The claims processing department of a large US health insurance company works to ensure claims are processed efficiently. Any claim-related questions are handled by over 1,000 agents across multiple contact centers handling over a million calls annually.
- Long wait times due to huge call volumes
- Inefficiencies due to manual after-call work
- Long average call handle times resulting from accessing multiple applications
- AInability to listen to voice of customer and understand their intent or emotion
- Leveraged chatbot to handle simpler customer calls to lower call volumes
- Automated mandatory tasks such as after-call work with conversational AI
- Augmented agent capability with alerts and knowledge base
- Extracted valuable insights by listening to voice of customer
Reduced after call work by 80% and average call handle time by 20%
Increased first call resolution thanks to agent capability augmentation
Improved productivity of agents and satisfaction of customers
Achieved annual cost savings amounting to $6 million.
THE BUSINESS NEED
Huge call volumes increased call waiting times, limited agent bandwidth and made it difficult to monitor every call to capture important customer information accurately from their voice data. It was also observed that agents were spending too much of their valuable time in mandatory after-call-work tasks. In addition, the manual after-call work summarization created factual errors and agents missing out on capturing important information. The after-call work summarization took about 60 seconds on average for each call, and the overall average call handling time was five minutes.
To reduce call handling times and improve efficiencies, the company decided to automate this after call work process to help agents reduce the time spent doing mandatory tasks, thus increasing their productivity and efficiency.
A CONVERSATIONAL SERVICE AUTOMATION SOLUTION
To increase automation, the company decided to implement Uniphore’s Conversational Service Automation Platform. With Uniphore akeira, chatbots were able to automate simpler customer tasks, thus reducing call volumes. With auMina™, Uniphore’s Conversational Analytics solution—the company increased automation of after-call work summarization and reduced operational cost and time spent by customer service advisors on mandatory tasks. The conversational analytics solution auMina™ uses the power of AI, NLP and ML technologies to increase the productivity of contact center agents by automating disposition capture and after-call-work summarization of every call.
HOW IT WORKS
As the call progresses between a customer and the agent, the solution captures and streams the audio to the transcription engine where the speech is converted to text in real time. The transcript of the call is further sent to a Natural Language Processing (NLP) layer to extract relevant information. The system automatically generates call summary. The auto-summarized report of a call eventually reflects on the Agent Desktop Application. The agent can now review and edit call summary within the Agent Desktop Application and take necessary action if required.