Filed Under:Claims, Claims Technology

Claims and Business Intelligence: Adjusters in the Spotlight

Many business intelligence (BI) applications and efforts are focused on policyholders. We know how to monitor and measure the myriad offers, discounts, and special programs we create for them. We know how many times policyholders and prospects are “touched” in our marketing and sales processes. We know the demographic profiles of policyholders and prospects, their buying behaviors, their preferred price points, and their appetites for risk.

But we seldom make the same efforts to provide metrics and BI to claims adjusters, the very folks who interact with our policyholders at the times in which they need us most—and in the circumstances under which they’re most likely to judge our performance as insurers. Setting aside the most obvious question—Why don’t we focus BI on adjusters?—let’s examine what we should look at and why.

Be Wary of Workloads

The two metrics most typically used to measure adjusters’ workloads are the number of claims being handled and the closing ratios of those claims. The downside to these metrics is they give adjusters incentives to handle more claims and to close them as quickly as possible. The unintended consequences are frequently dissatisfied policyholders and a loss of control over loss costs. More specifically, policyholders are dissatisfied because they get the impression adjusters are more interested in closing claims than in listening to them and performing comprehensive investigations. Such haste also may result in litigation and declining retention rates—rates that may be compounded by policyholders who complain to friends and/or post their complaints on social media.

Control over loss-costs is lost because measuring adjusters on closing ratios often increases the number of reopened claims, as well as the number and the amounts of after-closure payments. Both require the release of reserves needed to cover known losses. Control is lost to an even greater extent if policyholders believe they’re being rushed to close and turn to lawyers as recourse.

As an alternative, BI can help companies employ metrics such as customer retention after claims, the percent of first-party claimants who will recommend your company, numbers and amounts of after-closure payments, and the percent of claims that involve claimant lawyers. Monitoring these kinds of metrics, along with the number of claims being handled and the closing ratios, can improve policyholder satisfaction, restore control over loss costs, increase policyholder retention, and improve loss ratios.

Timing is Everything

After numbers of claims and closing ratios, we also seem to love seeing how long it takes adjusters to contact claimants, make first payments, and send coverage letters once the loss has been reported. While it’s important to make a positive first impression, what happens after those initial contacts? Claims processes can be very long, deeply involved, and highly iterative—and can seem especially so to the claimant.

Adjustment processes should be monitored and reviewed to ensure good practices and conscientious performance throughout the life of the claim, not just during the first steps. Do adjusters follow up in a timely fashion? How do they interact with the claimant thereafter? Claims files should be reviewed and graded for what was done well and what could be improved. Adjusters should be monitored for compliance with the carriers’ best practices beyond just time to first contacts. As insurance companies monitor metrics such as the number of times claimants were contacted, the longest periods with no contact, and the number of payments made, they will formulate best practices that they can communicate with their adjusters.

Defining the Terms of Success

Often, we judge the performance of adjusters on loss ratio. But what loss ratio? There are many ways to calculate loss ratios. Calculations may or may not include ALAE, ULAE, reinsurance recoveries, ceded premium, salvage, subrogation, other recoveries, and other factors. If adjusters are being measured on loss ratio, won’t the best adjusters purposely avoid complex claims with the potential for high losses? Aren’t those precisely the kinds of claims you reserve for your best adjusters?  If a carrier decides to enter a new market—and price policies low to attain a foothold—should adjusters be penalized for adjusting losses on those policies when the rates were low by design?

Better to derive performance metrics and corresponding incentives for adjusters from the aspects of adjustment they can actually control, as well as from those aspects that contribute to the betterment of the company and the satisfaction of policyholders. So, we might look at BI that indicates the percentage of total claim costs attributable to ALAE. We might monitor the numbers and the amounts of recoveries recognized. Or we might evaluate the percentage of claim files that passed review against the total number of claims reviewed. These are all metrics that the adjuster can directly influence and, to some extent, control.

Making BI Work

Regardless of the metrics or performance criteria we select, the value of BI is its precision. But that very precision means we have to be equally precise. We have to know what we need to know for the betterment of the business. We have to be clear about what we want to know to fulfill the promise of our brands and its value propositions. We have to know what our adjusters can control and what they can’t control. And we have to know how to query the data resident in our systems to derive what we need and want to know.

If our producers are on the front line of establishing business, acquiring policyholders, and bringing in revenue, our adjusters are on the front line of returning the premiums invested in us, of satisfying our policyholders, of retaining that business, and of controlling costs. Let’s be sure we’re harnessing the real power of BI to improve productivity—and profitability.

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