Case Study

Automated Dependent Verification

Project Goal: Automating the verification process of employee's dependents for their company's health benefits through AI and machine learning capabilities.

Role

UX / Visual Design / User Testing

Duration

6 Months

Deliverables

Research, Wireframes, Prototypes, UI/UX Design

The Problem

"Dependent documents can get accidentally verified through human error"

Dependents that get mistakenly verified for coverage when they are actually ineligible can cause thousands of dollars per year per employee. This can add up very quickly, so by using the power of our AI / ML engine we can eliminate these verification errors and save our users millions over time.

Research insights

Roughly 3.2m employees that use our Enrollment system every year.
5,000+ Employers with anywhere from 10 employees to 20k will be using this software
Right now an admin has to come in and manually reject or accept these documents, which is prone to errors

Outcome & impact

By using the power of our AI / ML engine we can eliminate these verification errors and save our users millions of dollars over time.

My design created a way for employees who have employer-provided health benefits to quickly upload their dependent documents and get verified or rejected almost instantly. Then the user is instructed to complete any actions required to continue. 5,000+ Employers with anywhere from 10 employees to 20k will be using this software and this tool will save them countless hours and millions of dollars.