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Home » AI in finance
AI in Finance

AI in finance

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Artificial intelligence (AI) will profoundly change the future of finance and money. And according to a new report from Citi GPS, this could potentially push global banking sector profits to $2 trillion by 2028, an increase of 9% over the next five years.

Just as the steam engine powered the industrial revolution and the Internet ushered in the information age, AI could commoditize human intelligence. Finance, a data-rich industry whose customers are rapidly adopting AI, will be at the forefront of change.

Long-established jobs have been eliminated during past periods of technological transformation, only to be replaced by new ones. Many businesses have also disappeared. The AI ​​will repeat this cycle, possibly speeding it up.

For now, GenAI in finance is largely in the proof-of-concept stage. But we are living in a period of rapid and unprecedented transition. In this report, we discuss likely use cases in the next two years, and we also look further afield, drawing on ideas from those at the forefront.

The technology adoption strategy of most incumbents is to add it to existing products or use new technology to increase productivity. Meanwhile, startups are using new technologies to disrupt and unbundle what legacy companies are doing.

As AI-based agents, robots and the like become more widespread, how will money and finance evolve? How will the underlying concepts and structures of finance be reshaped? In a robot-to-robot world, where machines transact with minimal human intervention, what will the world of money look like?

AI could generate productivity gains for banks by automating routine tasks, streamlining operations and allowing employees to focus on higher value-added activities.

Financial industry executives are extremely optimistic about AI’s impact on profits. Indeed, 93% of those questioned in an exclusive survey expect banks’ profits to increase thanks to productivity gains. But caution will need to be exercised when it comes to implementation timelines, talent costs, increased competition, rising customer expectations, and costs associated with increased AI-driven activity.

The shift to a world powered by robots also raises questions around data security, regulation, compliance, ethics and competition. Since AI models are known to hallucinate and create information that does not exist, organizations run the risk of AI chatbots becoming completely autonomous and harming the business financially or reputationally.

AI-based customers could increase price competition in the financial sector. The balance of power could shift.

AI could be adopted more quickly by cloud-native digital businesses, such as FinTechs and BigTechs, and agile incumbent banks would quickly follow. Many incumbents, burdened by technological and cultural debt, could fall behind in AI adoption, losing market share.

All technology goes through cycles: hype, disillusionment, then mass adoption. Expectations for AI have been high since mid-2023. As financial companies grapple with the transition, the gap between hype and mass production still remains wide.

In the world of finance and beyond, most of us have already been seduced by the potential of AI to drive disruptive change. The question now is: how?

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A French quant leader introduces an AI program for finance experts.

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