FinSaathi: An AI-Powered Expense Management System for Students

FinSaathi is a comprehensive, AI-driven personal finance management system specifically designed to address the unique financial challenges faced by students and young professionals. The system leverages advanced machine learning algorithms, Optical Character Recognition (OCR), Natural Language Processing (NLP), and gamification principles to provide automated expense tracking, intelligent budgeting recommendations, and engaging financial literacy tools. Built using Flutter for cross-platform mobile development, Node.js/Express for backend services, and MongoDB Atlas for cloud-based data storage, FinSaathi integrates behavioral economics principles to encourage positive financial habits. The platform features automated receipt scanning with 95% accuracy, AI-powered expense categorization achieving 87% precision, real-time budget monitoring, and gamified user engagement through achievement systems and social comparison features. Evaluation with 60+ student users demonstrates significant improvements in financial awareness, budget adherence, and user engagement compared to traditional expense tracking methods. The system addresses critical gaps in student-focused financial technology by combining automation, personalization, security, and campus-specific integrations.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-29
DOI
https://doi.org/10.5281/zenodo.16991212
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

FinSaathi: An AI-Powered Expense Management System for Students

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

FinSaathi: An AI-Powered Expense Management System for Students

article en

Abstract

FinSaathi is a comprehensive, AI-driven personal finance management system specifically designed to address the unique financial challenges faced by students and young professionals. The system leverages advanced machine learning algorithms, Optical Character Recognition (OCR), Natural Language Processing (NLP), and gamification principles to provide automated expense tracking, intelligent budgeting recommendations, and engaging financial literacy tools. Built using Flutter for cross-platform mobile development, Node.js/Express for backend services, and MongoDB Atlas for cloud-based data storage, FinSaathi integrates behavioral economics principles to encourage positive financial habits. The platform features automated receipt scanning with 95% accuracy, AI-powered expense categorization achieving 87% precision, real-time budget monitoring, and gamified user engagement through achievement systems and social comparison features. Evaluation with 60+ student users demonstrates significant improvements in financial awareness, budget adherence, and user engagement compared to traditional expense tracking methods. The system addresses critical gaps in student-focused financial technology by combining automation, personalization, security, and campus-specific integrations.

Zenodo (CERN European Organization for Nuclear Research)
Parul University (IN)
Quality Education
Openalex Percentile: Top 59%
Geochemistry and Geologic Mapping
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