Credit and Financial Risk Measurement of Financial Enterprises Based on PSM Model

2021 ◽  
Vol 7 (5) ◽  
pp. 3710-3723
Author(s):  
Yijun Chen ◽  
Xiao Yan ◽  
Qiuhong Jia
Keyword(s):  
Financial Risk ◽  
Rapid Development ◽  
Social Economy ◽  
Risk Measurement ◽  
Financial Risks ◽  
Financial Industry ◽  
Corporate Credit ◽  
Enterprise Credit ◽  
Fuzzy Neural ◽  
Default Rate

With the rapid development of social economy and information technology, the credit risk and financial risk of my country’s financial enterprises are also facing severe challenges. In financial enterprises, credit is related to the survival of the enterprise. As the business volume and scale of financial enterprises continue to expand, financial risks are correspondingly increased. Therefore, the research on financial enterprise credit and financial risks is of great significance. The research on the credit and financial risks of financial enterprises is helpful to help financial enterprises handle financial risks well and perform evasive operations on them. In addition, it can also enhance the credit awareness of enterprises and reduce the default rate in the financial industry. This paper studies and analyzes the financial enterprise credit and financial risk measurement based on the PSM model. First, it uses the literature method to study the PSM model, corporate credit, financial risk and other theoretical knowledge, and then establish a fuzzy neural network model for risk assessment. And the establishment of a PSM model to conduct a questionnaire survey experiment design, analyze the price sensitivity changes and acceptable price ranges under the PSM model, and get the optimal pricing of new financial products issued by financial companies. Finally, it analyzes the relationship between the default rate of corporate credit and internal finance. The conclusion is that when this financial product is priced at 45 yuan, the proportion of reserved recipients is the largest, reaching 66%; when the price is 75 yuan, the acceptable proportion is 23%, which is the acceptable number of people in the three price ranges. The proportion is the largest; if the price is 100 yuan, the unacceptable proportion is the largest, reaching 45%. This shows that the pricing of a new financial product is directly related to its sales. The reasonableness of the product pricing directly determines whether people are willing to pay for it and accept it.

scholarly journals Financial Risk Management and the Avoidance Strategy in Corporate Financial Projects

2020 ◽  
Vol 4 (3) ◽  
pp. 86
Author(s):  
Yuxuan Liu
Keyword(s):  
Risk Management ◽  
Financial Risk ◽  
Rapid Development ◽  
Social Economy ◽  
Current Situation ◽  
Financial Risks ◽  
Financial Risk Management ◽  
Different Types ◽  
Avoidance Strategy

<p>With the rapid development of social economy, enterprises enter into an era with best opportunities for development, and are facing with great challenges at the same time. Especially in the current situation, it is important for enterprises to make careful decisions to avoid financial risks when carrying out financial projects. Based on this, this article, starting with the financial risks in corporate financial projects, scientifically divides financial risks into different types and puts forward specific strategies to avoid risks for reference.</p>

scholarly journals Early Warning System for Penalty Constrained Financial Risks of Enterprises under Diversified Investment

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yongyong Zhu
Keyword(s):  
Rapid Development ◽  
Social Economy ◽  
Warning System ◽  
Economic Benefits ◽  
Positive Development ◽  
Economic Losses ◽  
Financial Risks ◽  
The Sustainable Development ◽  
Depth Analysis ◽  
Prevention Model

Based on the understanding of the main types and purposes of enterprise diversification investment, this paper conducts an in-depth analysis of the environmental, structural, and scale risks of enterprise diversification investment and uses this as the basis for the effective construction of a risk prevention model. It can help enterprises effectively avoid investment risks, avoid bringing huge economic losses to enterprises, and help lay a good foundation for the positive development of enterprises. With the rapid development of social economy, enterprises must realize diversified investment if they want to improve their market economy status. However, due to many factors, they face greater economic risks and even cause serious economic losses to enterprises. Therefore, effective measures must be taken to prevent risks and promote the sustainable development of enterprises so as to obtain more economic benefits.

scholarly journals Analysis of Identification and Supervision of Financial Risk Based on One Belt and One Road

2019 ◽  
Vol 2 (6) ◽  
Author(s):  
Bowen Duan
Keyword(s):  
Economic Development ◽  
Financial Management ◽  
Financial Risk ◽  
Social Economy ◽  
Road Construction ◽  
Financial Risks ◽  
Management Mechanism ◽  
Close Link ◽  
Modern Economy ◽  
The One

With the continuous development and progress of social economy, people pay more and more attention to financial risks. Thus modern economy has close link with finance, and the One Belt and One Road is a new exploration of social economy. If the modern economy wants better development, One Belt and One Road construction should be brought into economic development. And it has a impact on trade financing and outward investment of enterprises. Therefore, if it wants to be carried out smoothly, the financial management mechanism should be improved. In this paper, a concrete analysis of the identification and supervision of financial risks will be made under One Belt and One Road construction.

scholarly journals Development Status, Causes of Risks, and Risk Supervision Suggestions on Internet Finance in China

2021 ◽  
Vol 4 (5) ◽  
pp. 45-51
Author(s):  
Junxuan Ni ◽  
Haoxuan Ni
Keyword(s):  
Financial Services ◽  
Financial Risk ◽  
Financial Risks ◽  
Financial Industry ◽  
Financial Model ◽  
Healthy Development ◽  
Development Status ◽  
Financial Exclusion ◽  
Internet Finance ◽  
Risk Supervision

As a useful supplement to China’s financial system, the development of internet finance has promoted the innovation of financial model and injected strong vitality into the financial market. Internet finance provides customers with more convenient and fast financial services, effectively alleviates financial exclusion, and reduces information asymmetry. It is of great significance to promote the marketization of interest rate and the development of inclusive finance in China. However, internet financial risk events occur frequently, posing a serious challenge. Therefore, this research analyzes the causes of internet financial risks, and provides suggestions on internet financial risk supervision, so as to promote a healthy development of the internet financial industry in China.

scholarly journals Research on the Risk Measurement Algorithm of Supply Chain Order Financing Based on Insurance Actuarial

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Gushuo Li ◽  
Menglin Yin
Keyword(s):  
Supply Chain ◽  
Financial Risk ◽  
Foreign Currency ◽  
Risk Measurement ◽  
Raw Material ◽  
Financial Risks ◽  
Efficient Operation ◽  
Supply Chain Finance ◽  
Chain Order ◽  
New Perspective

In today’s globalized economy, all the links of supply chain are interlinked. Most of the upstream raw material manufacturers or producers in the said chain are small- and medium-sized enterprises (SMEs) that provide the basis for the efficient operation of the whole supply chain. However, SMEs in China, especially those playing a pivotal role in China’s export-oriented economy at this stage, do not have access to the corresponding financial treatment. Supply chain finance provides a new perspective to solve this contradiction. Henceforth, this paper introduces modern financial engineering risk measurement tools to measure the financial risk in supply chain finance, specifically while evaluating the single financing business. Moreover, the chief objective of this paper will be the analysis of the characteristics and connotations of order financing business model. In addition, the focus will be to analyze the risk of order financing from the perspective of banks and other financial institutions. Additionally, this paper will use the CreditRisk + model based on insurance actuarial principles to manage credit risk in order financing business based on foreign currency settlement, in conjunction with the characteristics of supply chain finance and multinational supply chain. Furthermore, a risk measurement method for the application of order financing in multinational supply chains will be provided. Ultimately, the experiments show that the solution of this paper defines and analyzes the financial risks brought by order financing business to bank financing.

Research on intelligent teaching of finance based on hypermedia

2021 ◽  
pp. 002072092098352
Author(s):  
Han He ◽  
Li Yin ◽  
Weiwei Liu
Keyword(s):  
Course Design ◽  
Intelligent System ◽  
Rapid Development ◽  
Relevant Literature ◽  
Social Economy ◽  
Development Trend ◽  
Traditional Teaching ◽  
Financial Industry ◽  
Teaching System ◽  
National Education

With the rapid development of the financial industry, the total social demand has changed greatly, so it is imperative to cultivate talents in the financial industry. The arrival of information society promotes the development of social economy, and the traditional teaching methods have been difficult to meet the current situation. Under the promotion of national education policy, the construction of online open high-quality courses has made significant advantages, which further promotes the research of financial intelligent teaching based on hypermedia. Based on the analysis of the traditional teaching in our country, combined with the knowledge of economics and finance as the content carrier of the intelligent teaching system, a virtual teaching model is established to realize the research and development of the intelligent teaching system of finance. First of all, through reading a lot of relevant literature to understand the development trend and disadvantages of the development of online intelligent system at home and abroad, so as to compare the achievements of traditional financial teaching and intelligent teaching system, and explore the applicability of traditional teaching principles and related theories in guiding the construction of open courses of intelligent network system. Secondly, it summarizes the key elements and basic principles of the course design, and how to apply them to practical teaching. By combining the learning situation of the platform course in the form of questionnaire, it summarizes and analyzes the problems and deficiencies in the construction and learning process of the intelligent teaching finance course teaching design. Through the research of this paper, it is concluded that the financial intelligent teaching based on hypermedia can effectively promote the participation of students, improve the construction of curriculum resources, and reduce the pressure of traditional teaching.

scholarly journals Organization Evolution of Fuzzy System Based on Financial Risk Degree of Commercial Banks

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Chao Liu
Keyword(s):  
Risk Assessment ◽  
Fuzzy System ◽  
Commercial Banks ◽  
Financial Risk ◽  
Business Models ◽  
Rapid Development ◽  
Foreign Banks ◽  
Financial Industry ◽  
Entropy Weight ◽  
Information Quantity

After the market-oriented reform of China’s financial industry, there have been some problems in financial risk assessment. In recent years, commercial bank finance has made rapid development, but on the whole, the financial risk assessment of commercial banks is still the weakest link in the Chinese financial system. This experiment selects data from state-owned commercial banks and foreign-funded commercial banks. Through the analysis and deconstruction of the macroenvironment, participants, and business models, this paper systematically combines the factors influencing the financial risk of commercial banks, which can identify the main sources of financial risk in this complex way of financing and clarify the effects of the transfer of financial risk between different participants. Based on this, the paper studies the differences between the assets and liabilities between banks on the risk-taking of banks and the reform of the organizational evolution of fuzzy system. According to the application scenarios and actual needs of commercial banks’ financial risks, the entropy weight analysis method is used to reflect the weight of indicators by the difference degree of observed index values. The information quantity of indicators is measured to ensure that the established indicators can reflect most of the initial information. The experimental results show that, compared with state-owned banks, the proportion of foreign banks’ assets in 2018 is very small. The highest value of public debt assets is 9.2 billion yuan, followed by financial institutions with 2.58 billion yuan, and deposit institutions with 280 million yuan. The central bank has no debt amount.

Simulation analysis of financial stock market based on machine learning and GARCH model

2020 ◽  
pp. 1-11
Author(s):  
Jie Tian ◽  
Yaoqiang Wang ◽  
Wenjing Cui ◽  
Kun Zhao
Keyword(s):  
Stock Market ◽  
Financial Risk ◽  
Simulation Analysis ◽  
Financial Analysis ◽  
Rapid Development ◽  
Model Performance ◽  
Garch Model ◽  
Decision Makers ◽  
Statistical Characteristics ◽  
Financial Industry

With the rapid development of the world’s financial industry, the complexity and relevance of risks are gradually increasing. At present, there are still some deficiencies in the model for measuring financial risk. In view of this, this study analyzes the financial stock market and combines VAR model and GARCH model to conduct financial analysis. Moreover, this study uses the standard deviation in the statistical characteristics of the data to characterize the fluctuation of futures, and then uses the univariate GARCH model to measure the fluctuation. In addition, this study combines the examples to analyze the effectiveness of the model, and compares the predicted data with the actual data to verify the model performance. The results show that the algorithm proposed in this paper has certain effectiveness, and through this research algorithm, investors, speculators or macro decision makers in the futures market can obtain some inspiration.

Digital financial inclusion risk prevention based on machine learning and neural network algorithms

2021 ◽  
pp. 1-16
Author(s):  
Ning Gu
Keyword(s):  
Risk Prediction ◽  
Financial Services ◽  
Financial Risk ◽  
Rapid Development ◽  
Prediction Method ◽  
Heterogeneous Data ◽  
Mobile Internet ◽  
Financial Inclusion ◽  
Third Party ◽  
Financial Industry

In recent years, China has increased its investment in science and technology, and digital technologies such as mobile Internet, big data, and cloud computing have continuously made breakthroughs. The integration with the modern financial industry has stimulated online lending, third-party payment, digital insurance, and New financial forms such as digital wealth management are booming. With the rapid development of digital financial inclusion, the development of traditional financial industry has broken through time and geographical constraints, allowing more groups excluded from the traditional financial system to participate in financial activities and enjoy more convenient and faster personalized financial products and services, meet their financial needs and improve the reach of financial services. While the development of digital financial inclusion has benefited more groups, it has not changed the original risks of the financial industry. It has also brought about some negative external effects of financial technology, which poses greater challenges to the protection of financial consumers’ rights and interests. Therefore, this research aims at the digital inclusive risk prediction of financial institutions and personal risk prediction respectively, and proposes a financial risk prediction method based on the adaptive fusion of multi-source heterogeneous data, which can improve the effect of financial risk prediction through the effective use of multi-source data. purpose.

scholarly journals A survey on deep learning for financial risk prediction

2021 ◽  
Vol 5 (4) ◽  
pp. 716-737
Author(s):  
Kuashuai Peng ◽  
◽  
Guofeng Yan
Keyword(s):  
Deep Learning ◽  
Risk Prediction ◽  
Language Processing ◽  
Financial Risk ◽  
Rapid Development ◽  
Financial Data ◽  
Financial Risks ◽  
Learning Models ◽  
Main Work ◽  
Data Heterogeneity

<abstract> <p>The rapid development of financial technology not only provides a lot of convenience to people's production and life, but also brings a lot of risks to financial security. To prevent financial risks, a better way is to build an accurate warning model before the financial risk occurs, not to find a solution after the outbreak of the risk. In the past decade, deep learning has made amazing achievements in the fields, such as image recognition, natural language processing. Therefore, some researchers try to apply deep learning methods to financial risk prediction and most of the results are satisfactory. The main work of this paper is to review the predecessors' work of deep learning for financial risk prediction according to three prominent characteristics of financial data: heterogeneity, multi-source, and imbalance. We first briefly introduced some classical deep learning models as the model basis of financial risk prediction. Then we analyzed the reasons for these characteristics of financial data. Meanwhile, we studied the differences of commonly used deep learning models according to different data characteristics. Finally, we pointed out some open issues with research significance in this field and suggested the future implementations that might be feasible.</p> </abstract>

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