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Banking Operations Through Data Analysis

Authors:

Joel Paul Madhavan Department of Computer Science Jain (Deemed-To-Be) University

Bangalore, India joelpaulmadhavan@gmail.com

Harsh Bherwani Department of Computer Science Jain (Deemed-To-Be) University

Bangalore, India harshnb79@gmail.com

Nesar KS

Department of Computer Science Jain (Deemed-To-Be) University Bangalore, India ksnesar@outlook.com

Abstract— In the evolving landscape of personal finance, users often rely on multiple disjointed applications to manage expenses, monitor stock portfolios, and receive investment advice. This paper evaluates the usability and effectiveness of integrating these core functionalities into a single, unified platform. We developed a full-stack web application that combines an Expense Tracker, a Stock Visualizer, and a Stock Suggestor. The goal is to eliminate the need for switching between various financial tools, thereby improving convenience, reducing cognitive load, and enhancing financial decision- making.

Through a structured development process involving modern web technologies, we created a system that not only offers seamless navigation across financial domains but also employs machine learning to provide personalized investment suggestions.

Keywords— Expense Tracker, a Stock Visualizer, and a Stock Suggestor.