Big data and analytics are combining to profoundly alter one of the most manual processes in the insurance industry: claims management. Simple algorithms can ferret out evidence of claims leakage, fraud and legal propensity while driving a better understanding of claims complexity and drivers of customer satisfaction, contributing to enhanced claims service, better cost control and increased operational efficiency.

Executive Summary

Starting with a specific use case targeting better reinsurance recoveries for catastrophe claims and an algorithm that uncovered double-digit millions of dollars of potential missed reimbursements, QBE is now using data analytics to update a host of manual claims processes. Simple algorithms can not only ferret out missed reinsurance payments but can also help the global insurer improve policyholder satisfaction with claims service, writes Jim Kinzie, who heads the carrier's claims analytics program.

Earlier this year, and as part of a global initiative called Brilliant Basics Claims (BBC), we launched a horizontal, multiyear, data-driven claims analytics transformation program to generate enhanced analytics capability and enablement across all divisions of our global claims operation. The success of earlier divisional data and analytics team deployments compelled us to elevate claims analytics as a strategic and global area of focus and investment.

In one of our claims divisions in Australia/New Zealand (ANZO), work had been started around a specific use case targeting better recovery of reinsurance on catastrophic claims. The team had experimented on this use case with data analytics using simple business rules for a couple years, advanced to incorporate machine learning algorithms. The division’s approach yielded extraordinary insights that culminated in millions of dollars of reinsurance payments that otherwise might have slipped through the net.

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