Research on the Collection of Microcosmic Warning Indicators of Systematic Financial Risk Based on Big Data

2020 ◽  
Author(s):  
Xin Wang
Keyword(s):  
Big Data ◽  
Financial Risk ◽  
Warning Indicators

scholarly journals Hydrological Layered Dialysis Research on Supply Chain Financial Risk Prediction under Big Data Scenario

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Jia Liu ◽  
Shiyong Li ◽  
Xiaoxia Zhu
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Risk Analysis ◽  
Risk Prediction ◽  
Financial Institutions ◽  
Surface Runoff ◽  
Financial Risk ◽  
Supply Chain Finance ◽  
Runoff Model

In recent years, internet development provides new channels and opportunities for small- and middle-sized enterprises’ (SMEs) financing. Supply chain finance is a hot topic in theoretical and practical circles. Financial institutions transform materialized capital flows into online data under big data scenario, which provides networked, precise, and computerized financial services for SMEs in the supply chain. By drawing on the risk management theory in economics and the distributed hydrological model in hydrology, this paper presents a supply chain financial risk prediction method under big data. First, we build a “hydrological database” used for the risk analysis of supply chain financing under big data. Second, we construct the risk identification models of “water circle model,” “surface runoff model,” and “underground runoff model” and carry on the risk prediction from the overall level (water circle). Finally, we launch the supply chain financial risk analysis from breadth level (surface runoff) and depth level (underground runoff); moreover, we integrate the analysis results and make financial decisions. The results can enrich the research on risk management of supply chain finance and provide feasible and effective risk prediction methods and suggestions for financial institutions.

scholarly journals Application of Big Data Model in Financial Taxation Management

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Li Lin
Keyword(s):  
Big Data ◽  
Financial Risk ◽  
Value Added ◽  
Operating Conditions ◽  
Value Added Tax ◽  
Strong Negative Correlation ◽  
Problems And Solutions ◽  
Business Income ◽  
Taxation Management ◽  
Big Data Technology

We have entered an era of information technology. Many financial and taxation management tasks have been applied to big data technology. Through big data technology, we can efficiently collect data and Internet information, realize efficient management of information, and establish a complete set of tax database. The research results of the article show the following. (1) We analyze the application status of big data technology and put forward the problems and solutions in data processing in our country. (2) Most financial managers of small and medium-sized enterprises are rather vague about the definition of taxation. Training in this area should be strengthened. Taking the industrial chain of Chinese enterprises as the survey object, the concept of taxation compliance and influencing factors have been elaborated, and a taxation respect model has been established. The investigation method can be analyzed through the model. (3) We established the coefficient of variation model with Pilka coefficient and found that the main business income has the highest correlation with the value-added tax payable and has the strongest linear relationship; the correlation between return on assets and value-added tax payable is the weakest, and there is a weak relationship. There is a strong negative correlation between sales profit margin and VAT payable (4) Taking a pharmaceutical company in our country as the subject of investigation, the company’s financial operating conditions have been studied for the past ten years, and it is concluded that the company’s main business income is increasing year by year, and the corresponding tax revenue is also increasing, and the tax growth rate is relatively unstable. Among them, the financial risk coefficient of corporate income tax is the largest.

Research on the Risk Characteristics and Regulation Paradigm of Internet Financial

2014 ◽  
Vol 687-691 ◽  
pp. 2011-2014
Author(s):  
Tian Xiong Liu
Keyword(s):  
Big Data ◽  
Financial Risk ◽  
Third Party ◽  
P2p Network ◽  
The Internet ◽  
Development Mode ◽  
Risk Characteristics ◽  
Internet Finance ◽  
Development Course ◽  
Financial Mode

Based on introducing the Internet finance and its development course, it combed the Internet finance related theory and analyzed the Internet financial P2P network model. The raised platform model has big data financial mode and third-party payment mode and development mode and puts forward the thinking of Internet financial risk and regulation.

scholarly journals Analysis of Financial Risk Early Warning Systems of High-Tech Enterprises under Big Data Framework

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Maotao Lai
Keyword(s):  
Big Data ◽  
Financial Crisis ◽  
Early Warning ◽  
Logistic Model ◽  
High Tech ◽  
Financial Indicators ◽  
Early Warning Model ◽  
Early Warning Indicators ◽  
Warning Model ◽  
Warning Indicators

With the further development of China's market economy, the competition faced by companies in the market has become more intense, and many companies have difficulty facing pressure and risks. Among the many types of enterprises, high-tech enterprises are the riskiest. The emergence of big data technologies and concepts in recent years has provided new opportunities for financial crisis early warning. Through in-depth study of the theoretical feasibility and practical value of big data indicators, the use of big data indicators to develop an early warning system for financial crises has important theoretical value for breaking through the stagnant predicament of financial crisis early warning. As a result of the preceding context, this research focuses on the influence of big data on the financial crisis early warning model, selects and quantifies the big data indicators and financial indicators, designs the financial crisis early warning model, and verifies its accuracy. The specific research design ideas include the following: (1) We make preliminary preparations for model construction. Preliminary determination and screening of training samples and early warning indicators are carried out, the samples needed to build the model and the early warning indicator system are determined, and the principles of the model methods used are briefly described. First, we perform a significant analysis of financial indicators and screen out early warning indicators that can clearly distinguish between financial crisis companies and nonfinancial crisis companies. (2) We analyze the sentiment tendency of the stock bar comment data to obtain big data indicators. Then, we establish a logistic model based on pure financial indicators and a logistic model that introduces big data indicators. Finally, the two models are tested and compared, the changes in the model's early warning effect before and after the introduction of big data indicators are analyzed, and the optimization effect of big data indicators on financial crisis early warning is tested.

TOWARDS SUSTAINABLE INDUSTRIALIZATION USING BIG DATA AND INTERNET OF THINGS

2019 ◽  
Vol 01 (01) ◽  
pp. 24-38 ◽  
Author(s):  
Suma V
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
New Product Development ◽  
Financial Risk ◽  
Big Data Analytics ◽  
Industrial Sector ◽  
The Internet ◽  
Competitive Edge ◽  
Potential Applications ◽  
The Internet Of Things

The developing nations requires to have sustainable developments in the industries to have new product development and continuous improvement in the social and economic levels paving way for the customer satisfaction. The Big data and the Internet of things are innovative technologies that have made their separate stand in the industrial sector of manufacturing and providing competitive edge to the companies. So the combining of two technologies would multiply anticipation and would create way for the enhanced productivity by satisfying the global needs of the business. Further, the internet of thing along with the big data analytics is also expected to provide with the enhanced security provision, quality of process and products with reduced production down time and financial risk. So the paper proposes the big data and IoT role in the industrial sector and evaluates its performance by analyzing the impacts of the big data and the internet of things in the industry to have sustainability in production process. The proposed framework also analyses the potential applications and the key advantages offered by the integration of the internet of things and the big data.

Sign in / Sign up

Export Citation Format

Share Document