This brief outlines how the HPE Machine Learning Platform helps financial services and insurance organizations operationalize AI in highly regulated environments. It addresses challenges including strict compliance requirements, governance of unstructured data, heterogeneous data sources, reproducibility for audits, and the high cost of GPU-based infrastructure. The platform delivers an end-to-end AI lifecycle with integrated data management, accelerated model training, and scalable inference using open-source technologies such as KServe. Its open architecture avoids vendor lock-in and supports deployment close to sensitive data, on-premises or in the cloud. With built-in experiment tracking, data lineage, and reproducibility, the platform enables trusted AI for use cases such as fraud det

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