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.

Summary

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 Kudr.ai, 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.