The data doom loop

Financial institutions are investing heavily in data, yet many remain stuck in a "data doom loop"—where complexity grows while trust erodes. Why is this happening, and what’s the way forward?

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• Rising costs, stagnant progress – Data spending is up 8-16% annually, but improvements in data quality and usability remain flat.
• Regulatory and real-time pressures – Global institutions struggle with compliance, high-frequency trading, and managing vast, fragmented data systems.
• Flaws in centralized data strategies – Lake house architectures help but can’t replace specialized databases tailored to different financial needs.
• AI & governance challenges – AI-driven finance needs high-quality data, but governance efforts often fall short of delivering business value.