Exploring the Path of Financial Risk Prevention in Big-Data-Supported Financial Audit

2022 ◽  
pp. 1097-1102
Author(s):  
Jianjun Xiao
Keyword(s):  
Big Data ◽  
Financial Risk ◽  
Risk Prevention ◽  
Financial Audit

scholarly journals Internet Financial Risk Early Warning Based on Big Data Analysis

2021 ◽  
pp. 48-60
Author(s):  
Noura Metawa ◽  
◽  
◽  
Saad Metawa
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Prediction Accuracy ◽  
Financial Risk ◽  
Big Data Analysis ◽  
Risk Prevention ◽  
Supervision System ◽  
Finance Industry ◽  
Risk Warning ◽  
Internet Finance

Internet financial risk prevention is an important area for financial risk prevention. In recent years, a series of vicious high-risk events, such as cash lending and P2P platform running, have caused a great negative impact on the reputation of the Internet financial industry, which has aroused great concern from all walks of life. Based on big data analysis technology, this paper constructs an improved algorithm model, and carries out high-precision risk warning for China's Internet financial risk. The forecast data is basically consistent with the actual situation, and the prediction accuracy reaches 90%. It can be seen that the improved model based on the decision tree algorithm has higher prediction accuracy for Internet financial risk warning. This paper systematically sorts out the risks of China's Internet finance from two dimensions: risk type and main risk. And pointed out that the current Internet finance industry in China has a large overall compliance risk, and insufficient infrastructure construction leads to fraud risks. Separate industry supervision has a regulatory vacuum, arbitrage risks are more obvious, and China's financial consumer quality is not high, Internet financial institutions Improper exemption is risky. On this basis, it is proposed to speed up the construction of a multi-integrated Internet financial risk prevention system including the internal risk control system, the industry association self-discipline system, the government administrative supervision system and the effective social supervision system.

scholarly journals Design of Campus Financial Risk Prevention and Control Platform under the Background of Big Data

2021 ◽  
Vol 257 ◽  
pp. 02040
Author(s):  
Sijin Li
Keyword(s):  
College Students ◽  
Big Data ◽  
Prevention And Control ◽  
Financial Risk ◽  
Risk Prevention ◽  
Financial Fraud ◽  
The Internet ◽  
Financial Industry ◽  
Control Factors ◽  
And Control

With the continuous development of information technology and the gradual rise of the Internet financial industry, the incidence of campus fraud is higher and higher, and the financial fraud against college students has gradually attracted widespread attention. In order to study the risk prevention and control factors of College Students’ financial fraud under the background of big data, an information platform is established to release risk information in real time and analyze the risk factors of College Students’ financial fraud. The Internet, big data and campus financial risk prevention and control are combined to improve the financial environment of university campus, improve the prevention awareness of college students, and reduce unnecessary losses.

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 Application of Big Data in the Financial Audit Procedures

2021 ◽  
pp. 4
Author(s):  
Kotryna Nagytė ◽  
Lina Dagilienė
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Big Data Analytics ◽  
Graphical Analysis ◽  
Statistical Correlation ◽  
Modern World ◽  
Audit Process ◽  
Systematic Analysis ◽  
Financial Audit ◽  
Jel Code

Annotation. Big Data (BD) is one of the most commonly used terms in the modern world of business and information technology. The main features of BD (quantity, speed, and variety) introduce to unique processing of large information amounts, regardless of their scale, storage and computational complexity, analytical and statistical correlation. The significant emergence and potential use of BD has affected business accounting and financial auditing by replacing the long-used mechanical data collection and completion processes with automatic ones, comparing and searching for correlations between different structure and nature data. According to analysis, the main advantages of applying the BDA in the audit process are related to faster and more efficient execution of procedures, obtaining more detailed results, grouping and comparing data according to selected criteria. In the meantime, cons of BD application are related to the additional professional supervision requirements and the proper data analysis in order for the correct results interpretation. The paper presents the conceptual model, which shows the relationships between BDA tools and financial audit procedures. In addition, the model shows factors and risks, which have impacts on internal and external environment of clients, the applicability of specific audit procedures. It was found that the application of the model in the procedures includes testing of 5 relationships, i. e. classification, clustering, regression and time series analyses, the method of association rules and text research, visualization tool. The Aim of the Study is to identify the application of DDA tools in financial audit procedures. Research Methods: comparative and systematic analysis of the literature; content analysis; statistical data analysis; graphical analysis. Keywords: Big data, Big data Analytics, Financial Audit, Financial Audit Procedures. JEL Code: M15, M40, M42.

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