The increasing use of artificial intelligence in financial systems is driving the industry towards a model where machines handle transactions on a large scale, posing 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 mounting pressure as transaction demands become more complex, with the breaking point occurring when latency, scale, and complexity start to hinder a firm's ability to compete. This necessitates a reevaluation of how systems are built. Borden emphasized that the focus has shifted from the capability of automation to issues of trust, with the key question being whether technology can be trusted and audited.
Microsoft is developing tools to manage this transition, including systems that assign identities and permissions to AI agents and track their actions. In regulated environments, firms must 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, noted that the crypto sector provides a working model of automated finance, with blockchain networks processing large volumes of transactions through smart contracts and software-driven wallets, creating an environment similar to agent-based systems. Levin highlighted the experience in risk management, citing efforts to track illicit funds across thousands of wallets as an example of the monitoring required in systems where transactions occur at scale without human input. Both executives anticipate a mix of systems coexisting in the future, with Levin predicting that most commerce will be settled on public infrastructure within a decade, while Borden envisions a more integrated approach combining public blockchains, private networks, and existing systems.