The trends and insights leaders need to govern what AI is building in finance in 2027.
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90% of technology professionals now use AI at work, and the volume of code entering organizations is rising faster than at any point in software history. The organizations capturing the productivity gains without inheriting the risk share one trait: they can see what they are running, measure quality continuously, and prove it when a regulator asks. Six chapters break down where financial services stands today.
Financial institutions handle some of the most sensitive data of any industry. Royal Bank of Canada alone has seen its LLM token usage surge more than 500% in the past year.
That's what's recovered by moving a system from 2-star to 4-star maintainability. Banks that fail to modernize could lose more than $57 billion by 2028, with missed payments revenue accounting for 42% of that figure.
Accenture research shows banking technology costs have grown roughly 4x faster than revenue over 15 years, with up to 70% of IT spend now going toward keeping existing systems running.
The average financial-services breach cost $6.3 million in 2026, the second-costliest industry after healthcare. The average system carries 20 critical security findings.
Nearly 60% of AI leaders cite legacy-system integration as their top barrier to deploying agentic AI. KPMG found core banking platforms are now the single biggest technology risk banking executives cite.
Roughly 1.5% of enterprise systems in production currently qualify as AI systems. US regulators have already extended bank model risk guidance to AI and machine learning models for the first time since 2011.
The sector is, in many respects, well positioned in the AI era: its maintainability figures are the strongest of any industry we benchmark. In other respects, it's exposed to risk: its security figures are not comforting, and a defect in AI-assisted code doesn't stay contained to the institution that wrote it, not in a sector with this much at stake.
Each chapter speaks to a different seat at the table. Start with yours, then read the rest to understand what your peers are working against.
Banking technology costs have grown roughly 4x faster than revenue over the past 15 years, with up to 70% of IT spend now going toward keeping existing systems running.
Chapters 02, 03Royal Bank of Canada's LLM token usage alone surged more than 500% in the past year. See what agentic coding actually costs, and where AI output needs a harness before it reaches production.
Chapters 01, 06The average financial-services breach already costs $6.3 million, the second-highest of any industry. See where AI-generated and open-source code is carrying more risk than your review process can catch.
Chapter 04Core banking platforms are now the single biggest technology risk banking executives cite, ahead of cybersecurity. Legacy integration is already the top barrier to deploying agentic AI.
Chapter 05