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Application Support Transformation in Insurance | Case Study

application support transformation

Introduction

Application support transformation is critical for insurance providers managing high volumes of customer-facing service requests across multiple channels. Traditional support models relying heavily on L2/L3 teams often lead to delays, SLA breaches, and inconsistent customer experiences. This case study highlights how an insurance provider transformed its application support operations by implementing self-service, automation, and a shift-left strategy. By optimizing ticket handling and enabling multi-channel support automation, the organization improved service efficiency, reduced operational effort, and enhanced customer satisfaction.

Customer

An insurance provider delivering application-based services across operations, finance, HR, and technology domains, handling high-volume support requests through web, voice, email, and alert-based channels.

Business Objective

  • Improve customer experience through faster resolution
  • Reduce SLA violations in response and resolution
  • Shift workload from L2/L3 to L1 through automation
  • Optimize operational effort and resource utilization
  • Enable scalable multi-channel support

Scope of Services

  • Ticket volume analysis and baseline assessment
  • Incident vs service request classification
  • SLA performance and compliance analysis
  • Skill-wise workload and resource optimization
  • Automation opportunity identification across applications
  • Self-service and BOT-driven support enablement
  • Shift-left strategy implementation across L1/L2/L3

Benefits

  • Reduced dependency on manual ticket handling
  • Faster response and resolution through automation
  • Improved SLA compliance across service operations
  • Better utilization of L1 support resources
  • Enhanced consistency across multi-channel support

Impact

  • ~48% of tickets identified for automation
  • ~37% effort optimization potential
  • Streamlined high-volume incident categories
  • Improved customer experience through faster resolution
  • Optimized workload distribution across support tiers
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