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for potential manipulation patterns including spoofing, where traders submit large orders they intend to cancel to move prices artificially.
This surveillance work has traditionally relied on systems that flag suspicious patterns for human review, but the exponential growth in message volumes means compliance teams cannot manually investigate every alert. That bottleneck has pushed NYSE towards AI solutions that can filter genuine anomalies from routine trading activity, allowing human analysts to focus on cases that actually require investigation.
NYSE has worked with Snowflake for six years, initially for data storage before expanding into AI applications through the platform’ s Cortex capabilities. The partnership reflects the exchange’ s focus on maintaining data quality whilst scaling operations to handle exponential growth in both trading volumes and regulatory requirements.
“ What really powers AI is that good source of truth. If you don’ t have a source of truth, you’ re going to have unfortunate outcomes,” Lynn says, speaking on stage at Snowflake Summit 25.
The exchange has actually used machine learning models for over a decade to enhance pattern recognition, but newer generative AI capabilities enable natural language queries of surveillance databases and automated preliminary investigations. This approach allows the compliance team to maintain the same level of oversight whilst handling far larger data volumes,
“ What really powers AI is that good source of truth. If you don’ t have a source of truth, you’ re going to have unfortunate outcomes”
LYNN MARTIN, PRESIDENT, NYSE GROUP
58 July 2025