How America First Credit Union Built a GenAI “Decision Explainer” — With Tracing That Scales

America First Credit Union, a major credit union in the U.S. with 1.5 million members and over $20 billion in deposits, developed an internal GenAI "decision explainer" to translate complex model-driven outcomes into user-friendly narratives, addressing the challenge of explaining AI-driven decisions to business stakeholders. The explainer, built with requirements for end-to-end context, low-latency explanations, and production-grade observability, uses Celery to parallelize tasks, enabling faster delivery of answers by breaking down explanations into multiple LLM sub-answers. Integrated tracing using Arize AX ensures performance monitoring and debuggability, allowing seamless integration with other projects. Initial results from the rollout indicate improved usability for business users, who receive plain-English narratives, and enhanced engineering efficiency. The explainer not only provides a comprehensive view of decision processes but also demonstrates a strong economic rationale by reducing ad-hoc efforts and accelerating iteration, achieving over 500% ROI in its first year.

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