This company is a U.S. Top 15 property-and-casualty (P&C) insurer, based chiefly on its market share for its largest product category: auto insurance.
They have a proud record of customer service, consistently outperforming their peers in policyholder experience and service performance.
And they had invested heavily in bleeding-edge technology, too. Their claims-management system was state-of-the-art. They even boasted an AI-enabled app that would produce damage assessments for tech-savvy policyholders who uploaded photos via their smartphones.
And when robotic process automation or RPA hit the scene, they developed an internal Center of Excellence, assigning teams of “citizen developers” to scour claims operations for automation opportunities.
All of the technology, however, represented management’s attempt to fix a persistent problem: this insurer’s expense and loss ratios were routinely higher than those of its peers.
The AI app didn’t help. The shiny claims-management system didn’t either. And their internal RPA team had only launched about a dozen bots.
Their initial conviction—that all the technology would standardize their efforts—lost its luster when they spoke with employees on the ground. They realized there must be massive worker-to-worker variance on everything from error rates, to claims severity, to subrogation referrals.
It was time for them to contact The Lab.
The eight-week auto-claims standardization initiative began with an end-to-end analysis that documented all business processes from first notice of loss (FNOL) through final payment and subrogation.
With our world-leading library of P&C claims-processing templates—including KPIs, data taxonomies, process maps, best practices, RPA use-cases, and more—we rapidly documented and analyzed work activities right down to the two-minute level.
Despite the detailed discovery, our work required only one hour per week of any subject matter expert’s time.
The Lab identified over 180 activity-level improvements. Approximately 60 percent of these could be implemented without any new technology. Of the remainder, half could be automated with the client’s existing technology (after the processes were standardized); the rest could simply use RPA and low-code applications such as automated forms and APIs.
The common thread—for reducing claims losses, increasing subrogation recoveries, and recouping organizational capacity—was inconsistency. Over the years, needless variation had crept into processes spanning FNOL data intake, adjuster assignment, loss reserving, and more.
Similarly, worker-to-worker metrics for error rates, claims severity, productivity, and subrogation recovery varied by orders of magnitude.
The self-funding, eight-month Phase II implementation plan targeted the most valuable opportunities selected by senior management. Examples:
1. Claims intake improvement. FNOL training was under-standardized and outdated, leading to subjective decisions, policyholder confusion, and extensive downstream rework. The Lab updated cause-of-loss definitions, and consolidated 50-plus adjuster-assignment “paths” down to just 12.
2. Reducing variance in claim severity. Analysis of claims-payout data revealed a massive variance in indemnity paid for similar claims, resulting in tens of millions in over-payments each year. The Lab worked with top adjuster managers to identify “red flags” among their teams—and send them preemptive alerts whenever one was spotted by AI.
3. Standardizing subrogation. Roughly half of all inbound subro requests were missing data, such as adverse carrier info, damage detail, or claimant contact information. The Lab “error-proofed” the request forms, upstream, by adding lockouts for improper submissions and bots to flag errors in real-time.
These are just the highlights. Get more detail on this fascinating case study by reading the full version here.
Client: Top 15 P&C Insurance Carrier North America
Sponsor: Chief Claims Officer
• 8-week Analysis and Discovery
• 8-month Implementation
• End-to-end auto claims process
• No new core technology
• Claims intake (FNOL)
• Increased productivity
• Fewer FNOL errors
• Decreased claims leakage
• Reduced operating expense
• Expanded use of automation
• Operating costs: Down 12%
• Claims cycle time: Down 15%
• Average claim severity: Down 4%
• Break-even point: 6 months
• ROI (12 month): 7x
Learn more about how The Lab has been helping P&C insurance carriers for nearly 30 years; we invite you to schedule your free, no-obligation 30-minute screen-sharing demo.
You’ll learn more about our patented approach to Knowledge Work Standardization®. You’ll see actual E2E process maps and RPA bots in action. You’ll learn how we are able to do all this, remotely, from our U.S. offices in Houston, with nothing outsourced or offshored, ever. And you’ll get all your questions answered by our friendly experts.
Simply call (201) 526-1200 or email email@example.com to book your demo today!