About Company
A leading private general insurer in India, the company serves millions of customers across motor, health, and personal insurance. With a strong nationwide distribution network and a rapidly growing digital customer base, renewals form a critical part of its business.
The insurer has been actively investing in modernising its customer engagement and retention workflows, with a focus on consistency, speed, and scalable outreach. As part of its broader digital transformation, the organisation began exploring AI-led automation to enhance customer experience and streamline high-volume renewal interactions.
This set the foundation for integrating voice-led AI into its renewal ecosystem.
The Challenge
Despite strong brand presence, the insurer’s renewal operations were facing structural constraints:
High dependency on large human teams, driving up operational costs
Inconsistent follow-up cycles, script deviations, and backlog-driven drop-offs
Limited scalability, with lead volumes increasing faster than hiring capacity
Leadership mandate to automate renewals, reduce operational cost, and redirect human effort to high-intent conversations
The Solution: Humanoid Voice AI Agents for Renewal Process
The insurer deployed SquadStack.ai’s Humanoid Voice AI Agent to automate end-to-end renewal process..
The scope of deployment included:
Automated renewal reminders
Qualification, premium confirmation, and intent capture
Real-time callbacks and multi-touch follow-ups
Automated segmentation and scoring
Warm transfer of qualified customers
Instant data sync with internal CRM
The AI agent became the frontline renewal engine, delivering consistency, speed, and compliance at scale.
Real Customer Conversations
Impact: A Faster, Leaner, AI-First Renewal Machine
Performance Outcomes
Higher Connectivity: AI delivered 85% connectivity, ~25–30% higher than humans, improving top-of-funnel coverage during renewal cycles..
Lower Average Handling Time: AHT reduced by ~33%, enabling faster conversations and higher throughput.
Stable Conversion Performance: Conversions remained consistent, validating that AI could fully take over renewal process without deteriorating outcomes.
Significant Cost Reduction: Operational cost reduced by 50–60%, aligning with the organisation’s mandate to optimise manpower and automate early-stage retention workflows.
Experience & Quality Outcomes
Better CX Through Consistency: Uniform, deviation-free conversations improved customer clarity and experience.
Seamless, Automated Journey: Structured, AI-driven workflows eliminated manual backlog and reduced friction for policyholders.
Real-Time Turnaround: Instant callbacks and automated re-engagement removed the earlier 24–48 hour delay.
Stronger Downstream Conversion Quality: More consistent qualification inputs improved the quality of leads routed to human closers, strengthening overall conversion performance.
Operational Efficiency Outcomes
Higher Human Productivity: Human agents engaged only with warm, high-intent customers, improving closing efficiency and reducing workload fatigue.
Scalable Infrastructure With No Linear Cost Growth: AI handled 10 lakh+ leads monthly without additional hiring or operational overhead.
Expanded Regional Reach: Multilingual AI capability allowed deeper engagement in Tier-2 and Tier-3 regions, a unique advantage not achievable earlier without proportional team expansion.
Investment & ROI
50–60% cost advantage over traditional BPO or in-house calling teams.
100% automated QA, with just 3% human audit sampling.
Continuous ML-driven optimisation improved accuracy and compliance.
Real-time monitoring and compliance triggers provided complete operational visibility.
This validated that AI could replace manual renewal process workflows while lowering cost, improving efficiency, and strengthening the organisation’s retention engine.
Paving the Future of Renewal Automation at Scale
By automating high-volume outreach, delivering consistent conversations, and reducing operational cost, the insurer built a more predictable and scalable renewal engine.
What began as a mandate to streamline retention operations has now evolved into a renewal workflow where AI acts as:
The first line of customer communication
The qualification and intent-capture layer
The automated follow-up engine
The foundation for future renewal automation across products
The success of this transformation serves as a blueprint for how insurers can modernise retention through an AI-first operating model.
