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Case Study

Unum leverages natural language processing (NLP) to cut email response time by 50%

  • Automatically triaged emails and classified topics via Pega (Natural Language Processing) NLP
  • Developed and integrated service to existing CRM applications
  • Completed development in less than six weeks

We were able to ultimately decrease the turnaround times on the email channels…[by] about 50% and that's really significant for our operational teams.

The Business Issue

Unum is a leading provider of financial protection benefits in the U.S., U.K., and Poland. In 2018, the insurance provider protected 38 million workers and their families. Unum’s U.S based contact center operational team, Ask Unum, is staffed with 150 agents that focus on connecting with plan administrators and brokers regarding topics including member demographic changes, evidence in insurability, and more. The team was experiencing high email volumes that resulted in agents having to manually triage messages. With all of the permutations in various requests, Unum knew they needed a sophisticated solution that would intelligently interpret these differences.

The Solution

Unum began investigating advanced capabilities of the Pega platform to help automate and triage emails. The insurance provider chose to implement Pega Natural Language Processing (NLP) as a service to address this need. In less than six weeks, Unum was able to complete development and deployed across their email intake channel. Pega NLP now analyzes email messages and carries out topic classification across their CRM system. This has reduced turn-around times by 50% and resulted in improved case and routing accuracy across the internal contact center operations team and outside Business Process Operations (BPO) provider.

The Results

  • Decreased email channel turnaround time by 50%
  • More emails are routed to the provider than originally anticipated
  • Completed development in 6 weeks
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Industry: Insurance Product Area: Customer Service Solution Area: Customer Service
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