How is the Network Risk Indicator determined? Follow
The panel surfaces risk signals that explain and provide context behind the Network Risk Indicator. Our product and engineering teams tested hundreds of attributes that are within our Identity Network. After this testing, we chose a combination of 147 features based on their proven predictive value. We trained our random forest machine learning model to look across these 147 features, giving equal weight to each input type. Then, our model surfaces the top features based on their predictive power. These top features are the risk signals you find in the panel, and they influence the Risk Indicator to be low, high, or uncertain. The Risk Indicator is a machine learning prediction, derived from the Ekata Identity Network, that provides insight into how risky a digital interaction is based on activity patterns of core identity elements.
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