EXL introduces new efficiencies for a health solutions company

Context

EXL’s client, a leading health solutions company, wanted to optimize the time required to onboard providers into its systems. EXL identified time-consuming manual steps in the client’s process workflows. The EXL team eliminated the manual steps by process automation using Python and NLP techniques. Using the new workflow, EXL was able to help reduce the provider onboarding time and accelerate the process of new provider integration.

Process

EXL redesigned the overall process of provider data mining for outreach and onboarding.

With the new flow, EXL automated the manual process of data extraction from multiple internal and external sources. This automation gave the client a productivity benefit of 70%, improved turn around time and error reduction by reducing manual steps.

The automated process was developed on Python with use of multiple libraries like Selenium, Pandas, and NumPy. The team also used Natural Language Processing (NLP) with data mining and web scraping techniques to extract data from web sources.

Automated process

Phase 1 complete

With the successful completion of phase 1 of the project, the client will continue to work with EXL to identify new candidate processes for automation across the organization in order to recognize further efficiencies.

Outcomes

YOY saving of ~$100K for client

YOY saving of ~$100K for client

Improved turnaround time by 30%

Improved turnaround time by 30%

Better provider experience and  faster revenue realization for client

Better provider experience and faster revenue realization for client

Productivity benefit of 70%

Productivity benefit of 70%

Improved quality by reducing manual errors

Improved quality by reducing manual errors