Optimizing Health Insurance Claims Processing & Fraud Detection with AI

Shift enables health insurers to prevent fraud, waste, and abuse prior to payment.

The healthcare industry has massive amounts of data available in health records, clinical trials, and in billing & claims processing systems. However, it’s still challenging for health insurers to unlock the value buried in this data to accelerate claim payments, reduce fraud, drive better patient outcomes, and maintain regulatory compliance.

Shift Fraud, Waste, and Abuse Detection

Shift helps health insurers effectively identify potential fraud, waste, and abuse in the claims process. It’s an automated, AI-native, SaaS solution that works with existing claims platforms.

  • Shift Enables Health Insurers to:
  • Identify more potential fraud, waste, and abuse cases
  • Reduce fraud losses and improper payments
  • Lower false positives and focus claims handler efforts
  • Improve investigator efficiency and shorten decision timeframes
  • Pay valid claims quickly, with confidence

Shift Claims Automation for Health

Shift’s AI Claims Automation solution enables health insurers to settle and pay a greater number of high-volume, low-touch claims quickly and confidently.

  • Shift Enables Health Insurers to:
  • Improve the claims experience
  • Settle and pay straightforward, valid claims more quickly
  • Increase claims handler productivity
  • Reduce claims leakage
  • Easily integrate automation with their existing claims platforms

Trusted by forward-thinking insurers globally.

Shift Perspectives

First Central Goes Live with Shift Insurance Suite to Mitigate Fraud in Application and Claims Processes

February 23, 2021

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Webinar – AI: Putting Insurers on the Path to Better Decision Making – March 16th

February 22, 2021

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Shift Technology and CRIF Collaborate in the Fight Against Insurance Fraud

February 16, 2021

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Event – Insurance Innovators Fraud & Claims – March 10th

February 11, 2021

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Learn how Shift can help you transform insurance decision making

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