FINSIGHT: An AI-Powered Personalized Finance Platform

Abstract

Managing personal finances in today\'s digital age has be-come increasingly complex, with individuals juggling multiple income streams, UPI-based transactions, and diverse spending habits. Existing tools often demand manual effort and fail to provide the kind of real-time, intelligent insights that modern users need. FinSight is a web-based personal finance management platform that addresses these challenges by combining AI-driven automation with an intuitive user experience. Built using Next.js, Tailwind CSS, Supabase and Prisma ORM, the platform offers features such as automated budget tracking, receipt scanning powered by the Gemini API, personalized financial dashboards, and monthly AI-generated reports delivered via email. A standout innovation in FinSight is its SMS-Based Transaction Track-ing system, designed specifically for the Indian digital payments eco-system. When users make payments through UPI applications such as Google Pay, PhonePe or Paytm, their banks send confirmation SMS alerts. FinSight\'s Android background service reads these messages with explicit user consent extracts transaction details including amount, merchant, date, and reference ID, and logs them automatical-ly. This eliminates manual data entry entirely and makes real-time ex-pense tracking effortless. Altogether, FinSight offers a scalable, priva-cy-friendly, and truly helpful way to manage your money that works with the payment systems you already use.

Introduction

The document presents FinSight, an AI-powered personal finance management platform designed to simplify budgeting, expense tracking, and financial decision-making in today’s complex digital economy. It addresses common challenges such as difficulty in tracking expenses, lack of financial awareness, and limited access to intelligent, secure, and automated financial tools.

FinSight uses modern technologies like Next.js, Supabase, Prisma ORM, and Google Gemini API to provide an integrated system for financial tracking, automation, and insights. It also includes SMS-based transaction detection, receipt scanning using AI, and automated categorization of expenses.

The system architecture is modular and layered, consisting of a user interface, frontend, backend, database, and external service layer. It supports key features such as real-time dashboards, budgeting tools, AI-generated financial insights, automated alerts, and chatbot-based assistance.

Technologies like OCR, machine learning, and background SMS parsing are used to automatically extract and process financial data. Security and scalability are ensured through authentication (Clerk), API protection (Arcjet), and background task scheduling (Inngest).

The literature review highlights that existing finance apps often lack deep AI integration, scalability, or strong security features. FinSight addresses these gaps by combining AI-driven analytics, automation, and secure architecture in a unified system.

Conclusion

FinSight combines artificial intelligence and modern digital technology to offer a holistic approach to the change of personal finance management. Processes like budgeting, track-ing expenses, data extraction from receipts, and UPI transactions via SMS can be automated to increase efficiency and decrease human work. The software\'s visual interfaces, machine learn-ing algorithms for data analysis, and secure authentication procedures enable users to utilize it safely and confidently to make wise financial decisions. Because UPI technology is spreading so quickly in India, the suggested SMS-Based Transaction Tracking component is often one of the most significant advancements. The truth is that each transaction is examined and transformed into a useful insight that will enhance each person\'s unique financial habits and behaviour. Such capabilities as automatic reporting and analytics, as well as the module-based architecture, ensure uninterrupted data processing and system reliability. In total, the described platform ensures a high level of ef-fectiveness and innovation in finance manage-ment, while automation, scalability, and data security are the main concerns of the system. The above approach demonstrates that AI-based solutions can totally revolutionize the way people manage, assess, and improve their finances by transforming FinSight from being a mere financial tracker to an AI-based financial management assistant

References

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Copyright

Copyright © 2026 Sarthak Rajendra Katare, Palak Pankajkumar Chhallani, Shravani Nitin Kikale, Atharva Deepak Alai, Dr. Kainjain Mahesh Sanghavi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.