AI/ML Driven Scheduling for Workload Management for an Insurance Company

Objective Automate the workload management to help insurance company save in OpEx.

  • Managed risks with ‘What-If’ Analysis by risk and control assessments, internal and external loss events, key risk indicators, and issue/action plan management within a single environment.
  • Provided internal auditors with a cross-departmental view into organizational GRC. Helped the company to efficiently plan, execute, report on, and review their audit universe.
  • Automated the ongoing test, review, approval and remediation process. Helped identify similarities between regulations to reduce redundancy and duplication of effort. A complete real-time view of how sensitive data was used, stored, and accessed throughout.
  • Automated private data reporting to improve accuracy, reduce audit time, and accelerate initiatives.
  • Helped the company with data extraction, integration and AI/ML analysis.
  • AI/ML driven predictive scheduling and workload management has generated upto 20% savings in OpEx.