BudgetBliss: Predictive Budget Planning using Neural Networks and Socioeconomic Factors

BudgetBliss: Predictive Budget Planning using Neural Networks and Socioeconomic Factors

Kapil Sanjay Phadale, Dimple Pandurang Rathod, Arya Jayavant Kanase, Harshil Dharmendra Agrawal, Milind Khairnar

Artificial Intelligence &  Data Science

Shah & Anchor Kutchhi Engineering College Mumbai, India

Abstract

BudgetBliss is a transformative web application developed to revolutionize personal finance management through the integration of Artificial Neural Networks. Leveraging a sophisticated architecture, BudgetBliss provides users with a comprehensive platform to effectively plan and manage their income. The development process involved meticulous data collection and preprocessing, followed by the implementation of an Artificial Neural Network model. By analyzing users' spending habits and categorizing income, BudgetBliss offers detailed financial breakdowns tailored to individual needs. This methodology ensures the accuracy and relevance of the insights provided to users. Furthermore, BudgetBliss serves as an inadvertent educational tool, fostering financial literacy as users gain insights into their spending habits and make informed decisions about their money. Additionally, the automation of categorization, analysis of spending habits, and provision of personalized insights significantly reduce financial stress, empowering users to feel in control of their finances and focus on achieving their goals with confidence. In today's fast-paced society, where financial management significantly impacts overall well-being, BudgetBliss addresses the critical need for a system that enhances household financial control. By enabling users to make informed decisions and gain a deeper understanding of their financial landscape, BudgetBliss facilitates a path towards contentment and fulfillment in life.

Keywords - Budget planning, Personal finance, Artificial Neural Networks, Financial management, Well-being