The increasing use of artificial intelligence in financial systems is driving a shift towards a model where machines handle transactions on a large scale, presenting new challenges related to control, oversight, and infrastructure, according to executives from Microsoft and Chainalysis. Bill Borden, Microsoft's corporate vice president of worldwide financial services, stated that legacy systems will face growing pressure as transaction demands become more complex, with the tipping point occurring when latency, scale, and complexity begin to impact a company's ability to compete.
This will force firms to reevaluate how their systems are built, he said at an event in New York City. While automation has long been a part of finance, Borden noted that the focus is now shifting from capability to trust. The question is no longer whether technology can automate tasks like executing a hedging strategy, 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, firms must be able to demonstrate what controlled a system and whether it followed policy when decisions are made without direct human input, Borden said. Jonathan Levin, co-founder and CEO of Chainalysis, pointed to the crypto sector as a working model of automated finance, where blockchain networks process large volumes of transactions through smart contracts and software-driven wallets, creating an environment similar to agent-based systems.
The experience of the crypto sector also extends to risk management, with efforts to track illicit funds across thousands of different wallets serving as an example of the kind of monitoring needed in a system where transactions happen at scale without direct human input. 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 10 years, while Borden envisions a more integrated approach that links public blockchains, private networks, and existing systems.