PEO Insider Issue

In your group health sales cycle, time is of the essence. Shorter sales cycles generally lead to larger volumes, higher revenues, more satisfied account execs, and repeat customers, especially for an annual purchase like group health insurance. You can shrink the time you turn a lead into a customer by adding a speedy new member to your sales team: artificial intelligence. AI can help you close deals faster than your competitors can get their boots on. 

Depending on your news diet, you might find the term “AI” a bit overhyped, but predictive models—although powered by AI—are anything but vaporware. You encounter them daily when, for instance, Amazon or Netflix suggests products or films you might like. And these models are not just ubiquitous in retail settings. The insurance industry has used and trusted them for over a decade.  

When it comes to group health risk assessment, the ability of models to deliver a score in moments confers several real advantages to PEOs competing for new groups.  

Here are four ways to put this proven technology’s speed to work and reap the benefits—and an additional advantage that’s based on one of predictive modeling’s other big strengths: consistency. 

1. PASS OR PURSUE—DECIDE IN MOMENTS 

Sometimes a model yields a risk score that indicates a group probably isn’t worth pursuing. Getting that knowledge quickly allows you to move on, freeing up your salespeople to look for groups that are a better fit. 

2. OUTPACE COMPETITORS WITH SAME-DAY QUOTES 

By providing an alternative to questionnaires and traditional medical underwriting, an AI-powered predictive model can cut the time it takes to deliver a quote from days to minutes, enabling you to prepare same-day bids and improve the customer experience. Getting that near-instant risk assessment gives you a healthy head-start when you’re competing with other PEOs to acquire “plum” white-collar or tech companies. 

3. BUY TIME TO PIVOT 

Even if you’re not in a flat-out sprint against competitors, a model’s quick turnaround still offers several advantages. 

When a quick risk assessment comes in high, you may still have time to submit the group to another master plan, if you have one available. Although all insurers share fundamentally similar goals, they sometimes have different appetites for risk, so a group may be rejected or priced out of contention by one insurer and still find a place with another.  

4. BUY TIME TO COOK UP A SWEETER DEAL 

Having a group health quote come in a little high doesn’t necessarily mean you’re out of the running, as long as you get that quote in time to make changes to the overall pricing.  

You may decide it’s worth sweetening signing incentives or negotiating administrative fees associated with workers’ compensation, state unemployment taxes, applicant tracking systems, or employee training platforms. If you really want the group, you may well be able to come up with a deal that works for both parties—but again, only if you have time to think it through.   

5. STRATEGICALLY BALANCE RISK 

Speed and accuracy fully justify the use of a predictive model, but those are not the only reasons to use one. A fundamental difference between predictive models and human underwriters is that given the same inputs, a model will always produce the same output. That makes model scores a consistent and easily understood reference that you can use to strategically balance risk. 

Over time, as groups come and go, you may find that the overall risk for your pool has drifted up or down. It’s useful to know if it’s gone up because that presents a direct threat to your rates. The last thing you need is to have your best groups shop their business around because, through no fault of their own, rates have gone up. On the other hand, if your overall risk has gone down, you may decide to bid a new group more aggressively because you have a cushion in terms of your total pool. A good sense of how individual groups contribute to overall risk can also help you to optimize retention efforts. 

The catch is that this kind of risk balancing is hard to do unless you have some metric that is consistent across all your groups. You might also choose to re-run groups for which you have only partially credible information. Even one or two cases of employee turnover can radically change a small group’s risk score.  

The advantage you get from using a predictive model—powered by AI of the un-hyped variety—is not just being able to quickly ascertain risk, close a deal in days, and shorten the sales cycle altogether. A model can also give you flexibility on deals that you might otherwise lose, and a consistent risk metric that you can use to balance overall risk and take a more strategic sales approach. 

KAITLYN FISCHER
Sales SpecialistMilliman IntelliScript