Study on early warning of E-commerce enterprise financial risk based on deep learning algorithm

Yali Cao, Yue Shao and Hongxia Zhang ()
Additional contact information
Yali Cao: Beijing Technology and Business University
Yue Shao: University of International Business and Economics
Hongxia Zhang: Jiyang College, Zhejiang Agriculture and Forestry University

Electronic Commerce Research, 2022, vol. 22, issue 1, No 2, 36 pages

Abstract: Abstract With the development trend of economic progress, the capital business of e-commerce enterprises has become complicated. The financial risk of listed companies is a problem that needs to be paid attention to. The financial risk of e-commerce companies is a complex and gradual process, and its unique reasons may be many. E-commerce companies are facing financial risks or difficulties, and bankruptcy and liquidation are also increasing. Financial risk has seriously affected e-commerce companies and society. As a result, the early warning methods of financial risks have been constantly improved. With the arrival of the new economic era in the era of knowledge economy, the early warning of financial risks in e-commerce companies has become a hot issue in the financial management of e-commerce companies. Based on the deep learning algorithm, this paper studies from the perspective of establishing the financial early warning model based on deep learning and constructing the financial risk early warning mechanism of e-commerce companies, and analyzes and forecasts the financial risks of listed companies. Through the construction of financial security early warning system, crisis signals can be diagnosed as soon as possible, and crisis signals can be prevented and solved timely and effectively.

Keywords: Financial risks; E-commerce enterprises; Deep learning; Early warning (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://link.springer.com/10.1007/s10660-020-09454-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:elcore:v:22:y:2022:i:1:d:10.1007_s10660-020-09454-9

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10660

DOI: 10.1007/s10660-020-09454-9

Access Statistics for this article

Electronic Commerce Research is currently edited by James Westland

More articles in Electronic Commerce Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().