Case study

Transforming Investment Valuation: Leveraging Advanced AI and Generative AI Solutions for Improved Efficiency and Accuracy

SG Analytics Gen AI Case Study_Transforming Investment Valuation Leveraging Advanced AI and Generative AI Solutions for Improved Efficiency and Accuracy


A global investment bank is facing significant challenges in investment valuation. The traditional methods, dependent on manual processes, are fraught with potential inaccuracies and inefficiencies. This necessitates a transformative approach to overhaul and improve the valuation process. 


Data-driven Foundation: 

  • Comprehensive Data Integration: AI application to process a broad spectrum of financial documents including income statements, balance sheets, and legal documents, ensuring a solid database. 
  • Advanced Data Extraction: Utilization of AI for detailed extraction and analysis of data in various formats, such as text, tables, and images.

    Innovative Analytical Techniques: 
  • Integration of Large Language Models (LLM): Incorporation of LLMs to augment the depth and accuracy of analysis, closely mirroring expert human analysis. 

    Operational Excellence and Efficiency: 

  • Automated Valuation and Scenario Analysis: Enhancing the valuation process with AI-driven automation, capable of managing complex queries and producing comprehensive scenario analyses. 

  • Scalable and Flexible Solutions: Ensuring the system’s capability to process large data volumes and adapt to various financial situations. 

    Advanced Machine Learning (ML) Integration: 

  • Retrieval-augmented Generation (RAG) with LLM: Merging RAG with LLMs for nuanced and sophisticated data interpretation. 

  • Hybrid Data Management: Combining AI capabilities to process a range of data formats for an all-encompassing analysis approach. 


  • User-centric Design: Developing interactive and intuitive features, supporting intricate queries, and automating valuation and scenario building. 

  • Continuous Improvement Mechanism: Establishing a system that consistently evolves and adapts, learning from new data inputs to improve accuracy and relevance. 


  • Enhanced Precision and Speed: Significant enhancement in the accuracy and speed of investment valuation and financial analysis. 

  • Operational Cost Reduction: Automation of complex processes leading to considerable operational cost savings. 

  • Empowered Decision-making: Enabling investment banks to make more informed, data-driven decisions. 

  • Customization and Adaptability: Offering customized solutions to meet the specific needs of investment banks. 

  • Future Readiness: Equipping investment banks with adaptive and evolving AI technology for future challenges. 


  • The SGA strategic approach to the Generative AI application in investment banks represents a significant shift in investment valuation methodologies.
  • Leveraging AI for data processing and analysis, this approach improves accuracy and efficiency.
  • The approach also positions banks for a data-driven, adaptable, and cost-effective future, ready to tackle the evolving financial landscapes. 

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