DIGITAL BANKING
where they must balance automation efficiency with regulatory oversight requirements.
Sridhar argues that this focus on solving specific problems reflects a broader principle about how technology should integrate with business operations.“ You should be able to ask a question with a voice memo and get an answer from your enterprise data. You should be able to launch a customer app without having to write a line of code. You should be able to harness the world’ s best AI models to create agents that can learn about your business,” he says.
Market surveillance systems require balance between automation and human oversight The Department of Defense IL5 authorisation that Snowflake recently received demonstrates the security standards required for financial market infrastructure that processes sensitive trading data.
NYSE’ s surveillance operations show how this security framework applies in practice. The exchange monitors 1.2 trillion daily messages for market manipulation patterns whilst ensuring that automated systems don’ t replace human judgment in critical decisions. Traditional surveillance systems generate thousands of alerts daily, but AI helps filter these down to cases that genuinely require human investigation.
The platform achieves 90 % accuracy for AI applications, though Sridhar says the company continues working to improve these levels. The accuracy
“ We continue to be very deliberate and not stray from our two core principles around transparency and market integrity”
LYNN MARTIN, PRESIDENT, NYSE GROUP
requirements reflect the nature of financial market applications, where data quality directly impacts market confidence and participant protection.
“ We know you [ customers ] need to move ahead with confidence that the right people are using the right data for the right purpose,” Sridhar says.
This focus on data governance becomes particularly important when financial institutions deploy AI for customer-facing applications or regulatory reporting, where errors can have significant compliance implications.
“ When it comes to AI, we have developed a very deliberate approach,” Lynn explains.“ We always come back to our principles of market integrity and transparency. So we’ ve been using a version of AI – LLMs, not generative – for more than a decade to add transparency to our markets. We continue to be very deliberate and not stray from our two core principles around transparency and market integrity.”
64 July 2025