Financial Risk Evaluation System in the Context of Great Intelligence Movement Cloud: A Hierarchical Analysis Approach

This paper examines the financial risk evaluation system in the context of the “Great Intelligence Movement Cloud” and employs the hierarchical analysis method as the primary research tool. With the rapid advancement of “Great Intelligence Movement Cloud” technology, enterprise financial risks have expanded from the offline domain to the information domain, encompassing a broader scope and more diverse channels. The traditional approach to risk identification, relying solely on single financial indicators, no longer meets current demands. Therefore, it is essential to integrate a non-financial early warning indicator system and adopt a combination of quantitative and qualitative analysis methods. Hierarchical analysis enables the decomposition of complex problems into multiple components and organizes them into a hierarchical structure based on their relationships, facilitating a more accurate assessment of financial risk. This study seeks to establish a comprehensive financial risk evaluation system suited to the “Great Intelligence Movement Cloud” context, offering enterprises more precise risk assessments to better address financial risks and achieve steady development.

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Publication Details

Journal
Proceedings of Business and Economic Studies
Published
2024-12-23
DOI
https://doi.org/10.26689/pbes.v7i6.9126
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.00
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article

Financial Risk Evaluation System in the Context of Great Intelligence Movement Cloud: A Hierarchical Analysis Approach

Fei Pan
Proceedings of Business and Economic Studies
Impact of AI and Big Data on Business and Society
article

Financial Risk Evaluation System in the Context of Great Intelligence Movement Cloud: A Hierarchical Analysis Approach

Fei Pan
article en

Abstract

This paper examines the financial risk evaluation system in the context of the “Great Intelligence Movement Cloud” and employs the hierarchical analysis method as the primary research tool. With the rapid advancement of “Great Intelligence Movement Cloud” technology, enterprise financial risks have expanded from the offline domain to the information domain, encompassing a broader scope and more diverse channels. The traditional approach to risk identification, relying solely on single financial indicators, no longer meets current demands. Therefore, it is essential to integrate a non-financial early warning indicator system and adopt a combination of quantitative and qualitative analysis methods. Hierarchical analysis enables the decomposition of complex problems into multiple components and organizes them into a hierarchical structure based on their relationships, facilitating a more accurate assessment of financial risk. This study seeks to establish a comprehensive financial risk evaluation system suited to the “Great Intelligence Movement Cloud” context, offering enterprises more precise risk assessments to better address financial risks and achieve steady development.

Proceedings of Business and Economic StudiesVol. 7(6)
Openalex Percentile: Top 71%
Impact of AI and Big Data on Business and Society
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