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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM65718

AI-Powered Smart Family Finance Management System with Investment Analytics and Wealth Prediction

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65718

Volume:

10 |

6 |

Jun 2026

Pages:

1-6

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM65718

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

Satheeswari Muthuchamy

Satheeswari Muthuchamy

Department of Computer Science and Engineering

Sri Vidya College of Engineering and Technology

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NR

Nisha Rajaram

Department of Computer Science and Engineering

Sri Vidya College of Engineering and Technology

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DPP

Dr. Pasupathi Perumalsamy

Department of Computer Science and Engineering

Sri Vidya College of Engineering and Technology

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Abstract

Personal finance management is a growing challenge for middle-class families, who must simultaneously track daily expenditure, manage a monthly salary and monitor a diverse portfolio of investments. Most existing tools address only one of these needs, forcing families to switch between disconnected applications. This paper presents Smart Family Financier, a full-stack web application that unifies expense tracking, salary management, investment portfolio management, financial reporting and rule-based advisory within a single dashboard. The client is a single-page application built with React and Vite, and the server is a stateless REST API built with Node.js and Express, secured using JSON Web Tokens. The investment module supports thirteen asset classes spanning traditional Indian instruments such as gold, fixed deposits, the Public Provident Fund and the National Pension System, and modern alternatives such as equities, mutual funds and cryptocurrency. Gold holdings are revalued in real time, a composite portfolio health score is computed from diversification, emergency-fund coverage and equity exposure, and a wealth-prediction engine projects value over multiple horizons. Evaluation on a representative family dataset of over one hundred and seventy expense records and eleven months of salary history shows that the platform computes the key financial indicators accurately and presents them in an intuitive, India-centric interface.

KEYWORDS

Personal finance management expense tracking investment portfolio portfolio health score REST API rule-based advisory.

Cite This Article

Satheeswari Muthuchamy, Nisha Rajaram, Dr. Pasupathi Perumalsamy, "AI-Powered Smart Family Finance Management System with Investment Analytics and Wealth Prediction," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-6, Jun 2026. https://doi.org/10.55041/IJSREM65718

Full Article/Conclusion

This paper has presented the design and implementation of Smart Family Financier, a full-stack web application that unifies expense tracking, salary management, investment portfolio management, financial reporting and rule-based advisory within a single dashboard. Built as a React single-page application backed by a stateless Node.js and Express REST API secured with JWTs, the system supports thirteen investment asset classes, revalues gold holdings in real time, computes a composite portfolio health score, generates personalized insights, projects future wealth and exports data to Excel and PDF. Evaluation on a representative family dataset demonstrated accurate computation of the key indicators in an intuitive, India-centric interface. Planned future work includes multi-member sub-accounts, category-level budgets, open-banking transaction import, live stock-market prices, an income-tax calculator, a React Native mobile application, and machine-learning-based spending-pattern analysis and anomaly detection.

References

1. Markowitz, H.M.: Portfolio Selection. The Journal of Finance 7(1) (1952) 77–91 2. Sharpe, W.F.: Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. The Journal of Finance 19(3) (1964) 425–442 3. Bodie, Z., Kane, A., Marcus, A.J.: Investments. 10th edn. McGraw-Hill Education, New York (2014) 4. Fielding, R.T.: Architectural Styles and the Design of Network-based Software Architectures. Doctoral Dissertation, University of California, Irvine (2000) 5. Fowler, M.: Patterns of Enterprise Application Architecture. Addison-Wesley, Boston (2002) 6. Richardson, L., Ruby, S.: RESTful Web Services. O’Reilly Media, Sebastopol, California (2007) 7. Jones, M., Bradley, J., Sakimura, N.: JSON Web Token (JWT). RFC 7519, Internet Engineering Task Force (2015) 8. Nielsen, J.: Usability Engineering. Morgan Kaufmann, San Francisco (1994)

Editorial & Review Transparency

Publication Date

6/30/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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