Automating 10-K Analysis with AI

Key Takeaway

10-K reports contain critical financial information about companies, but analyzing them manually is very time-consuming. AI models like custom NER and ChatGPT can automatically extract key details from these complex reports and provide insights much faster.


  • 10-K reports have structured financial tables and unstructured texts detailing company's financial health and risks. Manually reading them does not scale when having to analyze thousands of reports.

  • Using a no-code AI platform like, created an AI workflow with multiple services: OCR to extract text, custom NER model to identify risk factors, table parser to extract financial tables, ChatGPT to analyze the parsed info.

  • The custom NER model successfully extracted various risk factors from the raw text such as financial, regulatory, operational risks etc. It also identified macroeconomic risks like the COVID pandemic.

  • ChatGPT provided an insightful 3-4 line analysis of the key income statement, balance sheet and cash flow tables after verifying accuracy of the figures.

  • Combination of custom AI models and generative AI enables in-depth analysis of 1000s of 10-K reports automatically, saving significant manual work. But outputs still need human verification.

  • With right level of caution around limitations of AI, such workflows greatly enhance analytical capabilities and complement (not replace) human financial expertise.

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