VHI Case Study

Claims validation process automation

Deployment of Intelligent Document Processing reduces insurer’s claim validation time.


In brief

  • The successful deployment of IDP provided a strategic framework for the insurer's future AI adoption and digital transformation initiatives.
  • Automation through Intelligent Document Processing reduced operational costs and resources needed, while managing higher claim volumes and maintaining service level.
  • The integration of AI-powered IDP significantly improved claim validation efficiency and accuracy, reducing reliance on manual processing.

Opportunity

A leading insurance company had identified challenges in its claim validation process. The insurer was primarily concerned with two issues: growth in claims volumes leading to downstream delays as a consequence of heavy reliance on manual processing potentially compounded by a surge in claims processing costs due to that increase in claim submission volumes.

To manage its claim validation process, the insurer had engaged external assistance to review claims documents. However, they continued to be challenged to keep pace with the timely completion of reviews due to the growing complexity of claims and increasingly intricate documentation requirements.

Consequently, the insurer saw challenges in maintaining their service levels and a risk of average response time increase.

Furthermore, the insurer was confronted with the potential for rising operational costs. With claims growing annually, the insurer projected a corresponding rise in the claim processing cost from their existing approach. Without streamlining and automating processes, the health insurer expected its cost burden to grow substantially with an over-reliance on a human centric response to scaling.

Solution

To improve the service levels and for claims validation, retain/ improve accuracy levels and to reduce projected increase in costs, the insurer integrated an AI-powered automation feature into its existing platform. This advanced solution employed cognitive automation with artificial intelligence to swiftly interpret complex receipts, including those that were handwritten or creased.

The deployment of the AI-driven Intelligent Document Processing (IDP) module empowered the insurer to accurately process a wide array of documents, including non-digital and handwritten forms. This innovation not only automated the navigation of client systems for claim handling but also ensured precise validation of submitted information against the corresponding documentation, such as receipts. Introduction of the IDP module was a strategic move to improve operational efficiency and accuracy in the claim validation process.

The integration of IDP, driven by robotic process automation, significantly reduced the time required for receipt interpretation and validation and streamlined the overall claims processing.

Benefit

Deployment of the IDP module helps to reduce manual processing and thereby lower the costs associated with the process of claim validation. The automation provided by the IDP module reduced the workload and resources needed to validate claims and other document-related tasks.

The implementation of the AI-driven IDP module has delivered improvements and will help the insurer shape the future with confidence:

The secondary benefit of using digital capabilities to assist the processing and remain within key service level targets also has the benefit of call avoidance from customers ringing to check the status of their claim.

The technology’s application across the group enabled us to develop a strategic roadmap for the insurer’s broader AI adoption.

Summary

A leading insurance company integrated an AI-powered Intelligent Document Processing (IDP) module to help overcome challenges with claim validation and response times. The integration of IDP, driven by robotic process automation, significantly reduced the time required for receipt interpretation and validation and streamlined the overall claims processing. It reduced costs, enhanced service levels, and provided a strategic roadmap for future AI adoption.


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