Global Private Banking

How a global private bank calibrated AI tool investment with per-team impact metrics.

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%
Before 12%
After iftrue 34%
Measured AI contribution to merged code, once attribution was on.

Code churn

-50%
Before 14%
After iftrue 7%
Share of merged code re-written within 3 weeks. Halved with better AI review flows.

Prompt to merge

-41%
Before 5.4h
After iftrue 3.2h
Median time from first AI prompt to merged PR across all tracked repos.

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