-defined research projects that have universal benefit to the insurance industry and the public. Our hope is that the methods demonstrated here can be a good foundation for future ratemaking models to be developed and tested more efficiently. Full article

This article analyzes the risk factors influencing the achievement of solid waste sphere reforming goals in Russia. The given arguments present the current state of the reform as not very effective from an economic, environmental, and social perspective. The authors identify four groups of risk factors and put forward, as a critical condition for successful reform, the availability of reliable information, as well as risk management incorporated in the decision-making process. The basis for the research execution was the information from the regional solid waste sphere Master Plans and expert opinions on the readiness to achieve the reform goal regarding 100% MSW sorting based on the staff performance, public awareness, technology availability, and tariff validity assessments. The authors use a decision tree method and MSW sorting system development scenarios to provide the pessimistic and optimistic evaluation on the potential for fulfilling the reform tasks. The conclusions indicate the unattainability of the goals set by the Russian authorities for MSW sorting by 2030. The authors propose to change the status of risk factors through the implementation of certain measures for the transition from a negative to a positive scenario of reforming and to set the realistic goals for MSW sorting in Russia. Full article

Due to the low demand for conventional annuities, alternative retirement products are sought. Quite recently, tontines have been frequently brought up as a promising option in this respect. Inspired by unit-linked life insurance and retirement products, we introduce unit-linked tontines in this article, where the tontine payoffs are directly linked to the development of the underlying financial market. More specifically, we consider two different tontine payoff structures differing in the (non-)inclusion of guaranteed payments. We first price the unit-linked tontines by using the risk-neutral pricing approach. Consequently, we study the attractiveness of these products for a utility-maximizing policyholder and compare them with non-unit-linked tontines. Our numerical analysis sheds light on the design challenges and gives explanations why similar products might not be widely adopted already. Full article

The main function behind the conceptualization of creative accounting is maintaining the quality of financial reporting practice. This phenomenon has attracted the attention of researchers for decades, especially in the banking sector, concerning its wide implications and indications for stakeholders, investors, policy makers and competitiveness. However, the practice of creative accounting is accompanied by some undesirable implications resulting from manipulation procedures. Detailed investigations in the previous literature found limited implications of creative accounting determinants on this practice. Thus, the present study investigated the moderation impact of the audit committee in enhancing the impacts of creative accounting determinants and financial reporting quality in the context of commercial banking. A deductive research approach driven by a survey questionnaire was used as the methodology to attain the designed objectives. The analysed data contributed to providing theoretical conceptualization and practical validation of the moderation impacts of the audit committee on creative accounting determinants and financial reporting quality of the banks regarding designed advantages. In addition, the present findings showed that the audit committee highly moderates the determination of creative accounting regarding financial reporting quality in the commercial banking sector. Lastly, the present study introduces the necessity to use such corporate practice for the beneficial parties as the defense line to reduce manipulation practices and enhance the quality of financial reporting. Full article

Creative accounting is considered to be a 21st-century phenomenon that has received increased attention after the worldwide economic crisis and budget deficits, particularly the prevention and detection of accounting manipulation. Creative accounting is a practice that influences financial indicators by using accounting knowledge and rules that do not explicitly violate accounting policies, rules, and laws. The main purpose for implementing creative accounting is to show the financial position desired by the company management; stakeholders are informed of what the management wants them to perceive. Creative accounting can be used to manipulate financial information from its correct and accurate form by exploiting existing rules or, in many cases, ignoring one or more rules. Therefore, the methodology of the present work contributes to the existing literature by systematically reviewing the impacts of creative accounting determinants on financial reporting quality, especially in the banking sector. In this review, we describe and critically analyze previous relevant works to identify and assess the relationship between the constructs addressed in the study. In conclusion, this study offers insight for academia, researchers, and practitioners on determining creative accounting practices and their influences on fraudulent financial reporting between 2015 and 2020. Lastly, the present study contributes to the existing information by conducting new research on creative accounting determinants to enhance the quality of financial reporting and, therefore, help professionals to improve practices within the profession. Full article

Post retirement, annuities provide a steady stream of income for retirees. However, the annuitization rate is relatively small in the insurance market in many countries around the world. Prior studies have shown that a substandard health status in retirement reduces annuitization due to adverse selection. Recent innovation introduces an enhanced annuity plan where individuals with impaired health are entitled to higher annuity payments. However, this market is less explored in countries other than the UK. This paper aims to study the optimal annuitization rate where both standard and substandard annuity rates are offered in the market. The life cycle model in this paper incorporates multiple health states based on the likelihood of events and quality of life measures. Our framework consists of two important parts. First, we estimate the transition probabilities of all health states in our Markov model using reliable national data. Second, we derive the optimal consumption and annuitization solution to maximize a retiree’s expected lifetime utility given the uncertainty of future health risk. In addition, we also consider the bequest motive in our optimization problem. Our results show that the optimal annuitization is driven by the choice of bequest and risk-aversion parameters, as well as the health status of the annuitant. Whilst the health-dependent utility parameter only affects our results for certain cases. Full article

The link between leverage and growth opportunities has been a topic issue in corporate finance for many years. The present paper aims to investigate the link between credit risk, leverage, and growth opportunities in a sample of Italian innovative small-and-medium enterprises (SMEs), given the lack of empirical literature on the subject. The results of the WLS model confirm the relationship between investments, leverage, and credit risk highlighted by the literature—in particular, a negative relationship emerges between credit risk and investments and between leverage and investments, while the analysis reveals a positive relationship between investments and liquidity. Furthermore, in consideration of the significant economic differences existing between the regional macro-areas into which Italy is divided, the firms were classified by geographical areas. The results show that the northeast area is the region characterised by the most reliable and significant results. The paper is organised as follows: Introduction provides a review of the theoretical and empirical literature on the link between leverage, investments, and growth opportunities and on credit risk; Materials and Methods explain the model; Results explain the WLS regression; Discussions contain the main finding of the analysis; Conclusions summarize the study. Full article

The life insurance industry has experienced phenomenal growth over the years. The broad aim of this study was to establish the variables that influence the demand for life insurance in the BRICS countries (Brazil, Russia, India, China and South Africa). Although many studies have investigated the determinants of life insurance demand, little research has considered the supply-side factors such as financial regulation. Therefore, this study also contemplated the effect of the financial regulation variable on life insurance demand. The inquiry employed a panel of the BRICS bloc of countries as a unit of analysis for 1999–2020 and applied panel data econometric techniques. The study found that the life insurance demand variable (proxied by life insurance density and alternatively by life insurance penetration) was negatively affected by income, unemployment, interest rates and inflation variables. Furthermore, the study documented a positive relationship between life insurance demand and the economic growth and financial freedom variables. This study implies that regulatory authorities should deregulate the life insurance sector to foster financial freedom. Full article

Risk analysis and scenario testing are two of the core activities carried out by economists at central banks. With the increasing adoption of machine learning to enhance decision-support systems, and the amount of collected data spiking, institutions provide countless use-cases for the application of these innovative technologies. Consequently, in recent years, the term sup-tech has entered the financial jargon and is here to stay. In this paper, we address risk assessment from a central bank’s perspective. The uptrending number of involved banks and institutions raises the necessity of a standardised risk methodology. For that reason, we adopted the Risk Assessment Methodology (RAS), the quantitative pillar from the Supervisory Review and Evaluation Process (SREP). Based on real-world supervisory data from the Portuguese banking sector, from March 2014 until August 2021, we successfully model the supervisory risk assessment process, in its quantitative approach by the RAS. Our findings and the resulting model are proposed as an Early Warning System that can support supervisors in their day-to-day tasks, as well as within the SREP process. Full article

This study is an empirical analysis of sovereign credit ratings (SCR) in South Africa (SA) using Logistic Regression (LR) to identify their determinants and forecast SCRs. Data of macroeconomic indicators including SCRs from 1999 to 2020 in quarterly format were classified and analyzed to identify indicators utilized by Credit Rating Agencies (CRAs) and then predict future ratings CRAs take various information from political, infrastructure, financial, economic, regional, local, and other factors pertaining to a country and assess the ability of that country to pay its debt. This information is then presented through a grading scale termed rating, with the highest rating country being highly creditworthy and lowest rating likely to default. There are three major CRAs, namely, Fitch, Moodys and Standard and Poors. The study identified the use of different macroeconomic indicators by CRAs as well as different techniques in assessing and assigning sovereign credit ratings. The study points out that Household Debt to Disposable Income Ratio (HDDIR) was the most influential variable on SCRs. HDDIR, exchange rates and the inflation rate were the most crucial variables for guessing credit ratings. Policymakers should aim to reduce household debt in relation to disposable income, implement policies that strengthen the local currency and stabilize as well as lower inflation. Investors should watch out on nations that have high household debt levels as this may spill over into credit risk. Full article

One of the most basic methods of technical analysis that is used in the practice of investment is the analysis of moving averages, usually calculated for exchange rates in a candlestick representation. The following paper proposes a new, state model, describing the process of trajectory changes in a binary-temporal representation. This kind of representation carries a significantly higher informative value than the candlestick one. The model is based on a proper definition of the moving average, proposed for a binary-temporal representation. The new model allows for exchange rate trajectory prediction in a short future window and, as a consequence, can be used to construct effective HFT systems. The article provides a concept of this kind of system and its comparison with others based on historical data for AUD/NZD exchange rate from the 2014–2020 period. Full article