Reimagining User Access Management with AI

Harnessing AI to streamline user access management, reduce workload, and enhance operational efficiency for a leading insurer.

Case Summary

SLK partnered with one of the top 10 commercial insurers in the United States to tackle some of their critical business challenges like high costs, undue workload and delays across IT managed services. SLK implemented an AI-enabled solution in two phases to reduce manual interventions in user access management. This approach optimized service delivery, enhanced overall operational efficiency and reduced costs significantly.

The Challenge

The insurer struggled with high costs and operational inefficiencies stemming from the user access management within their managed services. Key challenges included:

Inadequate data and limited insights: The ticketing system failed to capture sufficient information to identify issues and areas for improvement.

High Manual Intervention: Significant manual effort was required tasks, resulting in rework and reconciliations

Operational Delays: Inefficiencies led to delays in handling user access management tasks.

The Solution

SLK implemented a solution in two phases to address these challenges.

Phase 1: Intelligence Generation through SLK’s proprietary AI/ML enabled PeakPerform™

  • Analysis of all tickets within the managed services
  • Identification of key Issues such as user access management
  • Intelligent environmental assessment on current capabilities and existing gaps

Phase 2: Solution Implementation through NLP

  • Multi-System Integration of NLP with NiceCXone IVR systems, ServiceNow, and Okta
  • Voice Command Automation to handle key user maintenance tasks
  • API Utilization with Okta APIs to automate processes and reduce manual intervention

Business Impact

The implementation of SLK’s AI-led solution brought significant improvements, including:

31%

Reduced manual intervention, with intelligent assessments

14%

Reduced ticket volume, contributed to improved customer satisfaction