Virtue and Risk Culture in Finance

The motivation for this research was the desire to disclose the social nature of the financial risks of global companies: the authors attempted a scientific explanation of the influence of corporate social responsibility, which is manifested through the preservation and creation of additional jobs, on the financial risks of global companies. The research aims to establish the interdependence between financial risks and sustainable employment in global companies. This goal is achieved using the SEM (structural equation modeling) method based on corporate statistics from the Fortune “Global 500” rankings for 2021–2023. As a result, the consequences of global companies’ CSR (corporate social responsibility) practices in personnel management and financial risk management are modeled and described through quantitative and qualitative patterns. The established regularities proved that for developed and developing countries, the larger the number of employees, the lower the financial risks of global companies—the risk of a decrease in profitability, the risk of loss of profit, and the risk of depreciation of assets. The main conclusion is that there is a close systemic relationship between the financial risks of global companies and their workforce size, suggesting that CSR is key to highly effective financial risk management. A clear distinction between the practices of financial risk management through CSR in developed and developing countries forms the basis of the theoretical significance of the research results. The authors provide recommendations to improve the current practice of financial risk management in global companies by integrating it more closely with personnel management practices, highlighting their managerial relevance. It is proposed that corporate strategies for global companies in developed countries should focus on reducing the risk of declining profitability, as CSR has the most pronounced and consistent impact on this particular financial risk. In developing countries, corporate strategies are recommended to be structured by diversifying the areas of CSR application, with the most promising in financial risk management being the reduction in asset depreciation risk and the reduction in profitability risk. The findings of this research have practical significance because they enhance the predictability of CSR activities of global companies and open up opportunities for highly accurate forecasting of the financial risk implications of ensuring sustainable employment by global companies, considering the specificities of developed and developing countries.

Purpose: The purpose of this study was to investigate how financial risk management strategies lead to growth of MFI sector in Kenya.Methodology: The study adopted a correlation survey research design. The population of this study was fifty seven (57) MFIs. The sampling frame was the list of MFIs provided in the AMFI website www.amfikenya.com. A sample of thirteen (17) MFIs was selected using the random sampling approach. A questionnaire and an interview schedule were the main data collection tools. Qualitative data was analyzed using content analysis whereas the quantitative data was analysed using Statistical Package for Social Sciences (SPSS) where descriptive and regression analysis were conducted to determine the relationship between enterprise risk management strategies and growth of MFIs.Findings: The findings indicated that MFIs had effective financial risk management strategies such as effective credit risk management practices, liquidity risk management practices, interest risk management practices and price risk management practices. In particular, MFIs took into consideration the conditions, characters, capacity, collateral and capital of borrowers. Strict debt collection practices were widely adopted by MFIs. In addition, the concept of Know Your Customer (KYC) policy, seem to have been adopted by MFIs. The relationship between financial risk management strategies and growth was positive and significant. It also shown that sources of funds for MFIs include external sources and internal sources and the most frequently used source of funds are bank loans. The use of banks loans may present various risk exposures to MFIs, the most significant being interest rate risk. However, the ability of MFIs to source funds from various sources indicates that MFIs can apply the pecking order by first exploiting internal sources of funds since they present a lower financial risks and then move on to external sources. However, despite the financial risk exposure accompanied by leverage from external sources, MFIs may also benefit as they may experience higher growth driven by the leverage. It was also found that MFIs had put in place a number of good practices that had emerged to promote responsible and inclusive lending. These include loan size limits, standardized (simple) loan terms, zero tolerance on delinquency, group-based lending. This finding implies that MFIs have put in place effective credit risk management policies which are part of an overall financial risk management strategy. The existence of effective financial risk management practices may have influenced the growth of MFIsUnique contribution to theory, practice and policy: The study recommends that the MFIs to continue practicing effective financial management practices as this would improve the growth of MFIs.

Microfinance institutions (MFIs) have evolved in different and complex ways to solve various market frictions, with some of them providing a wide range of financial products and using different lending technologies to reach poor and underserved populations. As a result, some MFIs are more efficient than others, but are efficiency gains aligned with risk management practices? The specific characteristics of the microfinance industry make the answer to this question less obvious than that of commercial banks. This paper tries to shed light on these issues by analysing the efficiency and risk management of MFIs and describing the potential implications of these relationships for the microfinance industry. After considering several measures of financial risk management ratios commonly used in the microfinance literature, our results show that cost efficiency improves asset quality and solvency of MFIs, but also reduces the need for holding idle cash or liquid assets. The results of this paper can help academics, policymakers, and regulators to better understand the impact of cost efficiency on financial risks management practices in the microfinance industry.

This is the third in a series of surveys on financial risk management practice and derivatives use by non-financial corporations in the United States undertaken by the Wharton School. This 1998 survey, written in partnership again with CIBC World Markets, extends the previous two surveys by asking new questions about certain aspects of derivative use and risk management practice. This report compares responses across the various surveys and notes changes in responses over time. A tabulation of the responses to all questions is included in the appendix.

PurposeThis article examines the relationship between financial risk management and succession planning in family businesses. Motivated by the Theory of Planned Behaviour, we hypothesize that the use of professional risk management practices is associated with an increased likelihood that businesses adopt professionalized approaches to succession planning. We then investigate if succession planning professionalization is, in turn, positively related to the financial performance of family businesses.Design/methodology/approachWe apply binary probit and ordered dependent variable regressions to unique data generated from a survey sample of Australian family businesses. To check the robustness of our results to potential endogeneity concerns we apply difference tests to propensity score matched sub-samples from our original cohort of respondents.FindingsThe results show that, in contrast to verbal or absent succession arrangements, formal written succession plans are both positively associated with the use of financial risk management practices and with superior financial performance in family businesses.Originality/valueOur arguments and findings suggest that active financial risk management provides a platform for planning succession in family businesses, and that this links with improved short-term financial performance. In light of the critical role that succession plays in ensuring long-term business sustainability, our findings provide important and novel insights into the conditions under which family businesses are most likely to use formal professionalized succession planning.

This paper analyses the methods and frameworks used by firms in emerging markets when adapting their risk management strategies across the different dimensions of the strategic, financial, institutional, and operational scopes. In addition to the existing literature surrounding enterprise risk management and the emerging economies (Boubaker et al. 2016), this particular study looked to understand the response of firms to increased levels of uncertainty attributed to macroeconomic turbulence, coupled with the regulatory and or institutional voids. With the use of a constructive integrative approach in the comparative and institutional literature, this paper attempts to consolidate analyses surrounding the firm-level adaptations to fragmented markets and governance policy constraints, coupled with an unpredictable policy environment. Empirical evidence suggests that risk management frameworks that are based (modified or otherwise) on global standards issued by the international regulatory bodies are rarely used by the firms in emerging economies. Rather, such firms tend to contextualize their systems by adjusting their frameworks to align with the institutional setting of the emerging economies within which they operate. In particular, firms tend to incorporate informal governance, relational contracting, and political risk-attribute frameworks into their strategic decision-making processes to counter regulatory and enforcement gaps (Henisz and Zelner 2015; Khanna and Palepu 1997). In response to the currency instability, gaps in capital market accessibility, and limited credit, the financial risk management practices and operational risk mitigate flexibility, redundancy, and supply chain risks, and the control mechanisms straddle. This type of operational adaptation signals a responsiveness to the management of risk in environments of continuous uncertainty and fundamental transformation. Integrated and context-sensitive risk management practices in emerging markets consistently outperform the application of standardized global models, which serves as the basis of the postulate of the undertaken research. Furthermore, the research illustrates that the alignment of risk management and local institutional order conditions proves the greatest resilient and high-performing divergence when compared to the application of systemic, contextually blind models (Hoskisson et al. 2000; McNeil et al. 2015). This conclusion elevates the importance of institutional knowledge as a distinctly relevant factor within enterprise risk management.

Fractional Brownian motion in option pricing and dynamic delta hedging: Experimental simulations

The rapid advancement of artificial intelligence (AI) technologies, particularly generative AI and large language models (LLMs), has ushered in a new era of possibilities for the financial sector. This paper explores the integration of these cutting-edge technologies into financial sector risk management, examining both the potential applications and the necessary regulatory frameworks. We provide a comprehensive analysis of how generative AI and LLMs can revolutionize risk assessment, fraud detection, market analysis, and regulatory compliance. The study delves into the technical aspects of these AI models, their implementation challenges, and the implications for existing risk management practices. Furthermore, we propose a novel framework for the responsible adoption of AI in financial risk management, addressing concerns related to model interpretability, data privacy, and algorithmic bias. Our findings suggest that while generative AI and LLMs offer unprecedented opportunities for enhancing risk management capabilities, they also necessitate a recalibration of regulatory approaches to ensure financial stability and consumer protection. This research contributes to the growing body of literature on AI in finance and provides actionable insights for practitioners, policymakers, and researchers in the field.

Purpose – This study investigates the role of AI-driven business analytics in strengthening financial risk management within the banking and insurance sectors. It examines the extent of AI adoption, its impact on organizational resilience, the challenges encountered during implementation, and the future prospects of AI integration in risk management practices. Design/methodology/approach – A quantitative research design was employed using a structured questionnaire administered to 350 professionals across banking and insurance organizations. The survey measured four core constructs—AI adoption, impact on risk management, challenges, and future prospects—using a five-point Likert scale. Descriptive statistics, reliability testing, and Pearson’s correlation analysis were conducted to ensure measurement validity and to examine interrelationships among constructs. Findings – Results indicate moderately high adoption of AI (M = 3.72, SD = 0.64) and a strong positive impact on risk management (M = 3.88, SD = 0.59). Respondents acknowledged moderate challenges (M = 3.41, SD = 0.70), including cost, regulatory uncertainty, and lack of skilled professionals. Despite these barriers, future prospects of AI in financial risk management were viewed with high optimism (M = 4.12, SD = 0.55). Correlation analysis confirmed significant positive associations between AI adoption, enhanced risk management, and future outlook, while challenges were negatively correlated with all other constructs. Originality/value – This study contributes to the growing body of knowledge on digital transformation in financial services by providing empirical insights into how AI-enabled analytics are reshaping risk management. The results indicate that the strategic role of AI in banking and insurance is not only significant but also that organizational, regulatory, and ethical issues are urgent in order to achieve the maximum benefit.

Implementation of the Single Customs Territory (SCT) in Tanzania, particularly at strategic points like the Holili border, continues to face significant challenges due to various risk factors that hinder the efficiency and effectiveness of cross-border trade. Despite the application of the SCT framework, risks related to compliance, security, and financial management remain persistent obstacles to trade facilitation. This study aims to assess the effectiveness of SCT risk management in enhancing cross-border trade by examining the influence of compliance, security, and financial risks. A convergent research design with a mixed approach was employed. The sample size of 200 respondents was selected using a convenience sampling technique. The data was collected through a structured questionnaire. The instrument was ensured through expert review, while reliability was confirmed with a Cronbach’s alpha coefficient of 0.846, indicating a high level of internal consistency suitable for data collection. Multiple linear regression analysis was used for data analysis. Testing the research hypothesis showed that managing the three risk factors (compliance risk, security risk, and financial risk) has a statistically significant and positive influence on cross-border trade, with financial risk management emerging as the most dominant predictor. In particular, effective compliance measures ensuring accurate documentation and adherence to trade regulations facilitate smoother trade processes. Similarly, strengthened security mechanisms, such as cargo scanning and tracking technologies, minimize disruptions and delays. Most notably, robust financial risk management practices significantly reduce fraudulent practices, build trust among trading parties, and improve the overall integrity and efficiency of trade operations. These findings affirm the importance of an integrated risk management approach in improving cross-border trade outcomes. The Tanzania Revenue Authority and relevant regional bodies should prioritize capacity building in financial oversight and deploy advanced monitoring tools to mitigate identified risks and optimize SCT performance. In addition, the results of this research may help improve the risk management system of single customs territories in other countries.

This bibliometric analysis explores recent trends and influential contributions in financial risk management, shedding light on thematic clusters, keyword occurrences, and highly cited works. The analysis encompasses a wide array of literature, ranging from the integration of risk considerations into broader corporate strategies to the impact of technological advancements on risk management practices. Thematic clusters reveal the interconnectedness of business practices, corporate social responsibility, and risk management, while keyword occurrences highlight dominant themes like financial performance and credit risk management. Highly cited works by notable authors provide foundational insights into risk management for financial institutions, emphasizing liquidity risk, corporate governance, and the integration of theoretical frameworks with practical applications. The synthesis of these findings offers a comprehensive understanding of the evolving landscape of financial risk management, guiding researchers, practitioners, and policymakers in navigating the complexities of risk in contemporary financial contexts.

Chinese financial market environment has also undergone a series of changes. How banks can identify and effectively prevent and control financial risks has become the focus of their research. For this reason, this paper makes a careful study on the management ideas of bank financial risk, first introduce the relevant content and characteristics of bank risk identification and management, explaining the new requirements and challenges brought about by the bank's financial risk management under the current background, and focus on analyzing the relatively representative issues in the financial risk management of banks in various regions, finally, it puts forward the strategies and improvement ideas on how to improve the quality and efficiency of bank risk management.

Использование таких понятий, как риск-аппетит и толерантность к риску, общепринято в международной практике финансового управления и риск-менеджмента. При этом международные стандарты не формализуют подходы к оценке риск-аппетита, поэтому для многих руководителей данные понятия остаются лишь теоретической конструкцией, которую сложно измерить в цифрах и применить в практической работе. В данной статье предлагается подход к оценке риск-аппетита на основании формализованной оценки финансового состояния компании – внутреннего кредитного рейтинга. Результаты такой оценки в дальнейшем могут быть использованы для построения кривой толерантности риска и для ранжирования рисков на карте рисков. Благодаря применению такого прозрачного подхода к оценке, риск-аппетит может стать практическим инструментом совета директоров, позволяющим определить приоритеты и распределить уровни ответственности за управление рисками компании.

The article examines the features of using financial risk management and corporate social responsibility tools to ensure the sustainability of construction enterprises. The principles of business social responsibility in modern conditions of the construction industry are analyzed. The aspects of implementing risk management measures in construction enterprises are identified. The issues of using the principles of risk management and corporate social responsibility of business are formulated. The need to improve the tools for implementing the financial risk management and corporate social responsibility system to ensure the sustainability of construction enterprises in the context of sustainable development and Industry 4.0 is substantiated. It is argued that the study of the theoretical basis of financial risk management and corporate social responsibility of construction enterprises confirmed the importance of implementing such tools not only to support the competitiveness of the business, but also to ensure its sustainable development in the long term. It is proven that the construction industry has a significant impact on regional socio-economic development and well-being of the population, which requires an integrated approach to the implementation of social responsibility strategies. It is analyzed that the activities of construction enterprises in the field of social responsibility are aimed at reducing the negative impact on the environment, improving occupational safety, developing local communities and adhering to high standards of business ethics. It is proven that the implementation of risk minimization principles requires not only careful analysis and risk management, but also the transformation of corporate governance, adaptation to the requirements of new technologies and flexibility in making strategic decisions. It is substantiated that understanding and taking into account these key aspects of risk management and social responsibility helps enterprises increase their competitiveness, adaptability and sustainability in the global economic environment.

In the past, financial risk management has always faced a changing market environment and while there were several traditional predictive models available for use, they have limited capabilities in addressing non-linear or high-dimensional risk factors. Therefore, enhancing the foresight in risk identification as well as the accuracy of decision-making within financial institutions will require further exploration into the application value of artificial intelligence and big data technology. Consequently, the goal of this paper is to conduct a comprehensive evaluation regarding the integration pathways and effectiveness of implementing these two technologies into financial risk predicting and managing practices. Findings from the research indicate that AI algorithms offer a deeper understanding of complex, hidden relationships among large amounts of multiple sources of information, while the availability of big data platforms provides opportunities for continuously monitoring risk in real-time. The combination of the two not only significantly improves the timeliness and accuracy of risk prediction, but also promotes the intelligent transformation of risk management models from passive response to active intervention.