Smarsh

Recorded Webinar: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research

For many quantitative trading firms and asset managers, building a self-provisioned historical market data environment remains one of the most time-consuming and resource-intensive steps in establishing a new research capability. Sourcing data, normalising symbologies, handling corporate actions and maintaining infrastructure can take months and absorb significant budget before a single model is tested. At the...

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Data and Governance Take Centre Stage in AI Adoption

Financial institutions are making significant progress in deploying agentic AI, but differences in data infrastructure, governance and commercial priorities are creating a widening gap between those scaling the technology and those still experimenting, according to new research from A-Team Group. The study, commissioned by LSEG Data & Analytics and based on responses from 200 senior...

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Data Management Summit New York City

Now in its 17th year, Data Management Summit (DMS) NYC returns in September 2027, to explore how to use data and AI to drive measurable business outcomes - reliably, repeatedly and at scale.

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...