Ecommerce fraud is expected to cost businesses $20 billion in 2021, up 18% from 2020. Not only is fraud expensive, but fraud techniques and patterns have evolved quickly. Fraudsters are getting smarter, using more complex strategies and tools to scam businesses around the globe.

This is why we built Framer Radar, a machine-learning-based fraud detection solution fully integrated with the Framer platform. We recently shipped a series of improvements to Radar to help businesses better prevent fraud and more efficiently manage fraud workflows. Read on for the highlights, or log in to your Framer Dashboard to see Radar in action.

Detect fraud more accurately with better machine learning

To help you adapt to quickly changing fraud patterns, we've tripled the speed at which we update Radar's machine learning models.

As our network grows, Framer is more likely to see critical data inputs across multiple attempted payments, making it easier to catch fraudulent usage. And with more data, our models' recall—a standard measure of machine learning accuracy—has improved by over 20%. This means that Framer catches more fraudulent payment attempts while minimizing the impact on legitimate transactions.