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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...
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Datactics Survey to Gauge Data Chiefs’ Pressure to Adopt AI Amid New Risks
The headlong rush to adopt artificial intelligence poses multiple risks to financial institutions that don’t take the necessary preparatory steps before implementation. One potential source is the increasing AI-savviness of company employees. As they become accustomed to using the technology on consumer devices and websites, there is a greater risk they’ll inadvertently leak or compromise...
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AI in Capital Markets Summit London
Now in its 3rd year, the AI in Capital Markets Summit returns with a focus on the practicalities of onboarding AI enterprise wide for business value creation. Whilst AI offers huge potential to revolutionise capital markets operations many are struggling to move beyond pilot phase to generate substantial value from AI.
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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...


