Agentic finance is changing how companies are analyzed. AI can now examine hundreds of pages of corporate disclosures, compare years of financial data, and identify patterns that human readers may miss.
Michael Diegelmann joins Dietmar Fischer to discuss Warren Wise, a multi-agent financial-analysis system based on principles associated with Benjamin Graham, Warren Buffett, and Charlie Munger.
Michael explains how CFOs and investor-relations teams can test annual reports, earnings materials, and equity stories before publication. The system can identify potential weaknesses, generate difficult investor questions, compare companies through a consistent methodology, and show how banks or institutional investors may interpret the information.
The conversation also explores the limits of financial AI. A professional system must distinguish between a missing value, a dash, a negative number, and an unusual human event. Without reliable data, guardrails, and context, a convincing AI answer can still be wrong.
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Michael argues that AI will make corporate finance faster and more transparent. It may also give executives an independent way to challenge internal assumptions before the market does.
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Dietmar Fischer is a podcaster and AI marketer from Berlin.
If you want help with AI strategy or digital marketing, visit:
βThe thing is, you can't hide stuff anymore.β
βThere's a new sheriff in town, and this is called artificial intelligence.β
βEverything may sound or look bad, and still isn't.β
00:00 Meet Michael Diegelmann
01:59 Building a Synthetic Warren Buffett
05:09 Testing an Equity Story Before Publication
08:07 The Patterns Hidden in Corporate Reports
15:41 The Coming Tsunami of Transparency
18:08 Why Financial AI Needs Better Data and Guardrails
28:12 Agentic Finance, Jobs, and the Future of Corporate Leadership