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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM40779

Integrating Expense Tracking with AI-Driven Investment Recommendations

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM40779

Volume:

9 |

1 |

Jan 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM40779

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

DSS

Dr. Shanthi S

PGP

Praveen Giridhar Pawaskar

AAK

Abdul Aman Khan

RA

Rehan Ashraf

aMSP

and Mihir Suman P

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Abstract

The Expense Tracker is a comprehensive financial management application developed using the MERN stack—MongoDB, Express.js, React, and Node.js—to simplify expense tracking, budgeting, and investment decision-making. The application features a secure backend powered by Node.js and Express.js, utilizing RESTful APIs for efficient data handling, while MongoDB ensures flexible and scalable data storage. The React-based front end provides a responsive and intuitive interface, enabling users to seamlessly input, categorize, and visualize their expenses. Core functionalities include user authentication for secure and personalized access, secure expense logging to maintain accurate financial records, category management and budget tracking for effective financial organization, and interactive charts offering real-time insights into spending patterns. A key innovation of the application is the PennyDrop feature, which leverages user income and expense data to provide personalized investment suggestions. Using data-driven algorithms, PennyDrop empowers users to make informed financial decisions by aligning their income with tailored investment opportunities. This integration of expense tracking with actionable investment insights creates a holistic platform for financial management. The application is designed to be scalable, maintainable, and user-friendly, making it an ideal solution for individuals and businesses seeking an efficient tool for managing their finances and optimizing their investments.

KEYWORDS

Budget Tracking Category Management Data-Driven Investment Insights Expense Categorization Expense Input Expense Logging Financial Management Application Income-Based Investment Suggestions Interactive Charts MERN PennyDrop Feature Personalized Financial Solutions Real-Time Financial Insights RESTful APIs Scalable Data Storage.

Cite This Article

Dr. Shanthi S, Praveen Giridhar Pawaskar, Abdul Aman Khan, Rehan Ashraf, and Mihir Suman P, "Integrating Expense Tracking with AI-Driven Investment Recommendations," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 1, Jan 2025. https://doi.org/10.55041/IJSREM40779

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Publication Date

1/15/2025

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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