Journal
IEEE ACCESS
Volume 8, Issue -, Pages 107685-107699Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.2997079
Keywords
Online banking; Business; Security; Computer architecture; Machine learning; Machine learning algorithms; HERCULES architecture; machine learning; hot release; smart deposits; white-collar loans; load balancing
Categories
Funding
- Intelligent Information Processing Laboratory, School of Computer, Fudan University, Shanghai, China
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The online banking transaction system is the application system with the most complex business, the most demanded, and frequent version updates in the software engineering application system. The existing online banking business sub-module is intelligent and faces major challenges in security. Traditional online banking systems cannot meet this capability. This article combines machine learning and online banking business module design to implement a business agent online banking system based on a new architecture. The article first proposes new features and new challenges of the online banking system, discusses the technical problems solved by the intelligent online banking system, and analyzes HERCULES Architecture business intelligent machine learning algorithm model, smart deposits and white-collar loans and other core processes, and then designed and implemented an intelligent online banking system business model, focusing on the issues of the intelligent online banking system, soft load balancing implementation and transaction security, through business implementation The effectiveness of the proposed business agent is verified. The actual use results show that the intelligent online banking of the HERCULES architecture has greatly improved the intelligence and security of the traditional online banking system. Finally, we summarize and analyze the value and innovation of the intelligent online banking system, and look forward to the shortcomings of the system.
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