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.


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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