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.

scholarly journals Value Added Tax in the Aspect of Forming the Enterprise Accounting Policy

2020 ◽  
Vol 23 (1) ◽  
pp. 120-124
Author(s):  
Olena Matros ◽  
◽  
Liudmyla Melnyk ◽  
Svitlana Mykhailovyna ◽  
◽  
...  
Keyword(s):  
Tax Policy ◽  
Financial Risk ◽  
Value Added ◽  
Tax Burden ◽  
Tax Credit ◽  
Value Added Tax ◽  
Tax Rate ◽  
Tax Legislation ◽  
Business Entities ◽  
Accounting Policy

Introduction. Currently, indirect taxes play a crucial role in shaping the state’s Tax Policy and creating the legal basis for a market economy. In their composition; the value-added tax acts as one of the regulators of the redistribution of public goods and one of the main and stable sources of income to the budget; as well as a way to distribute the tax burden, which allows maintaining the economic and legal equality of taxpayers. Purpose. The aim of the research is to identify possible directions for improving the process of managing value added tax in terms of the forming the enterprise accounting policy. Results. The research has identified a number of problems on the chosen topic, including: the problem of practical application of the principle of undisputed tax credit and non-execution of court decisions; lack of predictability of changes in tax legislation; uncertainty of tax risks and possible measures to prevent them. Based on the outlined problems, opportunities have been assessed and the feasibility of reducing the tax burden on business entities under VAT has been determined. The significance of tax planning has been determined – it allows you to provide for the size of the tax obligation to be paid and control the correctness of its accrual. If new business conditions arise, planning allows you to analyze tax factors and take them into account in the process of implementing tax policy. Conclusions. The theory of taxation defines the essence and content of the tax policy of the enterprise in terms of value added tax; tax risk zones related to VAT payment have been investigated; the concept of tax risk as a special type of financial risk characterizing the possibility of unforeseen financial losses (collection of tax arrears; penalties for late payment of tax; collection of penalties; non-reimbursement of VAT at zero tax rate; inability to use VAT tax credit) related to changes in tax legislation or is the result of taxpayer activity or actions of tax authorities; proposed classification of types of tax risks by VAT depending on the reasons for their occurrence and proposed means of preventing risks associated with the calculation and payment of VAT.

scholarly journals Research on Supply Chain Financial Risks and Preventive Measures in the Era of Big Data

2020 ◽  
Vol 214 ◽  
pp. 03032
Author(s):  
Weiting Sun ◽  
Puxue Shen
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Financial Institutions ◽  
Financial Risk ◽  
Large Scale ◽  
Theory And Practice ◽  
Privacy And Security ◽  
Internet Applications ◽  
Supply Chain Finance ◽  
Big Data Technology

The emergence of supply chain finance has reduced the financing costs of SMEs. Due to the development of a diversified supply chain financial subject platform, there is a lack of risk control in terms of theory and practice. Big data is generated in Internet applications and combined with information technology to form big data technology. It can provide financial institutions with large-scale data analysis methods and can effectively improve the efficiency and ability of financial institutions to serve supply chain members. However, big data has some problems, such as higher processing cost, lower authenticity, and difficulty in effectively protecting the privacy and security of users. There are many problems with this new development model. This article focuses on the risk problems faced by supply chain finance. It discusses the use of big data technology to effectively solve the supply chain financial risk problems, and gives some measures that can be effectively solved for how to effectively avoid these risk factors. By effectively solving the financial risk problem in the era of big data, it provides guarantee for the benign development of enterprises, and provides a certain reference for researchers engaged in related fields and workers in this field.

scholarly journals Research on Tax Planning of PPP Projects in China: Based on the Perspective of Digital Economy

2020 ◽  
Vol 4 (2) ◽  
pp. 128
Author(s):  
Jiangyu Huang
Keyword(s):  
Big Data ◽  
Value Added ◽  
Tax Planning ◽  
Digital Economy ◽  
Guizhou Province ◽  
Value For Money ◽  
Value Added Tax ◽  
Company Value ◽  
Fiscal Revenue ◽  
The Cost

The digital economy has become an important driving force for the growth of fiscal revenue in various countries. Tax planning is essential for the cost accounting of PPP projects, reducing corporate tax burdens, and increasing company value. This paper adopts a case analysis method, taking the smart highway PPP project in Guizhou Province as an example. Through statistical analysis, it is found that the value-for-money and big data of the PPP project affects tax planning, the project’ s value-added tax input and output items have time mismatches, and enterprises Income tax payment imbalance. In the context of the digital economy, the tax planning of China's PPP projects can be further improved: digital transformation and big data to prevent tax risks caused by value for money evaluation; based on digital technology to improve the value-added tax deduction chain, and digital communication platforms to alleviate time mismatch of value-added tax; use big data to monitor and balance project portfolio investment; improve the level of digital skills of financial personnel.

scholarly journals Digitalisation of the Value Added Tax

2021 ◽  
Vol 5 (1) ◽  
pp. 111-120
Author(s):  
Peter Rakovský
Keyword(s):  
Big Data ◽  
Slovak Republic ◽  
Value Added ◽  
Tax Revenue ◽  
Value Added Tax ◽  
Policy Makers ◽  
Electronic Filing ◽  
The World ◽  
National Governments ◽  
The Eu

This paper focuses on Value Added Tax (VAT), due to the importance of indirect taxes as one of the most vital tax revenue generators in the EU. VAT is more stable and contributes more to the tax mix than direct taxes. However, the VAT gap is still a serious problem for the national governments, as it reduces the overall tax revenue. Tax authorities are looking for more opportunities to reduce the information asymmetries between them and the taxation subjects. Due to that, collection and analysis of big data seems to be an excellent opportunity to do so in the Slovak Republic as well. One of the biggest sources of big data in VAT in Europe and the world is formed by the so-called “real-time reporting” and electronic filing, since electronic filing is mandatory in the majority of EU countries nowadays. However, policy makers should bear in mind that the mere collection of data is not enough (Bal, 2014). The main subject of this paper is to find, analyse and take into account the most important measures of VAT in the context of digitalisation. In addition, this paper focuses on new trends and challenges for VAT in the Slovak Republic, which may follow the trends within the world.

scholarly journals Enterprise Financial Risk Management Using Information Fusion Technology and Big Data Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Huabo Yue ◽  
Haojie Liao ◽  
Dong Li ◽  
Ling Chen
Keyword(s):  
Logistic Regression ◽  
Big Data ◽  
Information Fusion ◽  
Classification Accuracy ◽  
Financial Risk ◽  
Financial Risks ◽  
Fusion Technology ◽  
Financial Risk Management ◽  
Big Data Mining ◽  
Big Data Technology

This paper aims to study enterprise Financial Risk Management (FRM) through Big Data Mining (BDM) and explore effective FRM solutions by introducing information fusion technology. Specifically, big data technology, Support Vector Machine (SVM), Logistic regression, and information fusion approaches are employedto study the enterprise financial risks in-depth.Among them, the selection offinancial risk indexes has a great impact on the monitoring results of the SVM-based FRM model; the Logistic regression-based FRM model can efficientlyclassify financial risks; theinformation fusion-based FRM model uses a fusion algorithm to fuse different information sources. The results show that the SVM-based and Logistic regression-based FRM models can manage and classify enterprise financial risks effectively in practice, with a classification accuracy of 90.22% and 90.88%, respectively; by comparison, the information fusion-based FRM modelbeats SVM-based and Logistic regression-based FRM models by presenting a classification accuracy as high as 95.18%. Therefore, it is concluded that the information fusion-based FRM is better than the SVM-based and Logistic regression-based models; it can integrate and calculate multiple enterprise financial risk data from different sources and obtain higher accuracy; besides, big data technology can provide important research methods for enterprise financial risk problems; SVM-based FRM model and Logistic regression-based FRM model can well classify enterprise financial risks, with relatively high accuracy.

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