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AI powered Financial document analysis

  • Unique Paper ID: 175238
  • Volume: 11
  • Issue: 11
  • PageNo: 1888-1896
  • Abstract:
  • In order to enhance financial document analysis and improve decision-making, this study offers a comprehensive AI-driven solution utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). To analyze and interpret financial reports, the project combines advanced technologies, such as deep learning models like LLMs and information retrieval techniques like RAG. Financial analysts may take prompt action to identify trends and anomalies by using LLMs that have been trained on massive datasets of financial documents to extract and summarize key insights. RAG is employed for providing contextually relevant information based on user queries, specifically retrieving data from the knowledge base. The system also leverages the power of natural language processing through conversational AI, providing users with an intuitive interface to enhance decision-making regarding financial analysis. The architecture is built on a robust framework, ensuring real-time performance with an easy-to-use interface for financial analysts. By providing accurate financial insights and automated analysis, this system not only increases efficiency and accuracy but also contributes to the reduction of manual effort, supporting data- driven financial practices. In real-time situations, the solution is very helpful since it gives analysts the ability to make data-driven decisions, which boosts productivity and promotes informed financial strategies.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 11
  • PageNo: 1888-1896

AI powered Financial document analysis

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8.01 (Year 2024)
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