SigOpt's Machine Learning Looks to Improve Big Banks' Fraud Detection

The San Francisco-based vendor uses Bayesian techniques to improve the modeling and research processes.

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Those firms with sophisticated trading strategies that have invested in building machine learning pipelines to better extract value from their data are not going to simply rip and replace with a new solution.

That thinking was a major priority when SigOpt launched last year. The San Francisco-based vendor uses Bayesian optimization—a form of machine learning—to help firms to improve their research and development models and tools. But importantly, the Bayesian platform bolts on top of a firm's

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