John Stokes has spent over two decades at HSB, moving from equipment breakdown underwriting into leading technology-driven risk solutions. Today, he leads the Technology Risk Solutions division of HSB, where his team builds insurance-backed warranties and guarantees around technologies like Wint. We sat down with him to talk about why HSB’s engineering roots shape how the company evaluates new technology, what it takes to turn field performance data into an insurable guarantee, and why performance guarantee models are set to play a bigger part in how insurers back proven risk reduction.
Career Journey
You’ve spent over two decades at HSB, starting in equipment breakdown underwriting and evolving into one of the leaders of technology-driven risk solutions. Looking back, was there a specific moment or project that shifted your focus toward the intersection of insurance, engineering, and emerging technology?
Early in my career, the work was largely centered on understanding exposures, evaluating equipment risk, pricing appropriately, and responding when losses occurred. That foundation is still critically important and always will be. But over time, as equipment became more connected and operational data became more available, it became clear that insurers could play a much more active role in helping customers reduce risk before a loss happens.
At HSB, that approach is natural because our roots are in engineering. We understand how equipment fails, and how risk develops over time. Emerging technologies give us a new way to apply that expertise to help prevent losses.
Technology
HSB has been at the intersection of engineering and insurance for over 150 years. How does that engineering heritage affect the way your team assesses technologies like Wint, compared to how a more financially oriented underwriter might approach it?
A traditional underwriting view is essential, but it may begin with exposure characteristics, historical loss experience, pricing, terms, deductibles, and limits. At HSB, we certainly look at those factors, but we also go deeper into the mechanics of how a technology actually performs.
With a solution like Wint, we are asking very practical engineering and risk questions: How does the system detect abnormal water flow? How quickly can it distinguish between normal usage and a leak event? Can it shut off water before damage escalates? Does it perform reliably in complex commercial and construction environments? What happens during a power or network interruption? How does the technology behave in the field, not just in a controlled demonstration?
That level of technical due diligence matters because not every technology that claims to reduce risk produces the same outcome. Some tools may detect a problem. Others may prevent a loss. That distinction is especially important from an insurance perspective.
HSB’s strength is that we bring underwriting, claims, engineering, and technology evaluation together. We are not simply looking at whether a product is innovative. We are looking at whether it can deliver measurable risk reduction in the environments our customers actually operate in.
Insurance has historically been a reactive industry, responding to losses after they happen. The technologies you work on at HSB are designed to prevent those losses before they occur. How does that shift the way you think about risk modeling and product design?
Historically, insurance has been built around a react-and-respond model. You assess the exposure, price the risk, and respond when a claim occurs. That model remains necessary, but it is no longer the only model available to us.
When prevention technologies become part of the equation, we can begin asking a different set of questions. Instead of only asking, “What is the expected loss?” we can also ask, “What can be done to reduce the probability of that loss? What can reduce the severity if an event occurs? And can that improvement be measured with enough confidence to influence the insurance structure?”
This means insurance can begin to recognize the value of active mitigation. It allows us to better support customers who are investing in proven technologies and better risk practices. It also creates stronger alignment between the insurer, the customer, and the technology provider because everyone is focused on the same objective: preventing loss.
From a modeling standpoint, this does not eliminate the need for actuarial discipline. It enhances it. We still need credible data and rigorous analysis, but we can supplement historical loss experience with real-world performance data from technology deployments.
That is where the industry is heading. Insurance products will increasingly reflect the actions customers are taking to manage risk, not just what their historical risk profile suggests.
You work with equipment manufacturers and digital solutions providers to develop products that guarantee technology outcomes. Where does water intelligence fit within the broader suite of risk technologies you’re seeing come to market right now?
Water intelligence is one of the clearest examples of how technology turning risk management from passive monitoring to early prevention.
Across many categories, we are seeing digital solutions that monitor equipment health, detect anomalies, predict failures, improve efficiency, and reduce downtime. Water risk fits very naturally into that broader movement because the exposure is significant, the losses can be severe, and the opportunity for prevention is real.
What makes water intelligence especially compelling is that water damage is often both frequent and preventable. In construction and commercial property environments, a relatively small failure — a faulty fitting, open valve, pipe break, or system issue — can lead to major damage if it is not identified and addressed quickly. The longer water flows, the more severe the loss becomes.
Intelligent water management changes that timeline. Instead of discovering a loss after damage has occurred, these systems can identify abnormal usage, alert stakeholders, and in some cases automatically shut off water before the event escalates.
That is exactly the type of technology insurers should be paying attention to. It addresses a meaningful loss category, creates measurable operational value, and has the potential to improve outcomes for customers, insurers, contractors, developers, and property owners.
Performance Guarantee
HSB & Wint’s Water Leak Damage Prevention Guarantee is built around leak detection performance in live commercial environments. What does it take to translate a technology’s field data into something an insurer can actually structure a financial product around?
It takes discipline, data, and a clear understanding of the outcome being guaranteed.
From an insurance perspective, it is not enough for a technology to be innovative or promising. We need to understand how it performs across actual use cases and operating conditions. That means looking at real deployments, consistency, system reliability, claims impact, and the practical conditions under which the solution is expected to operate.
The key is translating technology performance into an insurable outcome. That requires clarity around several questions: What event is the technology intended to prevent or mitigate? How is performance measured? What conditions must be in place? What data supports the expected result? Where are the limitations? And how much confidence do we have that the technology can deliver consistently?
the disciplines that understand the technology, exposures, loss experience, and the financial commitment being made.
When that process is done well, the result is powerful. You create a product that gives customers greater confidence in the technology, gives the technology provider a stronger value proposition, and allows the insurer to support risk reduction in a more direct and meaningful way.
A performance guarantee puts HSB’s financial commitment behind a specific outcome. How do you define and measure that outcome in a water intelligence context, and how did you arrive at those definitions?
In a water intelligence context, the outcome is not simply that a sensor detects moisture or generates an alert. The real value is whether the system can identify abnormal water behavior early enough, respond effectively, and reduce the likelihood or severity of water damage.
So the definitions need to focus on performance that matters in the real world. That may include the system’s ability to monitor water flow, identify anomalies, distinguish between normal and abnormal usage, trigger notifications, and initiate shutoff where appropriate. The outcome has to be tied to meaningful mitigation, not just detection.
We arrive at those definitions by combining several perspectives. Engineering helps us understand the technical capabilities and limitations of the system. Claims experience shows us how water losses actually develop. Underwriting helps us understand the exposure and financial implications. Field data helps us validate whether the technology performs consistently in live environments.
The goal is to define an outcome that is measurable, practical, and aligned with loss prevention. If the definition is too broad, it becomes difficult to insure. If it is too narrow, it may not reflect the customer’s actual risk concern. The right structure sits at the intersection of technical performance, customer value, and insurance confidence.
Perspective on Water Risk and Mitigation
If you were advising a risk or facilities manager at a large commercial property portfolio on where water risk should sit in their overall risk management priorities, what would you tell them based on everything you’ve seen at HSB?
I would tell them that water risk deserves a much higher position on the priority list than it has historically received.
Many organizations have strong protocols around fire protection, security, life safety, and equipment maintenance. Those are all essential. But water damage is often underestimated because it can seem routine or localized until a major event occurs.
In reality, water losses can be enormously disruptive. They can damage property, interrupt operations, displace tenants, delay construction schedules, create mold or environmental concerns, and result in significant secondary costs. For a large commercial property portfolio, the exposure is not limited to one building or one incident. It is a systemic operational risk.
The good news is that water risk is also highly actionable. Facility managers can identify vulnerable areas, improve response protocols, install intelligent monitoring and shutoff technologies, and use data to manage the exposure more proactively.
The organizations that do this well will not only reduce losses. They will improve operational resilience, demonstrate stronger risk governance, and potentially create a better underwriting conversation with their insurers.
You’ve evaluated risk across a wide range of equipment and technology categories over your career. Where does water damage rank in terms of frequency and severity compared to other loss categories you see at HSB, and has that picture changed in recent years?
Water damage has become one of the most important loss categories to address because it combines frequency, severity, and preventability.
Historically, many people thought first about fire when they considered catastrophic property risk, particularly in construction. Fire remains a serious exposure, of course, but the industry has made significant progress over time through better codes, fire protection systems, site controls, and mitigation practices.
Water is now following a similar path. The frequency of water-related losses has made it impossible to treat them as isolated events or unavoidable accidents. In construction, water damage can occur late in the project lifecycle when building value is high, finishes are installed, and delays are especially costly.
What has changed in recent years is the availability of technology that can materially reduce the risk. That changes the conversation. If a loss category is frequent and severe, but there are limited tools to prevent it, the response is largely financial. But if the loss is frequent, severe, and preventable, then prevention becomes a business imperative.
The opportunity now is to apply the same kind of discipline to water risk that the industry has applied to other major perils: understand the exposure, deploy proven mitigation, measure the results, and continuously improve.
Water risk carries consequences that go well beyond the direct cost of the damage itself, business interruption, tenant displacement, reputational impact. How do you account for those secondary effects when you’re thinking about the full scope of water-related exposure?
That is an important point because the direct physical damage is often only part of the story.
When a water loss occurs, the immediate repair cost may be significant, but the broader consequences can be even more damaging. In a construction environment, water damage can delay project completion, require rework, disrupt trades, affect contractual obligations, and create downstream issues such as mold or corrosion. In an operating commercial property, it can interrupt tenants, affect revenue, create reputational concerns, and consume management time.
From a risk perspective, we have to think about the total cost of disruption, not just the visible damage. That means looking at how water moves through a building, what systems or spaces are vulnerable, how quickly an event can be detected, who is notified, whether water can be shut off remotely or automatically, and how response time affects the ultimate loss outcome.
This is where prevention technology becomes especially valuable. A fast response can be the difference between a minor incident and a major loss. If intelligent systems can detect abnormal water activity and stop flow before damage spreads, they can reduce both repair costs and operational disruption.
For customers, that broader view is critical. The real value of mitigation includes schedule certainty, tenant confidence, operational continuity, brand protection, and peace of mind, not just what appears on an insurance claim.
Looking Ahead
The performance guarantee model, where an insurer financially backs the outcome of a technology, is still relatively rare. Do you see it becoming a more common structure in the industry, and what would need to happen for that to scale?
Yes, I do believe performance guarantee models will become more common, but they will scale only where the fundamentals are strong.
There is growing demand for solutions that create more certainty around technology performance. Customers are investing in digital tools, AI, connected devices, and automation, but they want confidence that those technologies will deliver the outcomes promised. A performance guarantee can help bridge that trust gap.
For insurers, however, the model requires more than enthusiasm for innovation. It requires credible data, clear performance definitions, strong technical validation, and a deep understanding of the risk being assumed. The technology has to solve a real problem, and its impact needs to be measurable.
To scale, several things need to happen.
First, technology providers must be willing to share performance data and subject their solutions to rigorous evaluation. Second, insurers need the technical expertise to assess those technologies beyond a traditional underwriting lens. Third, customers need to see the value of prevention as part of their overall risk and financial strategy. And finally, the industry needs structures that clearly define responsibilities, outcomes, and conditions.
I do not think every technology is suited for a performance guarantee. But where there is strong evidence, a meaningful risk problem, and measurable prevention value, this model can be powerful.
In many ways, it represents the next evolution of insurance: moving beyond risk transfer to support proven risk reduction, and standing behind technologies that make reduction possible
