The OpenML Engine: How Data Scientists Can Bring Their Own Machine Learning To Fight Fraud

How will you stay ahead in the data science arms race?

Banks are shoring up AI-enabled fraud prevention resources, and they’re striving to grow their data science teams amid a talent shortage. Meanwhile, fraudsters are rapidly evolving their tactics, so banks are turning to third party innovators who have spent years perfecting machine learning-based fraud science. The winners in this adversarial climate will be the banks that combine the best of in-house data science tools and externally developed data science tools for fighting fraud with machine learning.

The problem is that the most advanced fraud-fighting vendors often constrain your data scientists with singular data science environments and proprietary frameworks.

That’s why Feedzai built the OpenML Engine. We believe your data scientists should have the flexibility to build models in any language, using any library, and on any platform. They they should be free to import these approaches to a platform that was purpose-built, from the ground up, to fight new and evolving financial crime.

Read this ebook and learn:

  • The full suite of integrations for training and importing models inside Feedzai
  • The architectural diagram of how The OpenML Engine fits with the rest of the Feedzai platform
  • Why bringing existing models inside Feedzai will uplevel your fraud prevention


Download the ebook