Feedzai Unveils AutoML: Automated Machine Learning That Fights Fraud in a Fraction of the Time

Feedzai AutoML allows for automated feature engineering, machine learning model creation, and more, providing industry-leading results in a fraction of the time

Feedzai announced today that it is bringing AutoML to the fraud space, an industry first. By automating tasks such as feature engineering and machine learning model creation, data scientists are now able to create fraud prevention solutions as much as 50 times faster than is possible with the traditional data science workflow.

“AutoML can get virtually the same results in a few hours, that would normally take a team of data scientists weeks to achieve.”

Increasingly intelligent fraud attacks require teams to act faster than ever to fight evolving fraud risks on multiplying fronts. Feedzai AutoML enables teams to deliver results faster and to quickly expand to new use cases, channels, and geographies.

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Now, data scientists can quickly generate the most relevant features and models, and adapt more quickly to fast-evolving fraud schemes and attack vectors. Feedzai AutoML works by automating and integrating the most repetitive and time-consuming steps in the data science pipeline, freeing data scientists to perform more consequential tasks. At a time when the demand for data scientists is growing more quickly than ever, Feedzai AutoML allows banks and other financial institutions to massively augment their data science teams.

“We’ve proven that Feedzai AutoML can get virtually the same results in a few hours, that would normally take a team of data scientists weeks to achieve,” says Pedro Bizarro, Feedzai Chief Science Officer and co-founder. “This is a ground-breaking advancement for Feedzai, but even more so, it’s something that will provide a substantial competitive advantage to our customers.”

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Feedzai AutoML cutting-edge innovation relies on an advanced type of semantic-based automatic feature engineering, where the machine recognizes the semantics associated to each field enabling the engine to automatically build context-aware features. This functionality is greatly empowered by Feedzai AutoML model selection capabilities: the most competitive algorithms are automatically trained, optimized and compared so that the best models are recommended at the end of the process.

Feedzai AutoML follows the April release of Feedzai OpenML, which allows data scientists to import open source and third party tools to the Feedzai Risk Engine. Feedzai AutoML and OpenML work in conjunction, creating flexibility and speed previously unseen in the fraud prevention industry.

“Our customers spoke, and we listened,” says Nuno Sebastiao, Feedzai CEO and co-founder. “AutoML and OpenML are the two latest examples of Feedzai’s dedication to bringing the market the best possible fraud prevention solutions. In the months to come, you can expect to see more and more of these kinds of innovations.”