International Journal of Innovative Research in Computer and Communication Engineering

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TITLE LLM Based Finance Assistance System
ABSTRACT In today’s fast-paced, data-centric world, individuals are increasingly required to make complex financial decisions without possessing the necessary financial expertise. Traditional advisory services, though effective, often remain inaccessible due to their high cost, limited availability, and time-consuming nature. While robo-advisors have emerged as a more affordable alternative, their rule-based frameworks restrict adaptability and prevent truly personalized guidance. To overcome these limitations, this project proposes an intelligent conversational financial assistant powered by Large Language Models (LLMs). The system uses advanced transformer-based architectures, such as GPT, LLaMA, or comparable models, fine-tuned on domain-specific datasets including investment reports and real-time market information. By interpreting natural language queries, the assistant delivers context-aware financial insights and actionable recommendations across key areas such as budgeting, investment planning, goal tracking, and risk assessment. This approach aims to democratize financial advisory services by making them more intuitive, adaptive, and accessible, especially for users lacking formal financial training.
AUTHOR PROF. WASEEM KHAN, NISARGA PATIL, PREETHI G V, SAHANA RAIKAR, BHUVANESHWARI B Assistant Professor, Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India UG Student, Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India
VOLUME 177
DOI DOI: 10.15680/IJIRCCE.2025.1312031
PDF pdf/31_LLM Based Finance Assistance System.pdf
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