Our Client is a major US health insurance provider. One of their key plans, MAPD (Medicare Advantage Prescription Drug), caters to people aged 65 and older. The client wanted to identify dissatisfied members through ML frameworks to prevent them from filing grievances and CMS complaints through interventions. The reduced grievances and CMS complaints are expected to improve customer satisfaction & plan disenrollment. This should deliver a marked improvement in the plan’s Star rating making it attractive for prospects. More specifically, the client wanted to:

• Develop a framework to predict members who are likely to file a first or repeat grievance
• Identify top drivers that cause a member to file grievances or CMS complaints
• Enable the client’s operations team to successfully intervene with the dissatisfied member

• The problem statement was relatively more unstructured
• Highly imbalanced data- Grievance/Repeat grievance/Complaint rate is between 1- 3%