When AI Outperformed Financial Analysts – Alex Kim

In this episode Glenn Hopper talks to the researcher responsible for the groundbreaking study which found that AI is better at conducting financial analysis than humans. Alex Kim, University of Chicago Booth School of Business, provides a full overview of his findings, methodology and the impact on FP&A, CFOs and finance from the attention-grabbing study “Financial Statement Analysis with Large Language Models”. The analysis, which made headlines across the world, found AI produces a 60% rate of accuracy in predictive financial performance. Human experts’ accuracy tends to fall between 53% and 57%.

In this episode Alex Kim reveals the implications for finance professionals:
 

• Alex’s finance background – from a Master’s degree in Business Administration to a Accounting and a dual Bachelor’s degree in Economics and Business Administration- to his doctoral and PHD career
• How he self taught himself coding and AI
• Practically how do finance pros take the insights from this paper and use them in their day to day?
• Why the model didn’t do so well with loss-making or startup companies 
• Improving on the performance models using a startup company data
• How can you combine AI and Human Intelligence 
• What humans can do better than AI in financial forecasting 
• Future research projects into information processing for investors 
• How to keep up to date on the latest ground breaking research in AI and Finance
• My military experience stationed with US soldiers in South Korea
• My favorite Excel feature ( and why one thing about Excel still cannot be rivaled).

Read the full paper here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4835311

Check out the analyzer for yourself here: https://chatgpt.com/g/g-9P3sIn487-financial-statement-analyzer

Follow Alex Kim on Linkedin Ph.D. Student at the University of Chicago: https://www.linkedin.com/in/alexgunwookim