Improve efficiency and reduce wastage
For insurance claims handlers, being able to identify potentially fraudulent claims early in the process is important for improving efficiency and reducing wastage. Claims handlers are able to tap their vast resources of historical data using AI to look for patterns in the data that indicate fraudulent behaviour. Here’s how it works:
- AI, and specifically machine learning (ML), can be trained to look for patterns in the data and to predict the likelihood of a claim being fraudulent right at the beginning of the process.
- This early insight can be used to improve and automate the next step of the claims handling process by removing and escalating these claims to be handling in a different way.
- AI can automate key insights (such as predicting fraudulent claims) directly to the software applications and tools being used to handle the claims process.
- This can lead to reduced costs, better efficiencies and ultimately an improved customer experience.
A proven resilient platform
Netcall’s intelligent automation offerings provide a route to enhancing and the claims process. Liberty AI, Create and RPA provide significant benefits that improve fraud detection:
- Train ML models with your historical data to proactively identify fraudulent claims early in the process.
- Present that information on-screen to a claims handler or use it directly to automate the next step of the process.
- Liberty Create applications and Liberty RPA process flows can act directly on the predictions provided by Liberty AI to deliver a seamless end-to-end automation process.
Using automation in this way provides improvements in the claims handling process. Not only can costs be reduced and efficiencies gained, patterns can be identified and reports generated that identify fraudsters and scam operations early so they can be closed down.
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