Reducing Human Error Using AI/ML with Mainframe Data Entry for a Major Health Solutions Provider

Image
Case Study: AI/ML Solutions

Reducing Human Error Using AI/ML with Mainframe Data Entry for a Major Health Solutions Provider

SUMMARY

A large health solutions wanted to prepare for future cloud migration while using AI/ML technologies to automate many functions with data entries. Spearhead Technology developed a solution with UiPath, with custom ML models and NLP to reduce human error and automate data entry processes.

Challenges

  • Client uses mainframe to run its bread-and-butter systems where data entries are performed manually.
  • The client wants to automate critical tasks of the process to prepare for future cloud migration while using AI/ML technologies to automate many functions in the manual process reducing errors and improving the overall claims processing time.

Solutions Offered

  • The solution provides automation of thousands of data elements pulled from many emails and spreadsheets by various users and manually entered into multiple modules running on AS400. The automation is developed using UiPath, while custom ML models are designed to enable automation robots to reason using NLP and computer vision techniques to help minimize human judgment errors, aid in interpretations, support tracking and auditing, and drive a much faster resolution on pending issues.