In a new interview series, we’re speaking with leaders from the loyalty industry about their solutions to challenges facing this field. First up is Len Llaguno, the founder and managing partner of KYROS Insights, the world’s only actuarial firm dedicated to loyalty programs.
Loyalty programs are often measured by short-term campaign metrics like redemptions, clicks and open rates. But Len Llaguno believes that approach minimizes the lasting impact of loyalty, contributing to its flawed perception as a cost center. That perception, he argues, stems from how loyalty programs are accounted for: every outstanding point a member earns is treated as a future cost—and in many programs, those unredeemed points represent the single largest liability on the balance sheet. While that’s critical for financial reporting, it rarely captures the other side of the equation: how much revenue and long-term value those points actually help generate.
As founder of KYROS, a consulting firm built on actuarial science, applies deep statistical modeling to help brands of all sizes, including Expedia, British Airways, Aeromexico and African Bank, better understand redemption costs, forecast customer lifetime value and prove the real financial ROI of their loyalty programs. For him, the key to loyalty’s future lies in changing how it’s measured and ultimately, how it’s valued.
What is actuarial science? Actuarial science is a discipline that assesses financial risk using mathematical and statistical models.
I spoke with Llaguno as part of the THINKINK Loyalty Leaders Series to explore why most loyalty programs are still flying blind—and how they can start thinking more like actuaries to earn the investment and credibility they deserve.
(This interview has been edited and condensed for clarity.)
Your background isn’t the typical loyalty track. Tell us how you got here.
I’m an actuary by training. It’s a bit of an esoteric profession—the stereotype is usually of a math nerd that builds financial models to help insurance companies predict life expectancy, which is critical to pricing. While I did start in insurance, I got staffed on a project with a loyalty program early on in my career and was immediately hooked. Though the two industries share similar challenges, loyalty programs are much more fluid and dynamic than insurance portfolios; there is a lot of room for creativity.
With loyalty, you’re trying to change people’s behavior. That means you need responsive models or tools that can adapt and pick up on signals in real time. Loyalty programs generate a huge amount of transactional data and that data can be used to estimate how many points will get redeemed and what it will cost.
What I realized early on is that most programs were not sophisticated in de-risking points liability. I saw an opportunity to apply actuarial thinking to change that.
You’ve said that loyalty programs often get treated as cost centers. What drives that perception?
It starts with how loyalty programs show up in the financials. Every time a member earns a point, that point represents a future cost. Programs have to account for that cost upfront by recording it as a liability on the balance sheet. We're talking billions of dollars. Every month, quarter and year-end, finance teams and auditors review that liability, which reinforces the cost side of loyalty.
However, very few companies have a structured way to look at the value side—what long-term profit a customer will generate in return. Loyalty ends up looking like an expense to manage rather than a value driver to invest in.
That’s why I always say: if you want to understand ROI, you must start by understanding redemption cost. That’s the denominator. The numerator is the change in customer lifetime value due to the program. Without both, you’re missing the full picture.
How does actuarial modeling help loyalty programs better understand customer lifetime value?
Actuarial science is helpful because it focuses on long-term forecasting, which aligns directly with the goals of loyalty programs.
At KYROS, we take a loyalty program’s transactional data and build forward-looking models using proprietary tools that combine actuarial science and data science. These models estimate how much profit each individual member is likely to generate over time—after accounting for the cost of the points they’re expected to redeem.
The individual-level view is very important: If you're worth $100 and I’m worth $1,000, we should probably be treated differently.
So where do most programs go wrong when it comes to value measurement?
They focus too much on past activity; you can’t influence what’s already happened. With actuarial modeling, you start to understand the behaviors that increase customer lifetime value—not just from a customer experience lens but from a purely economic standpoint. You can study the customer journey and find places where value jumps. For example, booking a second trip within a set period, redeeming for the first time, or crossing a certain spend threshold. If you can identify those moments, you can set KPIs around them and design campaigns to drive them.
Even when loyalty programs run A/B tests, they stop at the campaign level: did campaign A perform better than B? That’s a good start, but the real value is de-averaging those results to understand which segments responded and which didn’t. That’s how you stop wasting currency and start maximizing ROI.
You’ve said loyalty teams struggle to prove the value they’re creating. What’s getting in the way?
Every program leader I talk to says the same thing: “People think this is a cost center. I know it’s valuable, but I can’t prove it.” And because of that, loyalty rarely gets the investment it deserves.
When programs are measured by short-term KPIs—or when leadership turns over every couple of years—it’s hard to make the case for long-term value. That’s what we’re trying to change. If you can quantify long-term value, tied to real financial outcomes, it shifts the conversation and turns loyalty skeptics into advocates.
But this takes time and repetition. You can’t explain it once and expect everyone to get it. You need to educate constantly, especially when program owners are turning over more quickly than ever.
What’s the biggest opportunity loyalty programs are missing right now?
Most programs don’t know which offers are actually profitable. They take a one-size fits all approach and hope for the best. But if you analyze performance by segments, you’ll find portions where ROI is negative. When we do this analysis, we’ve seen clients 3–4x their campaign ROI just by cutting out waste and reallocating currency to where it works best.
The key is precision personalization. That means using the data to determine which offer drives the right behavior for each member. Some members may not need any offer at all. Others might need a bigger incentive. Once you figure that out, you can multiply the impact of your program.
What role does AI play in the work you’re doing?
AI is such an interesting term because it’s just another evolution of sophisticated machine learning—and that’s something KYROS has been using since day one; it’s deeply integrated into everything we do. Our models look at every customer, everything we know about them, all their historical behavior with the loyalty program to inform what we think they are going to do next. No human could analyze data at that level of granularity.
The real innovation in AI is the use of transformer models based on deep neural networks. We’re integrating a lot of those new model architectures into what we do to build “AI actuaries” that can get really good at forecasting: What is the likelihood of redemption? What is the likelihood of a customer returning? What will the customer’s value be? That’s just an incremental improvement on top of the more traditional machine learning models we have today.
That said, loyalty is still a relationship business. No CFO wants to hear results from a black box. They want trusted partners who understand the business and can explain the numbers. That’s where we come in.
For all the complexity in loyalty, Len Llaguno believes the solution starts with a mindset shift. Programs don’t need more data; they need a better way to use it. By applying actuarial science, KYROS helps loyalty teams prove financial value, manage redemption liability and optimize campaigns for long-term performance. The result? A clearer picture of ROI and a stronger case for investment.
To learn more about KYROS or speak with Len directly, visit kyros.com or connect with him on LinkedIn.