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Fraudulent Claims

  • Insurance claim fraud and abuse can cost insurers millions, if not billions of dollars a year.
  • It is not feasible to investigate every claim due the volumes of incoming claims.
  • This application uses historical insurance claim data to help insurance companies automatically prioritize investigations.
  • Focus efforts on investigating cases that have the high likelihood of fraudulent activity.
  • Reduce time spent on pursuing legitimate claims, increasing customer satisfaction.
GET APP Feature Labs makes it easy to connect to your data and deploy

How it Works

This application is ready to be deployed to provide value right away.

To get started, you just need to map your data to the required inputs. From there, Feature Labs’ data science automation will take care of the rest. The application will automatically

  • Extract historical examples to learn from
  • Identify predictive signal using Deep Feature Synthesis
  • Select and optimize a machine learning model for deployment

This application is not a black box. After the initial integration is made, it is simple for a developer to add additional data sources, tweaking the prediction problem, and deeply inspect how each step in the process works.

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