Driving long-term bottom-line savings with GenAI for a mutual fund organization | HCLTech

Driving long-term bottom-line savings with GenAI for a mutual fund organization

Enhanced customer service desk ticket resolution processes with a GenAI-based automation tool
5 min read
5 min read

The client's aspiration to deliver a seamless human experience complements a 'digital-first' strategic approach. In assessing the landscape of omnichannel interactions, an opportunity emerged to utilize automation not only to enhance operational efficiency but to also harvest significant long-term financial benefits.

The Challenge

Manual omnichannel interaction summarization

Omnichannel interactions through phone, chat and email require support agents to manually summarize and note essential information. This manual process often results in critical data loss, incomplete summarization, extended issue resolution times and decreased customer satisfaction. To enhance productivity and reduce operating expenses for the Service Desk, automation is necessary in the current setup.


The Objective

The primary objectives focused on three critical pillars

  • Enhance process efficiency
  • Boost employee productivity and satisfaction
  • Reduce the cost of service

The Solution

Harnessing Azure Open AI services for end-to-end automation

To address these objectives, HCLTech deployed a state-of-the-art, powered by Azure Open AI Services that offered an end-to-end ticket resolution system. This system featured automated responses and utilized historical interaction data to auto-identify resolutions. It also incorporated a sophisticated follow-up workflow, which employed advanced techniques, including classification, summarization, contextualization and matching similarities.


The Impact

The deployment of this cutting-edge solution yielded remarkable results

  • Streamlined ticket creation: An approximate 80% reduction in summarization efforts translated to expedited ticket creation
  • Flawless classification: Complete automation of ticket classification removed the process entirely from human hands, saving 100% of the associated efforts
  • Autonomous ticket resolution: A striking 70% reduction in manual labor for ticket resolution, with a lean L3 process optimization
  • Cost savings: The automation solution is expected to deliver projected savings of roughly $3.2 million annually