Undisclosed APAC Insurer

The APAC insurer was struggling with manual quality assurance processes for customer interactions, which were labor-intensive and time-consuming. The high volume of customer calls and interactions made comprehensive QA coverage difficult to achieve with traditional sampling methods.

WNS implemented an AI-powered interaction analytics solution that automated the quality assurance process by analyzing customer interactions at scale. The solution used NLP and speech analytics to evaluate calls and flag issues without manual review of every interaction.

The AI-powered interaction analytics solution reduced quality assurance efforts by 50%, significantly increasing efficiency and coverage. The insurer was able to monitor a much larger proportion of customer interactions while reducing the manual workload on QA teams.

• AI-driven interaction analytics can dramatically reduce manual QA effort while improving coverage and consistency
• NLP-based call analysis enables insurers to scale quality monitoring without proportionally scaling headcount
• Automating QA processes in insurance customer service delivers measurable efficiency gains