Enterprise Risk Assessment Research Articles

Asset risk assessment and management of large-scale electricity enterprises under the concept of financial sharing

The power grid is an important industry that is crucial to national security and economic development, and its importance in society continues to grow. As an emerging concept, financial sharing enables internal resource sharing and optimization, thereby improving the efficiency and effectiveness of asset management. This study investigates and analyzes the current situation of asset management in large-scale electricity enterprises in X Province, China, and proposes a comprehensive asset management strategy optimization plan based on the concept of financial sharing. The proposed plan integrates management models such as PDCA and designs an entire information management architecture to enhance resource utilization efficiency, reduce environmental pollution risks, and optimize asset allocation and operational decisions. In addition, it also utilizes the status of assets to assess the risks associated with fixed assets in the power grid. The results indicate that the asset risk assessment method under the concept of financial sharing can reduce power grid asset losses, effectively enhance the competitiveness and sustainable development capabilities of electricity enterprises.

A Multi-Level Deep Neural Network-Based Tourism Supply Chain Risk Management Study

With the rapid advancement of the tourism, the capital demand of tourism enterprises has gradually risen, but the confusion of market management has increased the difficulty of risk assessment of tourism enterprises by financial institutions, which has led to difficulties in financing tourism enterprises and seriously hindered their development. On this basis, this research first analyses the risk structure of the tourism supply chain (TSC) from the financial aspect and establishes a relevant risk assessment system. After confirming the assessment indexes, the data is dativized and normalized, and finally a multi-level deep neural network (DNN) is used to construct a TSC risk prediction model to calculate the transformed indexes and assess the risk degree of the enterprise according to the results. The experimental results indicate that the model has the best performance when the H-Net hidden layer is 3 layers and the L-Net hidden layer is 4 layers, and its accuracy reaches 93.35%, sensitivity reaches 84.13%, convergence starts at 25 iterations, the final loss value is only 0.8, and the predicted and the real value error is within 2.5%. Therefore, the multi-level DNN model constructed in this experiment has certain application value in TSC risk management.

A Prediction Model for Credit Risk Measurement of Small and Micro Enterprises Based On Particle Swarm Optimization random forest algorithm

In the context of rapid economic development, the credit risk assessment of small and micro enterprises has become the focus of attention in the financial field. The random forest algorithm is widely used in credit risk assessment due to its high accuracy and robustness, but it has some problems, such as difficulty in parameter selection and performance degradation in processing unbalanced datasets. In this study, we propose a credit risk prediction model for small and micro enterprises based on Particle Swarm Optimization Random Forest Algorithm (PSO-RF). The particle swarm optimization effectively solves the problem of random forest parameter selection and improves the prediction performance of the model through the balance of global search and local search. Experimental results show that the PSO-RF algorithm shows significant performance advantages in credit risk prediction, performs well in dealing with unbalanced datasets, and has certain advantages in feature selection. This study provides new ideas and methods for the credit risk assessment of small and micro enterprises, and is of great significance for improving the risk management capabilities of financial institutions and supporting the healthy development of small and micro enterprises.

Truck Driving Assessment for Chinese Logistics and Transportation Companies Based on a Safety Climate Test System

By applying the “safety atmosphere” measurement theory to Chinese management companies engaged in road transportation, a corporate and individual safety risk assessment system was established that is consistent with the management and cultural climate in China, thereby reducing the driving safety risk of truck drivers. The system realizes the safety risk assessment of enterprises, fleets and individuals in the form of test scales by constructing a structural model of the enterprise safety atmosphere, including the management, communication, and supervision of enterprises, fleets, and individuals. The safety climate was modeled using a two-level framework, at the organizational level and fleet level, and three dimensions of test items for each level were obtained by exploratory factor analysis. The three dimensions of safety management, safety supervision, and safety priority at the organizational level, and the three dimensions of positive communication, safety awareness, and self-discipline at the fleet level, respectively, passed a valid factorial test (p < 0.01). Finally, the validity of the system evaluation results was verified by relying on the actual in-vehicle monitoring data and accident records of the corporate transportation fleet. The results show that the total test scores at the organizational level and the fleet level are significantly correlated with their driving risk behaviors, and both are linearly and negatively correlated with the number of accidents per thousand kilometers. This indicates a high degree of consistency between the system’s test results and actual risky accidents.

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.

Enterprise Management and Risk Assessment Analysis Practice

Finance is the core competitiveness of the country. Since the reform and opening up, China's financial industry has developed rapidly and made historic achievements, but there are still many contradictions and problems that make it difficult to meet the requirements of high-quality economic development. First, the debt problem: China's enterprises, local governments and household sectors are all facing considerable debt pressure. Some enterprises and local governments have hidden debts, and the debt of the household sector is also increasing. This poses a risk to the stability of the financial system.Second, financial institution risk: Some financial institutions have risks, including credit risk and liquidity risk. Some non-bank financial institutions have relatively low capital adequacy ratios and are potentially at risk of default.Third, financial chaos: some financial chaos problems still exist, such as illegal fund-raising, online financial fraud and so on. These issues challenge the effectiveness of financial regulation and public trust in the financial system.Fourth, structural problems in the financial system: there are some structural problems in China's financial system, such as insufficient interaction between the banking sector and the capital market, and relatively low efficiency of financial resource allocation. These problems constrain the development of the financial system and sustainable economic growth.

Security and Risk Control of Enterprise Supply Chain Finance in the Context of Digital Economy

Abstract The widespread application of new-generation information technologies, such as the Internet of Things (IoT), has brought about significant changes in the operating environments of enterprises and the supply chains in which they operate. At the same time, enterprises aim to maximize profits while minimizing enterprise risks. This paper examines the risk assessment of enterprises in supply chain finance based on the relevant literature review. First of all, after combing and defining the relevant applications of digital technology in enterprise risk prevention and control, a Logistic enterprise risk assessment model under supply chain finance is constructed, and the parameters of the model are optimally selected and estimated for testing. The main factors affecting enterprise risk are analyzed from four dimensions: enterprise, core enterprise, financing asset risk and supply chain-related aspects, and a set of index systems suitable for enterprise risk assessment under supply chain finance is established by using correlation analysis, RF and Lasso regression methods. x3, x4, x5, x6, x7, x9 and x15 are negatively correlated with the enterprise risk, and the gross profit margin and the top five customers’ gross profit margin are negatively correlated with the enterprise risk, while sales and profit margin are negatively correlated with the top five customers’ gross profit margin. The correlation between enterprise credit risk and gross margin and the proportion of sales revenue from the top five customers is positive. The accuracy of prediction of the evaluation model is 93.3%. It can be seen that the proposed logistic assessment model is reasonable and effective, and can be practically applied in the security and risk control of enterprise supply chain finance.

Investigation of the Application of Machine Learning Algorithms in Credit Risk Assessment of Medium and Micro Enterprises

Investigation of the Application of Machine Learning Algorithms in Credit Risk Assessment of Medium and Micro Enterprises

Financial Risk Assessment of Environmental Protection Enterprises under the Background of Carbon Peak and Carbon Neutrality

Financial Risk Assessment of Environmental Protection Enterprises under the Background of Carbon Peak and Carbon Neutrality

Building Financial Enterprise Risk Assessment System Based on Big Data and Integrated Learning Technology

Building Financial Enterprise Risk Assessment System Based on Big Data and Integrated Learning Technology

Concrete Concept of Business English

Usually, business English mainly refers to the product of the combination of business and English. This subject includes the language application knowledge in all the aspect of business world in order to make sure the smooth going of all parts of business operation. Not only English language knowledge is needed, but also all the knowledge and abilities related to the business. The establishment of this risk assessment system solves the previous risk assessment of enterprises by Banks, which is mainly based on qualitative analysis and less on quantitative analysis, thus leading to the insufficiency of its relatively one-sided judgment standard. From the comprehensive strength and credibility of the two aspects of the study, extract five risk indicators to establish a risk assessment system. Among them, total input price and tax, total output price and tax, and profit rate are the evaluation criteria for the comprehensive strength of an enterprise. These indicators can analyze the production, sales and operation capacity, profitability and production and operation stability of an enterprise to reflect the comprehensive strength of the enterprise. The failure rate of the input transaction and the failure rate of the sales transaction are the evaluation standards of the enterprise's reputation. Such indexes can analyze the production management aspects such as the purchase planning of the enterprise's goods and the production quality management, to reflect the credibility of the enterprise. Therefore, the selection of these two aspects for analysis can fully evaluate the enterprise's credit risk.

STRENGTHENING ECONOMIC SECURITY OF ENTERPRISES THROUGH STRATEGIC RISK MANAGEMENT IN UNCERTAINSY

The priorities of the strategic management of the enterprise's economic security by ensuring sustainable economic development and reducing the ecological burden on the environment in the context of the current state of Ukraine's economy are considered. Economic and socio-political factors are analyzed, highlighting the basic principles that lead to crisis situations. It is proposed to constantly monitor and analyse risks, which is an essential and timely mechanism of anti-crisis management. The complex and protracted nature of the enterprise's risk system requires appropriate tools for their identification and assessment, which considers the need to review the strategic directions of diagnosis and analysis of relevant information for management decision-making. Particularly relevant in our publication is the development of approaches to the comprehensive assessment of the risks of the existence and effective operation of enterprises that are adequate to modern socio-economic requirements.
 A wide range of economic risks arising in the process of economic activity was analyzed, and measures were developed to reduce their impact on the performance indicators of the enterprise. An analysis of the existing risks was carried out, among which the following were highlighted: market risks, risks of an unstable situation in the country, a change in the competitive environment, force majeure situations at the enterprise, reputational and environmental risks, and an increase in resource prices. Methods of enterprise risk management to minimize or neutralize their negative impact, actions, and measures that make it possible to prevent the impact of risks on enterprise activity are proposed. In today's conditions of instability, the company is offered to develop a set of strategic measures and principles that must be followed for production and economic activity to be effective. Economic security strategy should be focused on overcoming the risks caused by military aggression and equalizing economic advantages, namely, finding centres of growth and managing access to global markets with the help of responsible investments in Ukraine's economy. The above measures are recommended for implementation in the company's strategy, which will optimize the structure and management process and contribute to the growth of the value of organizations. Ignoring IDE principles entails significant reputational risks for organizations and lost opportunities to engage partners and team members focused on sustainable development. The conducted research creates the basis for further improvement of the enterprise risk assessment methodology and its implementation in the management system of actual risks when enterprises carry out their economic activities within the framework of a preventive approach.

Credit Risk Assessment of Heavy-Polluting Enterprises: A Wide-ℓp Penalty and Deep Learning Approach

Effective credit risk assessment of heavy-polluting enterprises can achieve a balance between environmental and economic benefits. It requires the consideration of risk indicators for both the carbon information dimension and the compliance dimension. However, as the feature dimensions of the model continue to increase, so does the irrelevant feature or noise. Therefore, we investigate the use of non-integers for regularization from high-dimensional data under the conditions of a large number of irrelevant features. In this paper, a novel Wide-ℓp Penalty and Deep Learning (WPDL) method for credit risk assessment is proposed, which could provide a sparse solution. The Wide-ℓp Penalty component allows feature selection using a linear model with an ℓp Penalty regularization mechanism, where 0 < p ≤ 2. The deep component is a DNN that can generalize indicator features from the credit risk data. The experimental results show that the minimum prediction error occurs at a non-integer ℓp Penalty. Furthermore, the WPDL outperforms other models such as KNN, DT, RF, SVM, MLP, DNN, Gradient Boosting, and Bagging.

The Application of Big Data and Artificial Intelligence Technology in Enterprise Information Security Management and Risk Assessment

With the development of digitalization and Internet technology, enterprise information security is facing more and more challenges. Many enterprises have begun to adopt big data (BD) and artificial intelligence (AI) technology for risk assessment (RA) and prediction to effectively manage information security risks. This article discusses the application of BD and AI technology in enterprise information security management (ISM) and RA from two aspects. Firstly, the mobile payment signature scheme based on number theory research unit is used to improve the security of the mobile payment system. This scheme uses lattice algorithms to achieve fast key generation, signing, and verification and can resist traditional cryptographic attacks. Secondly, a set of enterprise ISM and RA system is established, including risk identification, RA, monitoring and early warning, emergency response, and other links. BD and AI technology is used to analyze internal and external data to provide accurate RA results to achieve automated RA.

Credit Risk Assessment of Small, Medium and Micro Enterprises Based on The Improved Logical Regression Model of Gradient Descent Method

Due to the weak strength of small, medium and micro enterprises, banks need to judge the credit risk of the enterprise based on the company's past credit history and the company's invoice information, etc., and then establish a reasonable and effective quantitative credit risk model.First, through the analysis and preprocessing of the data, this paper extracts six indicators such as marketing profit margin and invoice invalidation rate, and comprehensively evaluates the credit risk of the enterprise from the three aspects of enterprise scale, supply and demand stability, and credibility, and establishes a corporate credit risk evaluation system. Then, a logical regression model is constructed to predict the probability of compliance of the enterprise, a loss function is formulated to describe the deviation between the prediction result and the classification result, and a stochastic gradient descent algorithm is used to obtain the optimal parameter value. Finally, the optimized logical regression model is applied to the credit risk assessment of 123 companies. The results show that the stronger the company's strength, the more stable the supply and demand relationship, and the higher the reputation level, the less likely its credit default risk is.

Research on the Infrastructure Development Risk Assessment and Response Mechanism of Chinese Enterprises' Overseas Investment Under the Background of Big Data Technology

Research on the Infrastructure Development Risk Assessment and Response Mechanism of Chinese Enterprises' Overseas Investment Under the Background of Big Data Technology

Application of Big Data Technology in Enterprise Information Security Management and Risk Assessment

Nowadays, the application of enterprise management information has been deeply rooted in daily business activities, and the management risk of enterprise information security (EIS) has also increased. The use of advanced means to provide security protection for it has become the top priority. To optimize the EIS management system, and carry on the risk assessment (RA), firstly, this study analyzes the current situation of the enterprise's internal information management and summarizes the shortcomings and security risks faced by the system. In the era of big data (BD), the security risks of database information systems show a diversified trend. Secondly, to explore the application of BD technology in EIS management, the characteristics of this technology and security control measures for risks are summarized to strengthen the enterprise's information management innovation and implement the application of data security technology.

Risk Assessment of Water Transport Enterprises by Modeling Direct and Indirect Threats

Introduction. The methods of traffic modeling by water transport and assessing the risks associated with it is needed to identify the issues of the past period, proposing methods for assessing not only direct but also indirect risks to form the preconditions for preventing them in the postwar reconstruction. The coordination of different transport type’s actions of transport requires an assessment of risks impact of the previous stages of mixed transportation on the formation of the following risks’ stages. Existing methods of assessing such impact need to be improved.
 Aim and tasks. The aim of this study is creation of methodological approach to risk management in water transport based on a mathematical model for assessing the impact of both direct and indirect risks. The tasks are: to prove that the additive approach of taking risks into account leads to the systematic deviation appearance from the result; take into account the impact on the risk of cargo transportation.
 Results. It has proved that the calculation of risk as an additive function leads to a systematic deviation from the relevant result. It stated that the risk of each of the next stages of transportation depends on the risks of the previous stages. To increase risk analysis relevance in water transport, the use of an oriented graph in a multidimensional parameter space proposed. It stated that in order to calculate the integrated risk, it is essential building not only the risk matrix but also the risk incidence matrix to take into account their relation to business entities. It established the impact of even minor risks could take the form of a catastrophe, which leads to cargo flows reorientation. It established that: for calculation of integral risk, it is crucial consider direct and indirect influences of risks; risk calculation for water transport also requires risk analysis in related modes of transport.
 Conclusions. It was established that, when calculating integral risk, it is necessary to consider direct and indirect influences on risks and that the risk calculation for water transport also requires risk analysis in related modes of transport. The proposed approach significantly increases the relevance of water transport risk analysis and allows for managing changes in transportation routes in real time.

Ways of improving the efficiency of risk management in the context of integrated risk assessment of electricity industry enterprises

Methods. The theoretical and methodological basis of the research is the work of domestic and foreign scientists. The results were obtained due to the application of a system of methods: the method of logical analysis made it possible to develop the logic of the research; deductions – to identify individual factors affecting the risk level of the enterprise; generalization and synthesis – for the formation of a scientific approach to the integral risk assessment of electric power enterprises. The graphic method made it possible to visualize the obtained research results. Results. Domestic enterprises need the formation of approaches to risk management, which will allow them to ensure proper development and competitiveness. The article substantiates various approaches to risk grouping for electric power enterprises. The most important risks, according to the representatives of the electric power sector, are defined, among which the main ones are regulatory, operational and market risks. The authors prove that market risks in the electric power industry have a specific nature and are inherent only to national markets where there are competitive electricity trades. An approach to the integrated risk assessment of an electric power company has been developed, which is based on: calculation of financial and economic indicators of the company's activity; comparing them with normative values, assigning point values to the calculated coefficients; calculation of intra-group point values of coefficients of the financial and economic condition and calculation of the integral risk indicator of the enterprise's activity. Approbation of the scientific and methodical approach was carried out for the Khmelnytskyi electric power company and it was identified by the level of risk. Novelty. There is substantiated the scientific and methodological approach to the integrated risk assessment of enterprises as a tool for increasing the efficiency of risk management of enterprises in the electric power industry. Practical value consists in the possibility of applying the developed scientific and methodical approach to the integrated assessment of risk by enterprises of various industries. The obtained results allow domestic enterprises to participate in risk management processes and at the same time ensure competitive advantages in the relevant markets.

Effects of the host-country institutional environment on the operation mode change of international construction enterprises

PurposeThe operation mode of enterprises will affect its resource commitment in the host country, involving different costs and time, as well as risks. Yet, the current state of knowledge about how the institutional environment affects the operation mode change of international construction enterprises is equivocal. This study aims to explore the impact of a host country's institutional environment on the operation mode change of international construction enterprises.Design/methodology/approachFirst, this study proposes a model on the impact of the institutional environment on the operation mode change of international construction enterprises. Second, this study used the Worldwide Governance Indicators (WGI) published by the World Bank and a questionnaire survey to collect data. Finally, the study employs a multiple regression methodology to test the hypothesis and discusses the results.FindingsResults highlight that the important impact of the institutional environment on the operation mode change of international construction enterprises. The results showed that enterprises are more willing to increase resource commitments under the condition of stable institutional environment. In addition, enterprises' market-specific experience and general international experience, as moderating variables, weaken the impact of the institutional environment on the operation mode change. However, general international experience has no significant moderating effect.Practical implicationsThe findings of this study provide practical implications for the investment risk assessment of international construction enterprises. Enterprises need to consider the change in institutional quality and institutional instability of the host country, as well as their own international experience when changing operation mode.Originality/valueThis study extends internationalization theory to the international construction field and provided theoretical guidance for the mechanism of operation mode change of international construction enterprises.