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Data is the fuel that keeps modern financial institutions’ motors running but if that data can’t be trusted then the decisions made based upon it, or the uses to which its put, will be compromised. That’s especially important for data that’s fed into artificial intelligence models. If the data isn’t clean, accurate and complete, then...
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The friction inherent in mobilising data is a perennial problem for financial institutions, who have spent the last decade perfecting the passive data stack – investing heavily in cloud warehouses, governance frameworks and ETL pipelines designed to move data for human consumption. However, the operational reality remains plagued by manual intervention. Recent developments in agentic...
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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...



