Case study

Automated Financial Summary Creation and Standardization of Evaluation Parameters When Assessing Targets

Private Equity Case Study

BUSINESS SITUATION

  • The client, a leading private equity firm regularly encountered a high volume of companies  seeking fundraising opportunities. Financial models submitted in the pre-screening phase for  analysis required manual processing to generate comprehensive financial summaries
  • This manual approach often led to inconsistencies and posed challenges in maintaining the  firm's branding standards

ENGAGEMENT

  • We developed a system that efficiently extracts key financial parameters from the financial  model into a concise standardized format capturing all relevant ratios and KPIs
  • Our solution facilitates rapid and focused analysis of extensive documents.

 

SGA APPROACH

  • Designed a solution using four models: GenAI, OCR, NLP and ML
  • Textual Data Extraction: Retrieve information from databases, documents, and graphs.
  • Image Data Processing: Extract data from visual media.
  • Data Organization: Efficient data structuring and storage
  • Advanced Data Analysis: Employ programming languages for complex data
  • Data is presented in a standardized format using clients’ branding guidelines, for quick and  effective decision making
  • Tool to give a preliminary assessment based on the defined criteria


Data extraction using GenAI for automating financial summary creation for faster and more consistent deal evaluation

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BENEFITS & OUTCOME

  • Saved approx. 80% of the processing time
  • Ensured uniform presentation of financial data across all evaluations
  • Offers quick, informed decisions with preliminary assessments based on defined  criteria

 

KEY TAKEAWAYS

  • Automates the time-consuming process of data extraction, processing, and  analysis, significantly reducing the time required to generate financial summaries
  • Ensures high accuracy in data extraction and analysis, minimizing human errors  and maintaining consistent evaluation standards across all assessments

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