Building a Secure and Scalable Finance Chatbot: Client-Server Architecture, Load Balancing, and TLS Security

This research introduces a new and improved model for a financial chatbot based on deep learning, machine learning, and natural language processing to provide suitable financial services and increase the financial literacy of users. It utilizes a detailed financial database, another complex machine learning structure for market forecasts., and natural language processing to parse user questions. Moreover, there is the customer resource management feature that applies machine learning in the analysis of financial data and natural language processing for understanding the user”s intent. The paper also looks into the use of transport layer security (TLS) encryption to secure the flow of the sensitive information, the data that is to be transmitted from the chatbot server to the user clients. By integrating the dimensions of concepts such as financial analysis, personal finance advice, and data transmission, this research provides an extensive and secure approach to improving one”s financial situation.

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Publication Details

Published
2024-10-15
DOI
https://doi.org/10.1109/icses63445.2024.10762957
Citations
3
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
1.59
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article

Building a Secure and Scalable Finance Chatbot: Client-Server Architecture, Load Balancing, and TLS Security

C. R. Kavitha, Sreebha Bhaskaran, S. V. S. Manogna, S Akhilesh et al.
3 citations
FinTech, Crowdfunding, Digital Finance
1.59
article

Building a Secure and Scalable Finance Chatbot: Client-Server Architecture, Load Balancing, and TLS Security

C. R. Kavitha, Sreebha Bhaskaran, S. V. S. Manogna, S Akhilesh, T. Anisha Reddy
article en
3 citations

Abstract

This research introduces a new and improved model for a financial chatbot based on deep learning, machine learning, and natural language processing to provide suitable financial services and increase the financial literacy of users. It utilizes a detailed financial database, another complex machine learning structure for market forecasts., and natural language processing to parse user questions. Moreover, there is the customer resource management feature that applies machine learning in the analysis of financial data and natural language processing for understanding the user”s intent. The paper also looks into the use of transport layer security (TLS) encryption to secure the flow of the sensitive information, the data that is to be transmitted from the chatbot server to the user clients. By integrating the dimensions of concepts such as financial analysis, personal finance advice, and data transmission, this research provides an extensive and secure approach to improving one”s financial situation.

Amrita Vishwa Vidyapeetham (IN)
Openalex Percentile: Top 12%
FinTech, Crowdfunding, Digital Finance
1.59
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Building a Secure and Scalable Finance Chatbot: Client-Server Architecture, Load Balancing, and TLS Security — C. R. Kavitha, Sreebha Bhaskaran, et al. · (2024) | TGRS Research Map | TGRS