The increasing use of artificial intelligence in financial systems is driving the industry towards a model where machines execute transactions at scale, presenting new challenges related to control, oversight, and infrastructure, as stated by Microsoft and Chainalysis executives. Bill Borden, Microsoft's corporate vice president of worldwide financial services, warned that legacy systems will face mounting pressure as transaction demands become more complex. The tipping point is reached when latency, scale, and complexity start to impact a company's ability to compete, forcing firms to reassess how their systems are built, he said at an event in New York City.
While automation has long been a part of finance, Borden emphasized that the focus is now shifting from capability to trust. The question is no longer about whether technology can automate tasks, but rather whether it can be trusted and audited.
To manage this transition, Microsoft is developing tools that assign identities and permissions to AI agents and track their actions. In regulated environments, companies must be able to demonstrate what controlled a system and whether it followed policy when decisions are made without direct human input. Jonathan Levin, co-founder and CEO of Chainalysis, noted that the crypto sector already provides a working model of automated finance, with blockchain networks processing large volumes of transactions through smart contracts and software-driven wallets.
This creates an environment similar to agent-based systems, and Levin stated that the crypto sector has been preparing for this moment long before other parts of the financial services industry. Looking ahead, both executives expect a mix of systems to coexist, with Levin predicting that the majority of commerce will be settled on public infrastructure in the next decade, while Borden envisioning a more integrated approach that links public blockchains, private networks, and existing systems.