Customization is the new “it” thing
If you’re in group benefits, you’ve likely noticed a recent shift in group insurance over the last few years. For a long time, benefits plans sold to employers followed a traditional model. Most group plans offered a two-tiered solution based on clear demarcating lines. These lines could be based on various things decided by the employer. For example, you could have a management plan and a non-management plan, or a union plan and a plan for your non-unionized employees. When employees joined a company, they were immediately bucketed into one of the two tiers. Part of management? You get plan A. A labourer? Your part of plan B. What was lacking for employees was any semblance of choice.
And for decades, that was basically it. Some massive corporations had access to flex plans, but it was rare to see. And in small companies? Forget about it! Employees got what was given to them, and that was that.
Recently, however, things have started to change. The first time I realized we were entering a strange new world was when I came across Equitable Life’s MyFlex Benefits plan. I’m not sure if they were the first to offer individual benefits plans to small business owners or not, but they were the first insurance carrier I ever noticed doing so. In a very old industry, this was novel. All of a sudden, employees were given choice in their insurance – riders, top-ups, et al. In MyFlex, for example, employers now could choose between one to three tiers for their employees, and said employees could customize and choose from three tiers of their own. So an employee with a family may choose more the plan with more dental, while the employee who was a bachelor may decide that more massages was the the day’s order of business. Employers, meanwhile, decided what they wanted to pay for, with employees often paying out of pocket for top-ups or additional products that they decided were necessary for themselves. For the first time, an employee could decide to top-up more insurance products, be they life, critical illness, accidental death & dismemberment, or most anything else. If it was above the amount of money an employer was willing to pay, the employee would pay the difference.
The bonus for employees was that these insurance products tended to be 10%-15% cheaper than the same products available on the market. Customization and personalization became vogue terms for insurance. And why wouldn’t they be? When employees top-up or choose to purchase additional insurance plans through their benefits plan – everyone wins. The employee gets more insurance, the advisor has the ability to generate larger sales, and the insurance carrier gets to sell more coverage. That’s a win-win-win. This personalization and customization also explains why health spending accounts (non-taxable benefits) and wellness accounts (taxable benefits) are now being offered in many places – let employees choose what they want up to some premium price point, then pay out of pocket for anything exceeding that amount.
So why did flex plans take until the second decade of the 2000s to become widespread? Well, for a few reasons. Well, fundamentally, I believe it was an issue of technology. That is, flex plans started being offered when the technology within insurance carriers finally reached a certain point where a higher level of customer customization became possible. It is not a shocking change in the business model that led insurance carriers to offer these personalized plans – instead, it was the carrier’s ability to price, administer, and track more complex plans that led to this change in group benefits.
And the fact that insurance carriers are moving into personalization is going to be a massive shift in the future of insurance products. One that will lead to incredible effects downstream from them for insurance advisors, both individual and group.
Personalization is the next frontier of insurance
In the traditional models of insurance, hyper-personalization was incredibly difficult. Fundamentally, this was a problem of data. Consider how insurance works – actuaries use existing information to price risk, then offer insurance to large groups of people whereby they expect the premiums generated to be greater than the claims made on the policy. On average, they aim for a target loss ratio of 75%-80% (that is, for every $1 of premium, carriers expect to pay out $0.75-$0.80). Now, consider what information is generally used – age, gender, various health metrics, and potentially (and unfortunately) race. Are you overweight? Higher premiums. Are you a young male getting car insurance? Higher premiums.
This limited data, however, is the antithesis of personalization. After all, if you need to make sure your target loss ratio doesn’t end up greater than 100%, you need to paint in broad strokes. Two 35-year-old males with a similar BMI will pay the same premium for life insurance, even if one is a couch potato and the other is Arnold Schwarzenegger in his prime. This means that you end up creating anti-selection in insurance. The people who need dental care the most will be the ones to buy dental insurance, while the ones who have had a lifetime of healthy teeth may be priced right out of purchasing coverage.
Personalization, then, requires better data. It requires more granularity than currently exists. It needs to be able to price risk accordingly for people based on more thorough risk profiles. And this is hard. It requires immense amounts of data about clients. When we see customization, riders, and top-ups, we’re seeing the first steps towards this. But this is only the beginning. The future of insurance will be the future of big data. It will be a future where much more information is available about any given client that pricing risk will become far more personalized. It is also a future where products will be tailor-made to individuals based on their life circumstances and needs. So a new parent will have a young parents life insurance package built, marketed, and sold to him or her two weeks after a baby is born.
Now, there are obvious risks involved here that regulations will need to iron out. We don’t want the level of risk profiling where the people who most need insurance are essentially priced out of it entirely. Things like private medical records should remain off the table for carriers to price off of. But we already know that millennials are willing to trade some privacy for value, so the next generation of insurance products will be smarter than ever before with little social backlash. Imagine a world where buying pet food triggers an advisor that you have gotten a new dog, and may want to buy pet insurance, and you’re getting a bit closer to what’s coming next.
Big Data and the Advisor-Client Relationships
Unfortunately, while the technology to power this level of personalization is starting to be developed by insurance carriers, there has been minimal trickle-down for advisors. And this is hugely problematic. Flex plans in small and medium-sized businesses have, in my opinion, demonstrated the incoming headache that advisors sticking to pen and paper will have to go through in the future.
Let’s take a look at current processes surrounding flex plan top-ups / riders. For the most part, when a group benefits advisor sells a flex plan to an employer, he or she has a great opportunity to cross-sell and upsell employees. However, a great number of advisors I have spoken to do not do this. The majority recognize that they are leaving money on the table, but the amount of added work it takes to keep track of employees and help them understand complex decisions means they prefer to just focus on the next employer instead. At the end of the day, a top-up or rider is going to generate significantly less revenue than a new group plan – many group benefits advisors look at that and shrug their shoulders. Why bother?
Meanwhile, the advisors who do attempt to sell directly to the employees as well tend to employ a one-size-fits-all approach. They offer lunch and learns, group sessions, or mass emails with policy information. The hope, here, is that they can grab the lowest hanging fruit easily through these sessions, and then move on. These are the employees who have an easily identifiable need, or who have self-identified. But even then, keeping track of all of these policies is difficult. MyFlex, for example, has a two-year renewal process. So, for two years, an advisor needs to keep track of a client to ensure that when the renewal comes up, they renew the policy. Doing so using pen & paper, or old-fashioned CRM technologies is not helpful at all here.
More importantly, as products become more customizable and more individualized, the low hanging fruit will begin to vanish. Product customization will breed complexity – consumers are going to have more and more choice. But with more choice, they will require more handholding and explanation. And without technology, this future will lead to most insurance advisors struggling to service their clients appropriately.
This additional complexity and choice will hold true for all individual insurance advisors as well. Anyone selling insurance will now need to deal with a lot more complexity. Instead of there being a few product choices, clients will have dozens. The goal of the advisor will be to not just procure the right insurance product for a client, but figure out what the right product is. And, today, the tools to help do that simply don’t exist.
Technology for Complexity
Technology is going to rapidly become necessary for combating complexity. First off, advisors will need technology that helps them deal with immense amounts of new product information that will be coming down the pipeline. Imagine a world where you sit in front of a prospect, fill out their information, needs, and specific wants on a tablet, and immediately have 3-4 products and quotes for spit back out to you? All of a sudden, every client is receiving customized, personalized, white glove service. And, as an advisor, you get to provide clients with amazing service, educate them on the intricacies of the different product offerings, and close them quickly and on the spot. What’s not to like?
So what’s necessary for this sort of technology? Well, we need to merge the data layers between product and client. Today, the insurance carriers, MGAs, and TPAs control data about the product. They create or distribute the products, and are tasked with educating advisors on them. Whether they successfully do so is another topic for another time, but, suffice to say, if you have 10x as many products coming out in the next five years due to better data, advisors are going to be facing a far steeper learning curve. Meanwhile, advisors own the client data. They know who their clients are, what they like, what they want, and what they need. As long as these two data layers are separated, we are not going to see advisors succeeding.
The future of advisor enablement, then, involves merging these two data layers. It means that advisors collect client data which is directly sent to the carriers (or MGAs / TPAs), and advisors receive personalized product data in return. This would lead to all sorts of gains for clients, advisors and distributors. Clients will be able to receive better personalized coverage that fits their needs appropriately.
For advisors, the upsides are huge. First, you will be able to provide the exact right product for the right client. Moreover, intelligent recommendations will also help you upsell or cross-sell. If you have information about your client which, when pushed through the product data layer, suggests that your client is likely to purchased accidental death & dismemberment insurance, you are selling a product that may never have come up in the needs assessment conversation. You’re using big data to help guide clients towards products they need but don’t know they need!
Just as importantly, when you connect the data and product layer, future sales become easier to generate. Notifications from the product layer can alert you when clients should purchase a conversion product, or when a client has hit a certain milestone that means they may need a new product. Meanwhile, information brought in by the advisor about the client and provided to the product layer can generate a list of potential upsell opportunities. If you know your client just had his first child, now the product layer does and it can recommend the products clients similar to your client bought after having their first child.
Fundamentally, this is what we see as the future of the advisor. It ties into our concept of the bionic advisor. It is an advisor that will use technology to help automate and streamline the sales process, allowing him or her to focus on the hands-on relationship management of the business. In the future, advisors will be able to work with far more clients by doing far less back-office busywork.
What do you think? Are you ready for the future?