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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...
The strategic argument for treating market data as a product rather than a cost has arguably been won. What remains stubbornly unresolved is what comes next: measuring the return on data investments, breaking the hoarding cultures that prevent data from flowing across the enterprise, and building infrastructure robust enough to support AI at scale. Those...
The London sustainability breakfast is part of the global roundtable thought leadership event series hosted by RepRisk in key markets, including, New York, Toronto, London, Frankfurt, Oslo, Copenhagen, Stockholm, Hong Kong and Singapore in 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...