As machine learning systems mature in fintech organizations, a seemingly innocuous practice often emerges that can create significant operational risk: using staging environments for model validation and testing at scale. What starts as a pragmatic solution to data volume limitations can quickly evolve into a critical dependency that undermines the very purpose of environment separation.
