Financial risk assessment model based on big data

Kang, Qiong

doi:10.1142/s1793962319500211

Cited by 21 publications

(10 citation statements)

References 9 publications

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“…In order to solve this problem, he proposed a big data-based financial risk assessment model, which uses regression analysis to conduct big data analysis and prediction of financial risk assessment. Although the scholar's point of view is very good, he did not use some practical examples to illustrate whether the model he established is feasible [1]. Zhu and Liu found that establishing a good financial risk early warning mechanism has become very meaningful in today's society.…”

Section: Related Workmentioning

confidence: 99%

Risk Prevention of E-Commerce Supply Chain Financial Market Based on High-Performance Computing

Wang

Yang

Song

2022

Mobile Information Systems

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As an emerging industry, e-commerce mainly relies on online platforms to provide products and services for enterprises and consumers, and it has its own risks in the development of supply chain finance. When developing an online business, it can rely on the support of developed logistics and physical stores, which has its special advantages in operating supply chain finance, but at the same time, it also brings special business risks. With the rapid development of economic level in recent years, the application of EC Supply Chain has become more and more extensive. The emergence of EC Supply Chain has injected strong vitality into the financial market, but at the same time, the EC Supply Chain financial business is also facing huge risks. For cross-border import e-commerce companies, the core of the supply chain is the source of goods and logistics. Enterprises have more resources, which means that they have more initiative in the fierce competition, and a stable and perfect supply chain will be the core competitiveness of the cross-border import e-commerce industry. The purpose of this paper is to study how to prevent risks in the EC Supply Chain financial market based on high-performance computing. This paper puts forward the importance of high-performance computing and the significance of EC Supply Chain development and proposes preventive measures against financial market risks in EC Supply Chain. From the data in the experimental part of this paper, it can be known that the development trend of the risk generated by the EC Supply Chain in 2010 accounted for 6.9%. By 2015, the percentage of the development trend of EC Supply Chain risk was 17.9%, an increase of 11%. It can be seen that the development of EC Supply Chain risk is very rapid, so how to prevent the financial market risk of EC Supply Chain is very urgent. From the data, it can be seen that the exogenous risk in the e-commerce supply chain has a score of 7.4–8.4 for market risk, a score of 7.7–9.1 for economic risk, and the highest score for economic risk. Risk is the biggest risk factor. The characteristics of supply chain risk are not only complex, diverse, and uncertain but also transitive and virtual.

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Section: Related Workmentioning

confidence: 99%

Risk Prevention of E-Commerce Supply Chain Financial Market Based on High-Performance Computing

Wang

Yang

Song

2022

Mobile Information Systems

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“…is method uses quantitative analysis methods to analyze the explanatory variable model and the controlled variable model of financial risk assessment. e simulation results show that this method can provide high financial risk assessment accuracy; it has a strong adaptive evaluation ability for risk coefficients, and it has good application value in the prevention and control of financial system risk factors [2]. Zhai et al proposed a multiattention fusion modeling (multi-AFM) to address the problems of low efficiency and heavy workload of university curriculum evaluation methods.…”

Section: Related Workmentioning

confidence: 99%

“…e calculation of the above formula needs to first calculate the partial derivatives z/zT (h) nm y(t, c, a, b) and z/zc (h) n y(t, c, a, b) of the cost function y(t, c, a, b) corresponding to a single training sample (a, b), and the BP algorithm is very effective for calculating the partial derivative of the cost function [2]. e entire process of the back propagation algorithm is as follows:…”

Section: Back Propagation Algorithmmentioning

confidence: 99%

Teaching Method of Japanese Professional Writing Course Based on Big Data Fusion

Zhao

Guocai

2022

Security and Communication Networks

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In recent years, the number of Japanese learners has increased year by year. When Japanese is learned as a language, knowledge of the language itself is indispensable. This article aims to explore the teaching methods of Japanese professional writing courses based on the integration of big data. This article first introduces big data fusion and introduces the definition and model of data fusion. Generally, there are two types of data fusion models: distributed and centralized. Then, I analyzed the artificial neural network algorithm, which is a computational model that imitates the animal brain, and then researched the context-based teaching of Japanese professional courses and analyzed the context-based teaching of Japanese professional writing. The results of the context-based Japanese course teaching research show that the average Japanese writing score of the experimental class is 72.7833, the control class score is 66.3333, and the composition fluency scores are 156.27 and 119.73. It can be concluded that the composition performance and composition fluency of students in the experimental class are higher than those in the control class, so educators should let students strengthen vocabulary spelling and memory skills in situational teaching.

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“…Based on the economic game theory, big data technology is used to predict the possible risks in the financial field. Finally, an adaptive financial risk assessment scheme is formed [ 6 ]. His research is both theoretically and methodologically good, but no applied analysis of actual data has been carried out, and its predictive effect needs to be further verified.…”

Section: Introductionmentioning

confidence: 99%

Construction of Economic Security Early Warning System Based on Cloud Computing and Data Mining

Yuan

Xie

Tan

2022

Computational Intelligence and Neuroscience

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Economic security is a core theoretical issue in economics. In modern economic conditions, the ups and downs caused by economic instability in any economic system will affect the stability of the financial market, bring huge losses to the economy, and affect the development of the whole national economy. Therefore, research on the regularity of economic security and economic fluctuations is one of the important contents to ensure economic stability and scientific development. Accurate monitoring and forecasting of economic security are an indispensable link in economic system regulation, and it is also an important reference factor for any economic organization to make decisions. This article focuses on the construction of an economic security early warning system as the main research content. It integrates cloud computing and data mining technologies and is supported by CNN-SVM algorithm and designs an early warning model that can adaptively evaluate and warn the economic security state. Experiments show that when the CNN network in the model uses ReLU activation function and SVM uses RBF function, the prediction accuracy can reach 0.98, and the prediction effect is the best. The data set is verified, and the output Q province’s 2018 economic security early warning comprehensive index is 0.893. The 2019 economic security early warning index is 0.829, which is consistent with the actual situation.

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Financial risk assessment model based on big data

Cited by 21 publications

References 9 publications

Risk Prevention of E-Commerce Supply Chain Financial Market Based on High-Performance Computing

Risk Prevention of E-Commerce Supply Chain Financial Market Based on High-Performance Computing

Teaching Method of Japanese Professional Writing Course Based on Big Data Fusion

Construction of Economic Security Early Warning System Based on Cloud Computing and Data Mining

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