Financial Risk Prevention Research Articles

Unveiling the role of city commercial banks in influencing land financialization: Evidence from China

Local financial development is crucial for advancing regional financial supply side structural reform, enabling local governments to leverage financial instruments to effectively mobilize land resources and foster competitive growth. The introduction of numerous financial products linked to land-related rights and interests has resulted in a pronounced transmission and interconnection of fiscal and financial risks across regions. This study examines the impact of local financial development on land financialization in China using panel data from prefecture-level cities and detailed information on land mortgages. The findings indicate that the establishment of city commercial banks (CCBs) contributes to the progress of land financialization by incentivizing local government financing vehicles to participate in land mortgage financing, increasing the transfer of debt risks to the financial sector. Notably, the impact of CCBs on land financialization is more pronounced in regions with urban agglomeration, high GDP manipulation, inadequate local financial regulation, and robust implicit government guarantees. Further analysis reveals that CCB establishment has negative spillover effects on land financialization in neighboring areas, while expansion strategies such as establishing intercity branches, engaging in cross-regional mergers, and relaxing regulations have mitigated the rise of land financialization at the regional level. This study provides policy recommendations that focus on reducing local governments’ reliance on land financing and enhancing the prevention and management of financial risks.

Financial risk prevention and corporate green innovation: A quasi-natural experiment based on the new asset management regulation

In the context of economic globalization in the 21st century, financial risk prevention and corporate green innovation development have emerged as two indispensable themes in global economic growth. This paper selects Chinese A-share listed companies from 2010 to 2021 as a research sample and uses the introduction of the New Asset Management Regulation as a quasi-natural experiment. Employing a generalized difference-in-differences model, this paper identifies the causal relationship between financial risk prevention and corporate green innovation and assesses the policy effects of financial risk prevention. The results show that financial risk prevention significantly enhances the green innovation activities of companies with a high degree of financialization by constraining investments in financial assets and mitigating management's myopic tendencies. Heterogeneity tests reveal that the promotion effect is primarily evident in the service sector, regulated industries, state-owned enterprises, and regions with a higher level of shadow banking development. The findings reveal the value of financial risk prevention at the micro-level of corporate green innovation and provide useful policy implications for guiding finance to effectively serve the real economy.

Assessment of regional financial risk based on an integrated approach

Subject. The article considers a comprehensive model to assess the financial risk of the region. Objectives. The aim is to develop a financial risk prevention model that integrates economic, social, political, environmental, and financial indicators, having a significant impact on the economy. Methods. The study rests on methods of synthesis, analysis, comparison, and economic and mathematical calculations, i.e. weighted summation with preliminary normalization of each estimated indicator. The process of data collection, normalization, selection of indicator weights, and calculation of integral indicator of financial risk was implemented for 2022. Results. We established the presence of financial risks in the region. Both the results and the model itself can be useful for further research. The advantage of the model is the relative small number of applied indicators. This facilitates the collection of information, its processing and evaluation. The evaluation of the above calculations reflects the conditionality of ranking. The results that reflect dynamics are more indicative. Conclusions. The formed model, when assessing regional financial risk, enables to take into account the multidimensionality of modern regional economies.

Financial Risk Prevention Strategies from the Perspective of Financial Accounting

Financial risks pose challenges to the stability of capital markets and the financial health of enterprises. From the perspective of financial accounting, identifying and managing these risks is crucial for promoting long-term economic development and maintaining the continuity of enterprise operations. This paper first elaborates on the concepts of financial accounting and financial risk, analyzes the manifestations of financial risk, and explores the importance of preventing financial risk. Finally, the paper studies the financial risk prevention strategies from the perspective of financial accounting. It is hoped that the discussion in this article can provide some reference and assistance for the sustainable and stable development of enterprises.

The Impact of Climate Change Factors on Financial Markets: Evidence from China

ABSTRACT This paper examines the impact of climate change factors, namely Climate Risk Index (CRI), Climate Policy Index (CPI), and Climate Concern Index (CCI), on China’s financial markets. By employing quantile vector autoregression model and conducting network analysis, this paper intends to reveal the dynamic relationship and the risk transmission mechanism between climate factors and various financial markets under different market conditions based on the data ranging from Nov.1, 2011 to December 31, 2021. We find that climate shocks intensify the risk contagion among China’s financial markets, and the impact induced by each factor would present heterogeneity. The results also indicate that the systemic importance of climate shock index varies across market conditions. The findings shed light on the complex interaction between climate shocks and financial markets, which should contribute to policy implications for financial market stability and risk prevention.

Study on the Causes and Countermeasures of Enterprise Financial Risk

In the environment of fierce competition, the financial security of enterprises becomes extremely important. Enterprise financial security is a key issue in enterprise operation, which directly affects the survival and development of an enterprise. Therefore, enterprises should always pay attention to their financial situation, improve risk awareness, and establish a sound financial risk prevention system. Business management should take appropriate action to respond to changing domestic and international trends. This paper analyzes the financial risk of the company, and studies preventive measures according to the analysis results to reduce the financial risk of the company and improve the market competitiveness of the company in the challenging competitive environment, so as to provide guarantee for the sustainable development of the company.

Based on Financial Accounting Perspective Analysis of Financial Risk Prevention Strategy

<div>In recent years, the development of financial market in our country is very rapid, and has got remarkable achievements. Along with</div><div>the sustainable development of our economy, our country’s financial industry has also got great development. While the rapid development</div><div>of China’s financial industry, some problems have also emerged, which have had a serious impact on China’s economic development and fi</div><div>nancial market order. Therefore, we must strengthen the guard against financial risks to ensure the normal operation of financial markets. This</div><div>article starts from the financial accounting Angle, analyzes and discusses the existing problems in China’s financial risk prevention, and pro</div><div>poses corresponding measures to ensure the stable operation of the financial market in our country.</div>

Quantum Temporal Winds: Turbulence in Financial Markets

This paper leverages turbulence theory from physics to examine the similarities and differences between financial market volatility and turbulent phenomena on a statistical physics level. By drawing analogies between the dynamics of financial markets and fluid turbulence, an innovative analytical framework has been developed to enhance our understanding of the complexity inherent in financial markets. The research methodology involves a comparative analysis of several national stock market indices and simulated turbulent velocity time series, with a particular focus on key statistical properties such as probability distributions, correlation structures, and power spectral densities. Furthermore, a financial market capital flow model has been established, and corresponding solutions have been proposed. Through computational simulations and data analysis, it was discovered that financial market volatility shares some statistical characteristics with turbulence, yet there are significant differences in the shape of probability distributions and the timescales of correlations. This indicates that although financial markets exhibit patterns similar to turbulence, as a multivariate-driven complex system, their behavioral patterns do not completely correspond to natural turbulence phenomena, highlighting the limitations of directly applying turbulence theory to financial market analysis. Additionally, the study explores the use of Bézier curves to simulate market volatility and, based on these analyses, formulates trading strategies that demonstrate practical applications in risk management. This research provides fresh perspectives for the fields of financial market theory and econophysics, offering new insights into the complexity of financial markets and the prevention and management of financial risks.

Strengthen Financial Risk Prevention and Control Capabilities and Improve the Quality and Efficiency of Financial Supervision

The book Research on the Formation and Prevention of Systemic Risks in the Banking Industry from the Perspective of Platform Finance combines the complex network characteristics of the real banking industry and brings the two relatively independent financial markets of platform finance and banking industry into the same complex network framework. The analysis breaks through the traditional systemic risk research paradigm, fills the shortcomings of traditional economic methods in analyzing the internal structure of the system, provides a new way to study the topological structure characteristics of bank networks, and broadens the perspective of systemic risk research.

Research on the Identification of Rural Revitalization Potential and Precise Financial Support in Poverty-Stricken Areas

Research on the Identification of Rural Revitalization Potential and Precise Financial Support in Poverty-Stricken Areas

Variational Neural Network Optimized with Lyrebird Optimization Algorithm for Analysis and Empirical Evidence of Using Data Mining in Financial Risk Prevention Research

In the contemporary landscape of global finance, the effective prevention and mitigation of financial risks have become pivotal for the stability, resilience, and sustainable growth of financial institutions and markets. As financial instruments and markets continue to evolve in complexity, the need for a thorough analysis of risk prevention strategies has become increasingly apparent. In this manuscript, Variational Neural Network (VNN) optimized with lyrebird optimization algorithm (VNN-LOA) is proposed. Initially data is taken from machinehack-financial risk prediction. Afterward the data is fed to Adaptive Variational Bayesian Filter (VBF) based pre-processing process. The pre-processing output is provided to the Variational Neural Network (VNN) to effectively classify financial risk prevention as either involving risk or no risk. The learnable parameters of the VNN are optimized using lyrebird optimization algorithm (LOA). The proposed method is implemented in MATLAB and the efficiency of the proposed method DM-FRP-VNN-COA is estimated with the help of several performances evaluating metrics like, accuracy, precision, recall, f1-score, sensitivity, specificity, computational time, and ROC are analyzed. The proposed DM-FRP-VNN-LOA method attains 38.88%, 35.75%, and 33.16% higher accuracy for risk classification; 34.31%, 38.47% and 37.23% higher accuracy for no risk classification; 22.63%, 33.27% and 21.49% high precision for risk classification; 22.63%, 33.27% and 21.49% high precision for no risk; 35.136%, 39.04% and 38.81% lower computation Time compared with the existing method like data mining using financial risk prevention based back propagation neural network (DM-FRP-BPNN), data mining using financial risk prevention based machine learning (DM-FRP-ML), and data mining using financial risk prevention based convolutional neural network (DM-FRP-CNN) respectively.

Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model

Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model

Blockchain technology concerns and corporate financial risk prevention—A quasi-natural experiment for Chinese listed A-share companies

The rapid development of blockchain technology (BT) has gained widespread attention from all sectors of society. In order to remain competitive, enterprises have responded positively to this research and development, which is conducive to the enhancement of their own digital construction. BT can provide technical support for companies to strengthen their internal management and reduce business risks caused by information asymmetry. However, the ability to reduce enterprise financial risk effectively depends on the breadth and depth of BT concerns. This study constructs word-frequency statistical variables of BT concerns based on the annual report data of listed companies. It conducts an empirical study on the issue of BT concerns affecting corporate financial risk prevention and regulation based on a propensity score matching difference-in-difference model. The results show that: (1) Attention to BT significantly reduces corporate financial risk (2) In terms of the mechanism effect, Attention to BT can significantly reduce corporate financial risk by optimizing accounts receivable management, enhancing debt servicing ability, and improving corporate performance. (3) The heterogeneity analysis shows that the concern of BT in reducing financial risk is even more significant for enterprises whose social responsibility is not effectively regulated and for hybrid enterprises. This study enriches the literature on the mechanism of BT to enterprise financial risk and provides a reference for both enterprise-level blockchain concerns and strengthening enterprise financial risk management.

Commercial Bank Loan Risk and Prevention

Under the environment of China's market economy, the healthy and stable development of commercial banks is an important guarantee for the healthy operation of the social and economic system. As an important part of the financial management system, credit management of commercial banks is not only related to the sound development of commercial banks, but also has a direct impact on the stability of the whole society. At the same time, risk factors in financial activities are always following, and if there is no reasonable avoidance and prevention of financial risks, it will affect and threaten the survival of financial institutions. In such a situation, commercial banks should attach great importance to the prevention and control of loan risks, establish reasonable control strategies based on the actual situation, optimize the risk management system, continuously improve the level of risk management and control, ensure that the healthy operation of the financial system has good depth and breadth, and lay a solid foundation for the sustainable development of commercial banks. This paper discusses the risk and prevention of commercial bank loans from the aspects of the concept and characteristics of commercial bank loan risk, the current problems in the risk management and control of commercial bank loans, and the countermeasures to the risk management and control of commercial bank loans, so as to provide reference for promoting the healthy development of the financial industry and standardizing the management of financial enterprises.

Economic policy uncertainty on stock market risk contagion: a network-based approach

It is necessary to study the relationship between the dynamical uncertainty and risk contagion in the financial market. In this paper, we use the Economic Policy Uncertainty (EPU) Index, calculate the stock index volatility of the top seven global economies in 2021, then construct a risk spillover network. For the sub-sample analysis, we select three different types of global crises to study the transmission direction and intensity within the risk network across each time period. The results show that firstly, EPU has both direct and indirect effects on risk contagion in cross-country stock markets. It mainly plays an intermediary role. Secondly, in the risk network, the intensity and structure are time-varying, no single country serves as the exclusive issuer or recipient of risk spillovers. Thirdly, the speed and impact of shocks from public health security crises are much greater. In light of the findings above, investors and policymakers in different countries are expected to strengthen cooperation in financial risk prevention and enhance risk early warning. And we provide new evidence to emphasize attention to shocks caused by public health events, aiming to prevent the recurrence of large cross-border financial risks.

STRUCTURE AND MEASUREMENT OF UNIVERSITY FINANCIAL RISK

Since the 1990s, higher education in China has expanded significantly. In 2020, the gross enrollment rate will reach 54.4%, and the total number of students in higher education accounts for one-fifth of the total scale of higher education in the world, ranking first in the world in terms of scale. The scale of higher education in China has grown, and the continuous increase in investment in higher education funds has increased the difficulty of controlling financial risks. Strengthening the prevention and control of financial risks in colleges and universities and strengthening the construction of internal control will be of great significance to the healthy development of universities. To understand the sources and causes of financial risks in universities, this study interviews the financial staff of S University and constructed a structural map of financial risks in universities using the grounded theory method to obtain data. The researchers compiled a questionnaire to study the financial risk of universities, distributed and received back 308 questionnaires at S University. By analyzing the survey data, the constructed structure of the financial risks of the university was verified.

Financial Risk Evaluation and Prevention and Control Methods of Listed Companies in China's Electric Power Industry

With China's economy entering the stage of rapid development, the competition of listed companies in the electric power industry belonging to the national economy is also very fierce, and it is easy to appear many problems related to financial risks. Through the research on the current situation of financial risk of listed companies in the power industry, this paper has an in-depth understanding of the types of corporate financial risk and the ways of evaluation, and discusses the ways of preventing financial risk combined with the concrete practice, so as to provide some feasible suggestions for promoting the further development of listed companies in the power industry. The types of financial risks are very complex, and enterprise managers need to make accurate decisions on the long-term development of the company according to the actual situation, so as to help the normal operation of the financial market and promote the progress of society.

Internet financial innovation and financial risk prevention

With the rapid development of e-commerce, the application of Internet technology has promoted the circulation of commodities and domestic consumption. However, with the development of Internet finance, there are also many unforeseen risks that traditional finance can not foresee. Therefore, at the same time of development, it is necessary to do a good job of regulation and prevention to ensure the healthy development of Internet finance. We must carefully sort out the impact of Internet finance on Chinese enterprises and the impact of traditional models, learn from the advanced concepts and models of Internet finance, constantly innovate and develop, improve business competitiveness, and consolidate our competitive position. This paper introduces the related concepts of Internet finance, analyzes the innovation bottleneck of Internet finance, and finally studies the countermeasures to solve the innovation bottleneck of Internet finance.

Modeling of extended osprey optimization algorithm with Bayesian neural network: An application on Fintech to predict financial crisis

<abstract> <p>Accurately predicting and anticipating financial crises becomes of paramount importance in the rapidly evolving landscape of financial technology (Fintech). There is an increasing reliance on predictive modeling and advanced analytics techniques to predict possible crises and alleviate the effects of Fintech innovations reshaping traditional financial paradigms. Financial experts and academics are focusing more on financial risk prevention and control tools based on state-of-the-art technology such as machine learning (ML), big data, and neural networks (NN). Researchers aim to prioritize and identify the most informative variables for accurate prediction models by leveraging the abilities of deep learning and feature selection (FS) techniques. This combination of techniques allows the extraction of relationships and nuanced patterns from complex financial datasets, empowering predictive models to discern subtle signals indicative of potential crises. This study developed an extended osprey optimization algorithm with a Bayesian NN to predict financial crisis (EOOABNN-PFC) technique. The EOOABNN-PFC technique uses metaheuristics and the Bayesian model to predict the presence of a financial crisis. In preprocessing, the EOOABNN-PFC technique uses a min-max scalar to scale the input data into a valid format. Besides, the EOOABNN-PFC technique applies the EOOA-based feature subset selection approach to elect the optimal feature subset, and the prediction of the financial crisis is performed using the BNN classifier. Lastly, the optimal parameter selection of the BNN model is carried out using a multi-verse optimizer (MVO). The simulation process identified that the EOOABNN-PFC technique reaches superior accuracy outcomes of 95.00% and 95.87% compared with other existing approaches under the German Credit and Australian Credit datasets.</p> </abstract>

Construction and Evaluation of Credit Risk Early Warning Indicator System of Internet Financial Enterprises Based On AI and Knowledge Graph Theory

Through in-depth analysis of credit risk in the context of the development of Internet finance, the study recognized that its diversification and complexity not only include financial risks, but also involve the impact of non-financial factors. Based on this, combined with ESG factors, principal component analysis and grey correlation method are used to optimize the indicators, ensuring the comprehensiveness and accuracy of the indicator system. Using Convolutional Neural Network (CNN) as the warning model, considering the dynamic and static characteristics of data, a sub convolutional network was designed for training different types of data. At the same time, the credit rating division and warning threshold selection methods were optimized, improving the accuracy and practicality of the model. Through experimental verification, we found that the CNN model has a high accuracy in credit risk warning, and it also shows excellent classification performance and comprehensive effect compared to other models. Through systematic research and application, this paper provides a complete solution for the credit risk management of Internet financial enterprises, and makes positive contributions to the stability of the financial system and risk prevention. At the same time, we also emphasize the important role of technological innovation in financial intelligent management, especially the application of innovation systems centered on AI and knowledge graphs in the field of credit management, which points out the direction for the future development of the financial industry.