Welth - AI Powered Finance Management System

Abstract

The increasing reliance on digital transactions and online financial services has created a strong demand for intelligent and efficient financial management systems. This project presents “WelthAI,” anAI-poweredfinancial managementplatformdesigned to simplify expense tracking, budgeting, and financial analysis for users. The system leverages modern full- stack technologies to provide a responsive and user- friendly interface, enabling users to manage their financial activities seamlessly. A key feature of the platform is the integration of artificial intelligence for automatedreceiptscanning,whereimportantdetailssuch as transaction amount, date, and vendor information are extractedfromimagesusingopticalcharacterrecognition techniques. This significantly reduces manual data entry and improves data accuracy. The system further processesthecollecteddatatogeneratereal-timeinsights throughinter activedash boards,helpingusersunderstand their spending patterns and make informed financial decisions.Inaddition,secureauthenticationmechanisms and scalable backend services ensure data privacy, reliability, and efficient performance. By combining automation,intelligentprocessing,anddatavisualization, the proposed system provides a comprehensive solution for modern financial management and enhances overall financial awareness among users.

Introduction

The text describes the design and development of an AI-powered financial management system that improves traditional finance tracking by replacing manual, error-prone processes with intelligent automation and real-time analytics.

It explains that traditional financial tools rely heavily on manual data entry, leading to inefficiencies, inaccuracies, and limited insights. To solve this, the proposed system uses Artificial Intelligence (AI) to automate tasks such as expense categorization, fraud detection, and especially receipt scanning using OCR (Optical Character Recognition), which extracts transaction details like amount, date, and vendor automatically.

The system is built using a modern full-stack architecture:

• Frontend: React.js, Next.js, Tailwind CSS, ShadCN UI
• Backend: Supabase, Prisma
• Authentication: Clerk
• Background processing: Inngest
• Security: Arcjet
• AI processing: Gemini AI for OCR-based receipt analysis

It provides key features such as:

• Automated expense tracking and categorization
• Real-time financial dashboards and insights
• Secure authentication and data protection
• Event-driven background processing

The methodology includes a layered architecture (UI, logic, database, AI processing) and a workflow from user login → data input/receipt upload → AI extraction → storage → analysis → dashboard visualization.

The literature review highlights that AI in finance is widely used for prediction, fraud detection, and risk analysis, but most systems lack full integration, transparency, and real-time usability. The research gap is the absence of a comprehensive, scalable, AI-integrated financial platform combining automation, analytics, and user-friendly design.

The problem identified is that existing financial tools still depend on manual input, lack intelligent insights, have weak automation, and often suffer from poor security and scalability.

Conclusion

TheAI-poweredfinancialmanagementsystempresented in this research provides an effective solution for simplifying and automating personal financial activities. By integrating artificial intelligence with modern full- stack technologies,the system successfullyaddresses the limitations oftraditional financial management methods. The platform enables users to track expenses, analyze financial data, and gain meaningful insights through an intuitive and interactive interface.The incorporation of AI-based receipt scanning significantly reduces manual effort by automatically extracting and organizing financial information. This improves accuracy and enhancestheoverallefficiencyof data management. The use of a scalable backend and secure authentication mechanisms ensures reliable performance and protection ofsensitiveuserdata.Furthermore,thesystemoffersreal- timevisualizationoffinancialactivities,allowingusersto better understand their spending behavior and make informed decisions. The modular architecture and integrationofevent-drivenprocessescontributeto smooth system operation and flexibility for future enhancements.In conclusion, the proposed system demonstrates how the combination of artificial intelligence and modern web technologies can transform financial management into a more intelligent, efficient, anduser-friendlyprocess.Itprovidesastrongfoundation fordevelopingadvancedfinancialsolutionsthatcanadapt to evolving user needs and technological advancements.

References

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Copyright

Copyright © 2026 Prof. Priya Meshram, Mr. Deepak Niwalkar, Mr. Chaitanya Karmore, Mr. Deepam Nerkar, Mr. Devesh Bhujade, Mr. Aayush Atkari, Mr. Chaitanya Jumle. 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.