Artificial Intelligence Optimizes the Accounting Data Integration and Financial Risk Assessment Model of the E-commerce Platform

This research focuses on the use of artificial intelligence (AI) technology to optimize the accounting data integration and financial risk assessment model of e-commerce platforms, aiming to solve the data complexity and risk prediction problems faced by e-commerce platforms in financial management. The research first analyzes the challenges of accounting data integration of e-commerce platforms, including problems such as diversified data sources, inconsistent formats and uneven data quality, and proposes solutions based on machine learning (such as random forest) and deep learning (such as LSTM model). Through data cleaning, missing value filling and standardized pre-processing, an efficient accounting data integration model is studied and constructed, which significantly improves the accuracy and efficiency of data integration. In terms of financial risk assessment, the AI-based risk prediction model is designed, focusing on the unique credit risks and market risks of the e-commerce platform. The experimental results show that the accuracy of LSTM model in risk prediction is significantly higher than that of traditional methods, which can capture market changes in real time and provide timely risk warning. In addition, the study also verifies the effectiveness of the model in practical application through case analysis, which provides a scientific basis for the financial decision-making of the e-commerce platform. The main contributions of the research are as follows: the first, the significant advantages of AI technology in accounting data integration and financial risk assessment; the second E-commerce platform provides operational AI model and optimization scheme; third, it provides theoretical support and practical reference for the wide application of AI in financial management in the future. The research conclusion shows that AI technology can not only significantly improve the financial management efficiency of e-commerce platforms, but also provide reference for the financial digital transformation of other industries.

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Publication Details

Journal
International Journal of Management Science Research
Published
2025-02-10
DOI
https://doi.org/10.53469/ijomsr.2025.08(02).02
Citations
3
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
6.32
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article

Artificial Intelligence Optimizes the Accounting Data Integration and Financial Risk Assessment Model of the E-commerce Platform

Jonathan Chew, Zhiyuan Wang, Wang Yong, Ke Hu et al.
3 citations
International Journal of Management Science Research
Impact of AI and Big Data on Business and Society
6.32
article

Artificial Intelligence Optimizes the Accounting Data Integration and Financial Risk Assessment Model of the E-commerce Platform

Jonathan Chew, Zhiyuan Wang, Wang Yong, Ke Hu, Zhihao Shen
article en
3 citations

Abstract

This research focuses on the use of artificial intelligence (AI) technology to optimize the accounting data integration and financial risk assessment model of e-commerce platforms, aiming to solve the data complexity and risk prediction problems faced by e-commerce platforms in financial management. The research first analyzes the challenges of accounting data integration of e-commerce platforms, including problems such as diversified data sources, inconsistent formats and uneven data quality, and proposes solutions based on machine learning (such as random forest) and deep learning (such as LSTM model). Through data cleaning, missing value filling and standardized pre-processing, an efficient accounting data integration model is studied and constructed, which significantly improves the accuracy and efficiency of data integration. In terms of financial risk assessment, the AI-based risk prediction model is designed, focusing on the unique credit risks and market risks of the e-commerce platform. The experimental results show that the accuracy of LSTM model in risk prediction is significantly higher than that of traditional methods, which can capture market changes in real time and provide timely risk warning. In addition, the study also verifies the effectiveness of the model in practical application through case analysis, which provides a scientific basis for the financial decision-making of the e-commerce platform. The main contributions of the research are as follows: the first, the significant advantages of AI technology in accounting data integration and financial risk assessment; the second E-commerce platform provides operational AI model and optimization scheme; third, it provides theoretical support and practical reference for the wide application of AI in financial management in the future. The research conclusion shows that AI technology can not only significantly improve the financial management efficiency of e-commerce platforms, but also provide reference for the financial digital transformation of other industries.

International Journal of Management Science ResearchVol. 8(2)
Universiti Sains Malaysia (MY), University of Aberdeen (GB), Association for the Advancement of Artificial Intelligence (US), Hospital Universiti Sains Malaysia (MY), Heilongjiang Institute of Technology (CN), Cranfield University (GB)
Openalex Percentile: Top 5%
Impact of AI and Big Data on Business and Society
6.32
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