STAC-ML Working Group
The STAC-ML Working Group develops benchmark standards for key machine learning (ML) workloads in finance. These benchmarks enable customers, vendors, and STAC to make apples-to-apples comparisons of techniques and technologies.
A major focus is real-time inference of signals from event-driven financial data, an essential workload in trading and investment. The group’s first benchmark, STAC-ML (Markets) Inference, addresses this challenge.
Beyond inference, ML plays a crucial role in financial workflows, from fraud detection and risk assessment to accelerating model development and optimizing execution strategies. The rapid evolution of ML frameworks, architectures, and cloud-based services makes standardized benchmarks critical for firms evaluating new technologies.
To explore our ML benchmarks, browse the reports below. To help shape the next wave of ML benchmarking, click “Enable me!” or reach out to us.
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