How the group benefits industry can solve bad data challenges
This will come as little surprise to insurance-carrier executives, but erroneous enrollment data is rampant in the group benefits industry. Such errors—incorrect birth dates, social security numbers, addresses, effective dates, and more—cause all sorts of critical problems: Poor member experiences, claims and billing issues, operational inefficiencies and premium loss for carriers. The list goes on.
But here’s what might surprise many in the industry: this universal problem is solvable.
To be sure, if we’re to fix this problem at the industry level, we’ll need to shift the industry’s collective mindset, adopt modern technology, and foster greater collaboration throughout the ecosystem. But before we embark on the path forward, it’s important to share a clear understanding of the stakes.
Data errors: Bad for members, bad for carriers’ bottom line
My company has found that about 8% of employee enrollments have a critical coverage issue, i.e., they’re either missing coverage for a benefit in which they’ve enrolled, or the employee is still enrolled after their coverage should have been terminated.
We have every reason to believe that these findings scale to the industry at large: 110 million people in the U.S. have employer-sponsored health insurance and employee benefits. By our estimation, almost nine million employees could have a coverage issue.
It’s important to internalize two things: First, these data issues are ubiquitous throughout the benefits ecosystem, including within all carriers’ systems. Second, coverage issues have a significant impact on both the member experience and carriers themselves.
For members, it is not uncommon for an employee, or their dependent, to arrive at a medical appointment, only to discover they weren’t enrolled in health insurance. But imagine the aftermath if an employee dies and wasn’t correctly enrolled in life insurance. Nothing erodes the reputation of employers, brokers, and carriers quite like a poor employee-benefits experience, and many of these common examples result from inaccurate data.
Bad data’s impact on carriers is two-fold: operational inefficiencies and lost revenue. It’s a resource-intensive operational burden to retroactively fix data errors, overloading carriers’ member-support and enrollment-operations teams. Carriers also miss out on premium—our experience suggests tens, if not hundreds of millions annually—because employees are not enrolled in benefits they selected. And this back-of-the-envelope cost analysis doesn’t include the reputational harm from lackluster member experiences.
The way forward: New mindset, modern tech, more collaboration
As deeply embedded as data errors are in the fabric of our industry, there’s a clear path to eliminating them and their harmful impact.
Our industry must adopt a new mindset. For too long, carriers and other stakeholders have allocated resources to solving the symptoms of data inaccuracy, but not the problem itself. It’s time for the industry, collectively, to agree that this is a problem worth fixing—and a problem that’s fixable. Until those two ideas are universally understood and accepted, we’ll have a hard time eradicating data errors.We must embrace modern technology. This is especially so when it comes to using application programming interfaces to help identify, communicate, and rectify data errors before they morph into costly, harmful coverage issues. An API-connected ecosystem would speed up enrollment transactions, cut down on errors at the point of transmission, and simplify how carriers, employers, brokers, and others fix issues.Collaboration must become the norm. Fixing our industry’s data problems will require contribution and cooperation from all stakeholders. Truly, this isn’t the responsibility of a single party, nor can any one carrier solve this problem for themselves. It will take a group effort.
Already, we’re seeing some carriers develop technology partnerships that have more accurate enrollment data as a principal objective.
But if we can unite behind all three of the above imperatives—new mindset, modern tech, greater collaboration—we can eliminate inaccurate benefit data once and for all.
It will be well worth it, for carriers, for members, for the entire industry.
