Global Private Banking
How a global private bank calibrated AI tool investment with per-team impact metrics.
"Before iftrue we had no way to tell if AI tools were actually making us faster. Now we see AI code ratio, churn, and prompt-to-merge per team, and we sponsor the tools that prove their worth."
CTO
Global Private Banking
The Challenge
The bank had paid for Copilot seats for a year without knowing if they were worth it. Engineering leadership needed to justify AI tooling spend to finance and risk, and had no per-team or per-tool visibility into actual impact.
The Solution
iftrue deployed on-prem inside the bank's private cloud. AI code ratio, churn, and prompt-to-merge are now tracked per team and per AI assistant. Leadership sponsors the tools that prove their worth, and sunsets the ones that do not.
The Results
First full quarter after on-prem rollout.
AI code ratio
+183%Measured AI contribution to merged code, once attribution was on.
Code churn
-50%Share of merged code re-written within 3 weeks. Halved with better AI review flows.
Prompt to merge
-41%Median time from first AI prompt to merged PR across all tracked repos.
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