What happens when machines think about money? - Podcast with Santiago Walliser

What happens when artificial intelligence starts to understand financial markets - perhaps even better than we do? In this episode of the podcast "AI and Society - Paths to the New World", Santiago Walliser, PhD student in Quantitative Finance, talks about the silent revolution in investment: when satellite images, news sentiment and data models suddenly predict stock market prices.

But what does this mean for advisors, investors - and our trust in money? Santiago explains how alternative data and AI analyses are providing new insights, why "crowdedness" is becoming a problem and why human intuition remains indispensable. A conversation about the future of the financial world - between algorithms and a sense of proportion, between dashboards and gut instinct.

Parking lot analyses from space, cell phone movements, media moods: What sounds like sci-fi has long since become reality for financial professionals. Hedge funds have Walmart parking spaces counted by satellite or analyze the shadows cast by oil tanks in order to identify market trends earlier. In the podcast "AI and society - paths into the new world" Christoph Soltmannowski talks to Santiago Walliser, PhD student in Quantitative Finance, about how artificial intelligence (AI) enables new insights into the economy and society through creative data analysis - and why communication professionals play a central role in this.

Podcast on Youtube

Alternative data: Parking lots, patents and posts

Traditionally, analysts rely on hard figures such as share prices or balance sheets. Alternative data broadens this view: Satellite photos, patent data, social media posts or news texts provide early indicators before they appear in official figures. In this way, customer flows, market sentiment and innovative strength can be identified even before the quarterly reports are published.

In the podcast, Walliser explains how AI converts unstructured data - such as news articles - into structured information, evaluates it and links it to share price trends. An accumulation of positive media reports can point to rising shares, negative ones to declines.

View from above: Shadows and signals

The example of the satellite analysis of Walmart parking lots is impressive. More cars mean more customers - and therefore rising sales. The method is even more sophisticated in the oil market: AI systems use the shadows cast by fuel caps to recognize how full oil storage facilities are. This makes it possible to estimate global stock levels and predict price movements - an information advantage that can be worth millions.

However, Walliser emphasizes: "Whether this makes social sense is questionable." After all, such exclusive data sources create advantages for financially strong players - an information inequality that raises ethical questions.

Crowdedness and creativity

When many people use the same data sources, they lose their value - a phenomenon that Walliser calls "crowdedness". Those who combine data creatively, such as patent data with media coverage or mobile phone data with weather information, remain successful. These unconventional connections create new insights before the mainstream discovers them. "The future does not lie in the amount of data, but in its clever combination," says Walliser.

Conclusion: creativity remains human

AI delivers speed and precision - but meaning, context and empathy remain human. The combination of both worlds opens up opportunities far beyond the financial sector. Those who use data creatively and communicate it in an understandable way are helping to shape the new era of artificial intelligence. Because in the end, it's not the machine that determines success - it's the person who knows how to speak its language.

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The video podcast "AI and Society - Paths into the New World" is produced by the Text Academy Foundation. Two episodes are published monthly, on Spotify, Youtube and other podcast platforms.