The increasing use of artificial intelligence in financial systems is driving a shift towards machine-executed transactions, presenting new challenges related to control, oversight, and infrastructure, according to Microsoft and Chainalysis executives. Microsoft's corporate vice president of worldwide financial services, Bill Borden, stated that legacy systems will face growing pressure as transaction demands become more complex. The turning point occurs when latency, scale, and complexity start to impact a company's ability to compete, prompting firms to reevaluate their system architecture, he explained 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 adhered to policy when decisions are made without direct human input. Jonathan Levin, co-founder and CEO of Chainalysis, pointed to the crypto sector as a working model of automated finance.
Blockchain networks process large volumes of transactions through smart contracts and software-driven wallets, creating an environment similar to agent-based systems. Looking ahead, both executives anticipate a mix of systems to coexist. Levin predicted that the majority of commerce will be settled on public infrastructure in 10 years, while Borden envisioned a more integrated approach linking public blockchains, private networks, and existing rails.