Enterprise Risk Research Articles

A study of the impact of staggered boards on corporate financialization: from the perspective of board governance.

The objective of this study is to assess the influence of staggered boards on corporate financialization and the role that incentive and supervision mechanisms play in this process. We employ a total of 20,647 panel data samples of Chinese A-share listed companies over the period 2011-2020 to empirically test the impact of staggered boards on corporate financialization in the Chinese context. The results indicate that implementing staggered boards significantly increases levels of corporate financialization. On the one hand, the implementation of a staggered board structure can exacerbate the speculative mindset and profit-driven behavior among board members, leading management to prioritize financial investments for personal gain. On the other hand, a staggered board system may also amplify managerial laziness, potentially incentivizing them to rely heavily on financial investments in order to swiftly achieve performance targets with minimal effort. Furthermore, both managerial ownership and audit supervision are found to be critical factors in mitigating this positive impact and preventing excessive financial investment behavior. This paper offers guidance on comprehending the applicability of staggered board provisions and mitigating financial risks in enterprises.

The Effect of Enterprise Risk Management, Intellectual Capital, and Corporate Policy Disclosure on Company Value with Good Corporate Governance as a Moderation Variable

This study aims to test and empirically prove the effect of Enteprise Risk Management, Intellectual Capital, and Dividend Policy on Firm Value with Good Corporate Governance as a moderating. The source of this study data uses secondary data from companies available at SP Capital IQ with a total of 141 observations that have met the criteria used using purposive sampling techniques. This study employed quantitative research by using multiple regression analysis with a moderating effect (Moderated Regression Analysis) with the STATA program. The results of the study showed that Enterprise Risk Management had negative influence on firm value, Company policy, namely dividend policy, had positive effect on firm value, and Inttelectual Capital also Good Corporate Governance had no effect on firm value. The study also showed that Good Corporate Governance as a moderating variable strengthens the relationship between company policy, namely dividend policy, on firm value but Good Corporate Governance can’t moderate the relationship between both Enterprise Risk Management and Intellectual Capital on firm value.

Chief risk officer and audit fee: An investigation from financial industries in Indonesia

The appointment of a CRO (Chief Risk Officer) influences the implementation of ERM (Enterprise Risk Management), which reduces risk and lowers audit costs. Financial Services Authority Regulation No.17/2014 in Indonesia requires companies to have an RMC (Risk Management Committee), which is different from a CRO equivalent to a C-Level. This study examines the impact of a CRO on external audit costs. The data consists of financial companies listed on the Indonesia Stock Exchange (IDX) from 2011 to 2020. The results show that companies using a CRO have lower risk, thereby reducing audit costs. Additionally, the expertise of a CRO also impacts a higher ERM, which in turn affects the reduction of audit costs. This study contributes to the practical world by supporting the appointment of a CRO to reduce company risk. Thus, the company can deliver better performance.

دور التنبؤ بالأزمات في تفادي المعوقات والمخاطر في المنشآت الصغيرة والمتوسطة في حي الروضة المملكة العربية السعودية

Crisis forecasting is one of the important sciences in management sciences, especially within the scope of small and medium enterprises, because it is more affected than others as a result of their limited financial, administrative and human capabilities. Given this importance, this study aimed to measure the role of crisis forecasting in avoiding obstacles and risks for small and medium enterprises in... Al Rawdah District - Kingdom of Saudi Arabia. In order for the researcher to be able to verify the study hypotheses and achieve its objectives, she followed the descriptive analytical approach, in its social survey style. She also relied in her study on the questionnaire, which was built via the Google Drive forms application for the purpose of sending it via an electronic link to a sample. An amount of 178 individuals are owners and managers of these establishments. The researcher also used the SPSS application to conduct statistical tests to ensure the integrity of the questionnaire, as well as to calculate the impact and statistical differences. The study concluded: - There is a statistically significant role at the significance level of 0.05 for predicting crises and avoiding obstacles and risks. - There are no statistically significant differences at the significance level of 0.05 between the averages of the sample’s answers, whether regarding predicting crises, or avoiding obstacles and risks, which is attributed to the personal variables of the study. The study also presented many recommendations, most notably: Small and medium enterprises in the Qassim region must prepare a reserve staff to avoid their staff from stopping work, in order to ensure business continuity in the event that workers stop working.

Риски внедрения цифровых платформ как отраслевой аспект стратегирования

Even under the current foreign sanctions and external restrictions, Russia’s economic policy is aimed at industrial innovations. However, the ongoing digital transformation remains a serious challenge for timber enterprises: in fact, this industry demonstrates one of the lowest rates of digitalization. Digital transformation has both strategic advantages and strategic risks for such enterprises. If major business fails to consider these risks, the outcome can have long-term negative consequences. Effective strategizing of industrial enterprises needs special methods to identify, describe, and analyze strategic risks. The authors identified the strategic risks of digital transformation and summarized tools that could help timber and forestry enterprises to overcome them. The research relied on the theory and methodology of strategizing developed by Professor V.L. Kvint. According to this approach, a strategy does not identify problems: its main purpose is to identify opportunities, and opportunities always come with risks. The analysis systematized the general and specific features of ERP-systems and digital platforms as key elements of digital transformation. The article introduces opportunities and risks of digital transformation for timber industry enterprises, which must be taken into account by strategists. It also describes an automated process management model as a means of overcoming the risks.

Enterprise risk management and firm performance: Exploring the roles of knowledge, technology, and supply chain

Risk management has become crucial for organizations in the current era. Therefore, this study assesses the impact of Enterprise Risk Management (ERM) on an organization’s performance and examines how knowledge management and technology adoption mediate this impact, along with the moderating effect of supply chain resilience based on the resource-based view and dynamic capabilities theory. Utilizing a questionnaire-based survey, data were collected from 297 respondents in Ho Chi Minh City, Binh Duong, and Dong Nai, Vietnam, by cluster random sampling. The data were statistically analyzed using the partial least squares method. The results indicated a positive effect of ERM on financial performance, while the association with non-financial performance lacked significance. Knowledge management and technology adoption fully mediated the positive impact of ERM on non-financial performance and partially mediated its relationship with financial performance. Furthermore, supply chain resilience strengthened the positive link between ERM and financial performance. In conclusion, these findings contribute to advancing the comprehension of the mechanisms and dynamics involved in knowledge management and technology adoption as mediators and supply chain resilience as a moderator, regarding an emerging country. The study enriches the risk management literature and significantly contributes to enhancing firm effectiveness.

Research on enterprise financing credit based on soft and hard information under the background of blockchain

Under "accelerating the formation of a new development pattern of domestic circulation and domestic and internationaldouble circulation mutually promoting", high-tech enterprises, as an important role in promoting scientific and technological innovation and economic development, are facing the dilemma ofdifficult and expensive financing. This paper establishes acharacteristic evaluation and credit guarantee systembased on big data credit model to explore the difference ofsoft and hard informationon financing of high-tech enterprises in Anhui Province under the background of double circulation. Taking 131 high-tech enterprises in Anhui Province as samples, this paper analyzes the influence of unstructured soft information and structured hard information on credit evaluation and its intensity byhierarchical linear regression model. The results show that soft and hard information indexes have significant positive effects on credit risk of high-tech enterprises, and soft information has more obvious effects on small and medium-sized high-tech enterprises.

Development and Implementation of a Multilayer Deep Learning-Based Bank Credit Risk Forecasting System

The complexity of the financial environment and the international community makes the capital flow face various challenges, and it is difficult to obtain accurate credit prediction results in the actual application environment. Considering the complex non-linear characteristics of customer information, the Analytic Hierarchy Process is studied to meet the needs of bank credit risk assessment. On this basis, a depth neural network with different complexities was selected for the three indicators built to classify the features. The composition of the neural network module and the number of neurons were determined by experiment, and Dropout was used to prevent overfitting of the test dataset. Stability and ablation experiments showed that the model can control the error between datasets to 0.021. The ablation experiment showed that the numbers of hidden layers and neurons were the best. Simulation tests showed that the sensitivity and accuracy of this method were 85.25% and 92.55%, respectively, which were superior to other classification methods. The real data of banks in the past four years were tested. The results could accurately classify the risks of enterprises and individual customers, and the results of stress test showed that the model is stable. It is found that traditional credit risk assessment models rely on statistical means and rule decisions, and these methods may not fully reveal the complex non-linear relationship and the internal relationship of financial indicators in high-dimensional data. The combination of deep learning technology and hierarchical analysis can better deal with and explain the complex non-linear problems in bank risk assessment.

A Review of Research on Strategic Differences and Debt Default Risk

In recent years, more and more scholars have been studying the impact of corporate strategy on debt default, so as to provide enterprises with more perfect strategy differentiation strategy, thus reducing the risk of corporate debt default, and improving the ability of preventing and coping with unforeseen shocks for enterprises with large strategic differentiation, thus reducing the operational risk of enterprises. In this paper, we look at the measurement indexes of strategic differences and debt default risk, as well as the influencing factors of debt default risk, the current status of the research on strategic differences and debt default risk, and put forward governance proposals for debt default.

Enterprise Credit Risk Decision: Application Based on Improved AHP

The credit risk of Shouguang vegetable enterprises in China is the biggest obstacle to corporate loans. Building a credit risk assessment model for Shouguang vegetable enterprises and accurately rating the risk of loan enterprises is the key to successful loans. This article aims to construct an AHP evaluation model for the credit risk of Shouguang vegetable enterprises. The data is sourced from managers, bank credit personnel, university researchers, and enterprise related customers who are familiar with the enterprise, while considering four risk levels: impact degree(I), occurrence probability(P), risk manageability(M), and government support(S). This article uses AHP and risk index scores to evaluate the credit risk of Shouguang vegetable enterprises. This model calculates the risk index score based on survey data from 41 corporate credit risk professionals, constructs a pairwise comparison judgment matrix, and conducts consistency testing. It calculates the risk level membership vectors of impact degree, occurrence probability, risk manageability, and government support level at four risk levels, and then calculates the comprehensive evaluation membership vector of credit risk for Shouguang vegetable enterprise. The calculation results show that the comprehensive credit risk assessment level of Shouguang vegetable enterprise belongs to the general risk level, with a membership value of 0.5836. The results still show that the credit rating of Shouguang vegetable enterprises in the four risk levels of impact degree, occurrence probability, risk manageability, and government support are all average risk levels, but there are differences in membership values. The maximum membership value under the impact degree level is 0.6163, and the minimum membership value under the risk manageability level is 0.5572. This study provides a feasible and practical model for enterprise credit risk assessment and conducts a detailed evaluation of the credit risk of Shouguang vegetable enterprise, providing valuable reference for enterprise managers, bank credit personnel, and related researchers.

Mechanism for ensuring risk resistance in the system of management of enterprises in crisis conditions

The article proposes the structure and relationship of the elements of the mechanism for ensuring risk resistance in the system of managing the activities of enterprises in crisis conditions, which includes three main components: resource, organizational, and support system, each of which contains several elements. It was established that the dual role of risk resistance in the enterprise management system is that, on the one hand, risk resistance contributes to purposeful functioning and development, affecting the overall results of operations. On the other hand, it is determined by the interaction of the enterprise with higher-level systems, as well as internal and external factors that can become sources of risk in crises. It is emphasized that the structure of the mechanism for ensuring risk resistance, being complex and dynamic, requires constant improvement. Regardless of operating conditions and strategic goals, an enterprise must have a mechanism for ensuring risk resistance that best meets its needs. It is justified that the resource component of the mechanism for ensuring the risk resistance of the enterprise includes financial resources of the enterprise; material and technical resources necessary for the organization and ensuring the continuity of the enterprise's risk activities; personnel resources, which are determined by the number of employees engaged in analysis, assessment, and risk management. The organizational component of the mechanism for ensuring risk resistance includes organizing the most effective use of the resources involved, namely methods of analysis, assessment, and management of risks, as well as socio-economic relations arising in the process of a risky situation. The third component of the mechanism for ensuring risk resistance – the security system – includes regulatory and legal, information security, and corporate culture. Keywords: risk resilience, uncertainty, crisis conditions, anti-crisis management, strategic enterprise management.

Enterprise risk management and corporate tax planning

AbstractThis study examines the impact of enterprise risk management (ERM) programs on corporate tax planning. ERM is a holistic approach to managing an enterprise's entire portfolio of risks. We hand‐collect data on ERM adoption for a sample of Standard & Poor's 500 firms from 1993 to 2016. We empirically document that firms with ERM programs have lower cash effective tax rates than firms without ERM. Additionally, we find that the relation between ERM and tax avoidance is stronger among firms with more business segments. Finally, our results suggest ERM adoption offsets an increase in opacity and tax uncertainty typically associated with tax avoidance strategies. Overall, we provide evidence that ERM allows firms to exploit tax avoidance opportunities through enhanced coordination and communication.

Intelligent Financial Risk Warning for Enterprises Through Knowledge Graph-Based Deep Learning

The financial risk warning methods for enterprises have always been a practical concern. In digital society, the computational intelligence has brought more spirit to this demand. This paper first introduces the current situation of the development of Knowledge graph technology, describes the deep learning fusion method based on Knowledge graph, and expresses the feasibility of this study. Then, according to the requirements of Knowledge graph, it completes the method fusion of core data training and extraction, and completes the adaptive deep learning design for the Beautiful SCOP database, and establishes a STDE-FG financial risk early warning model. Through empirical analysis, the shortcomings of this model were identified, and a comparison of optimized and optimized results was completed. Two aspects of phenomenon can be found from experimental results. For one thing, the accuracy of the unoptimized STDE-FG early warning model has been improved by 37.5–55.3% compared to traditional prediction models, but the prediction value during legal person changes has a greater error than traditional prediction values. For another, the optimized STDE-FG early warning model has also improved its accuracy in predicting new investments and equity changes, with improvements of 17–32% and 16–28%, respectively, with significant changes. This model will have a positive impact on improving enterprise risk management capabilities and reducing financial risk costs.

Стратегічне управління ризиками на малих та середніх підприємствах в кризових умовах: концептуальна модель

This article seeks to explore the need to adapt enterprises risk management (ERM) to crisis environment, i.e., to the situation of martial law in Ukraine. To the best of the author’s knowledge, no ERM framework accounts for business operations in the situation of martial law (i.e. war environment). Organisational activities in hazardous, dynamic, and safety-oriented circumstances are researched in the area of high reliability theory. The paper presents the results of a preliminary literature review in these fields. As a result, the conceptual model "Enterprise Risk Management / High Reliability Theory" ("ERM/HRT") – which formulates the direction of the future research – was developed.

Financing risk formation paths for sustainable development of Chinese fishery enterprises: A configurational analysis based on panel data

Effectively preventing the financing risk of Chinese fishery enterprises is a common concern of the government and academia. Based on the “complex dynamic perspective”, this study constructs a configuration analysis framework of influencing factors and explores the coupling matching relationship between the antecedent conditions in the temporal dimension. This study revealed that (1) in recent years, fishery enterprises have exhibited five distinct paths contributing to the formation of financing risk. The identified paths encompass considerations related to growth, profitability, expansion, loss, and decline. These formation paths can be categorized into three models based on risk preference. High-grade financing risks are caused by the combination of risk-seeking behavior and operational failure. (2) The China‒U.S. trade war and the global pandemic caused by COVID-19 prompted the dominant paths to integrate into one turning point path, which caused a significant turning point in the core conditions that originally occupied the dominant position. (3) Before 2020, the financing risks of fishery enterprises exhibited multiple condition configurations and were affected by multiple trajectory coupling effects, similar to a “loosely coupled” system. The research conclusions of this study can help to deepen the understanding of the nature and mechanism of financing risk for fishery enterprises and promote the transformation and upgrading of the marine economy.

The spillover effects of U.S. uncertainties on the systemic tail risk of Chinese enterprises

This study examines the impact of U.S. uncertainties, as indicated by the Macroeconomic Uncertainty Index (MU), Financial Uncertainty Index (FU), and Economic Policy Uncertainty Index (EPU), on the systemic tail risk within Chinese enterprises. Our findings reveal a significant positive relationship between U.S. uncertainties and systemic tail risk of Chinese enterprises. Additionally, this relationship is mediated through two main transmission channels—investor sentiment and financing constraints.

Minimizing the consequences of credit risks for agricultural producers

The article presents the results related to minimizing the consequences of risks for agricultural producers. It is established that the credit risk of agricultural enterprises should be considered as the probability of loss not only of mortgaged property, but also of future income. Its components are: systemic risks — arising in the external environment of participants in the credit process; collateral risks — related to the probable loss of mortgaged property or a decrease in its value; production risks — leading to losses in production activities. It is proved that one of the means of reducing credit risks is credit insurance, which should be considered as a set of types of insurance aimed at reducing credit risk at the level of the borrower and the lender. At the level of an agricultural enterprise, crop insurance, animal insurance, life insurance of the borrower, liability insurance for non-repayment of loans can be used. At the lender level, such insurance concerns the risk of non-repayment of loans and the risk of loss of property by the mortgagee. It was found out that a number of risks that lead to high loss-making of agricultural enterprises have a significant impact on the process of crediting agricultural enterprises. In particular, the combination of systemic risks, most of all price, inflation, and government regulation risk, reinforced by the complexity of the formation of market structures, leads to price disparity between products produced in agriculture and products consumed by them. It is determined that agricultural enterprises are not able to generate stable cash receipts, and the lack of an effective mechanism for the sale of agricultural products also does not contribute to increasing the profitability of enterprises in the industry.

Evolutionary game analysis of violation regulation in the electricity market based on blockchain technology

Electricity market violations affect the overall operations of the electricity market. This paper explores the evolutionary stability strategies of electricity generation enterprises and electricity consumers under two modes: traditional regulation and blockchain regulation to analyze blockchain technology’s mechanism and conditions in solving electricity market violations. The experimental results indicate that the likelihood of consumers accepting electricity and the regulatory capacity of regulatory agencies play a crucial role in determining the violation approach adopted by electricity generation enterprises. Under traditional regulatory models, due to information asymmetry, regulatory agencies may not be able to detect violations promptly. Meanwhile, electricity consumers may choose to accept violations by power generation companies due to high appeal costs. Blockchain technology enables regulatory agencies to improve their regulatory capabilities by eliminating information asymmetry, reducing the cost of complaints from electricity consumers, thereby elevating the risk for enterprises engaging in market violations and optimizing the evolutionary game towards an optimum state.

Application of Artificial Intelligence Data Mining Algorithm in Enterprise Management Risk Assessment

For governmental and non-governmental enterprises to tackle risk management with conviction, enterprise management risk assessment (EMRA) is required. This work proposes a research methodology based on an AI-based data mining algorithm (MSVM+EFCNN) for evaluating enterprise-related risks. Initially, all the possible risk assessment indexes of the enterprise are established using a large variety of identification parameters. Then, the data mining algorithms are trained by considering the previous data for building an EMRA model. At last, the current conditions are analyzed using a cluster of risk indicators, and the risk index is identified via the EMRA model. The support vector machine is used for classification purposes, and the fuzzy-based convolutional neural network is enhanced with a genetic algorithm for creating the enterprise risk assessment. The results obtained after keen analysis and experimentation indicate that the data mining algorithms used in this work can evaluate the enterprise-related risks effectively.

Risk management practices and financial performance nexus: Evidence from MSMEs in Osun State, Nigeria

This study assessed the effect of enterprise risk management on the firm financial performance of Micro, Small and Medium-scale Enterprises in Osun state Nigeria. Precisely, the risk encountered, the adoption of risk management practices, the implementation of Enterprise Risk Management (ERM) practices, and the financial performance of micro, small and medium scale enterprises in Osun state Nigeria. Primary data was used for this study; a well-structured questionnaire was used to elicit data from 273 respondents. The study population consists of owners and managers of small and medium businesses in Osun state, Nigeria. Data were analyzed using descriptive analysis and was the inferential statistic used to test the hypotheses. The results showed that market (33.7%), strategic (57%), financial (46.9%), operational (34.2%), management (47.6%), and technological (45.4%) are risks prevalent to micro and small businesses, but most of the respondents disagreed that the relationship of their staff to the customer is poor. Risk acceptance with a mean score of (2.27 ± 1.21) is the most utilized risk management practice adopted by the MSMEs. The implementation of ERM practices shows that MSMEs more utilized setting of objectives (43.6%), risk identification (38.3%), risk assessment (36.2%), and control activities (31.2%) and the financial performance of the businesses was moderate (69.7%). The correlation analysis shows no significant relationship between the scale of business and the adoption of risk management practices. Also, the regression analysis shows that Risk identification (? = 0.388, p ?0.01) and Control activities (? = 1.096, p ?0.01) are the only ERM variables that significantly affect financial performance. The study concluded that the implementation of enterprise risk management practices has a significant effect on the financial performance of Micro, Small and Medium enterprises in Osun State, Nigeria.