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Insurance Companies Are Engineering Firms First
Key Takeaways
Equipment risk reduction has always been part of HSB’s business. What’s changed is how the company gets there. John Stokes, SVP of Technology Risk Solutions at HSB, joins Practitioners Unplugged hosts Dante Vaccaro and Sree Hameed. Together, they explain why real-time equipment data is turning industrial insurance from a backward-looking payout into a genuine prevention strategy.
An Engineering Company First, an Insurance Company Second
HSB, short for Hartford Steam Boiler, marks its 160th anniversary this year. The company’s founding story has little to do with underwriting. In 1865, steam boilers were exploding at a rate of roughly once every four days across American industry. Most people considered it an act of God, comparable to an earthquake or a hurricane.
That changed when a boiler explosion aboard the steamship Sultana on the Mississippi River killed more than 1,100 passengers. It remains the deadliest maritime disaster in U.S. history, and it became a tipping point for boiler safety nationwide.
In response, HSB’s founders created the Hartford Standards: specifications for how boilers should be designed, manufactured, and maintained. Those standards became the foundation of the codes that steam boiler and pressure vessel operators still follow today. Notably, HSB issued its first insurance policy only after establishing itself as an engineering and standards organization.
That order has never reversed. HSB employs nearly 3,000 people worldwide, and more than half hold a technical or engineering background. Inspection and engineering come first. Insurance comes second.
From Actuarial Underwriting to Real-Time, Observable Risk
For most of the insurance industry’s history, risk has been priced through actuarial underwriting. That means measuring risk based on how losses trend over time. It’s a backward-looking method, and one that depends on getting eyes on equipment in person, which is slow and expensive.
In fact, Stokes describes a shift already underway, one where connected equipment and real-time data start to replace estimation with observation.
“We’re moving away from this model where insurers are estimating risk only through these actuarial principles, and now we’re onto these more observational, observable and measurable risk through real-time insights from connected equipment and data.”
John Stokes, SVP, Technology Risk Solutions, HSB
That shift matters for claims, too. Richer data, Stokes says, will improve the experience for every stakeholder in the chain: the insured, the OEM, and the insurer itself.
Equipment Risk Reduction in Practice: Cutting Risk by Up to 90 Percent
The clearest evidence for equipment risk reduction through technology comes from HSB’s own performance guarantee work. Stokes points to vibration monitoring on rotating equipment as a concrete example. Picture a motor driving a pump in a wastewater facility, or an industrial fan in a data center. Traditional vibration monitoring flags a problem only after it already exists, usually forcing an unplanned overhaul, repair, or replacement. Machine learning applied to that same data works differently. It catches the first anomaly and turns a catastrophic failure into a minor maintenance task instead.
“We’ve done performance guarantees where it’s been in our assessment that the presence of technology can reduce that risk on a single piece of equipment by as much as 90 percent. That is strong and really impactful when it comes to insurance costs.”
John Stokes, SVP, Technology Risk Solutions, HSB
That number changes the calculation for manufacturers weighing a technology investment against its return. Factor in what that level of equipment risk reduction saves on insurance costs and maintenance budgets. The technology can pay for itself well before the depreciation schedule says it should.
The “Uber for Machines” Model: Selling Outcomes, Not Equipment
Stokes draws a direct comparison to Uber’s disruption of transportation. The technology, not a better vehicle, made that model work. He argues the same shift is underway in industrial equipment, with OEMs moving from selling machines to selling outcomes.
“Think about an Uber for machines model where OEMs are not just selling equipment, they’re selling outcomes. Equipment as a service. No capital expense required upfront. The customer is really paying for that equipment based upon how it performs and what it ultimately produces.”
John Stokes, SVP, Technology Risk Solutions, HSB
Rolls-Royce proved this concept decades ago with its Power-by-the-Hour model for jet engines. Airlines paid a flat hourly rate rather than buying engines outright. Stokes sees the same logic extending into manufacturing plants and logistics centers, especially as robotics make automated production lines more common. The model only works if three things are true. The equipment must be connected, the data must be available, and someone on the other end must know what that data actually means. Without all three, Stokes is direct: it doesn’t work financially for anyone in the chain.
“Hope Is Not a Strategy”: Why Prevention Beats Payout
In practice, the obstacle to wider adoption of these models is rarely the technology itself.
“We’ve all heard hope is not a strategy, right? And there’s a lot of ways to plan for the bad things that are gonna happen, and I think insurance is just one of those. The basic principle of insurance is that it responds when something bad’s already happened. Mitigation and prevention are much more important, and that’s where technology plays a role in many use cases, if not all.”
John Stokes, SVP, Technology Risk Solutions, HSB
Relatively small technology investments, Stokes notes, aren’t always easy to implement. That’s largely because of a cultural divide: OEMs and their customers have operated the same way for decades. Evolving that mindset, from “bad things are gonna happen, that’s why I need insurance” to “I have things at my disposal to keep those bad things from happening,” takes time.
The CFO Is the Real Catalyst for This Shift
Stokes is direct about where the decision to adopt these new models ultimately gets made: the CFO’s office. The conversation has to pencil out financially before it goes anywhere else, and it can’t only be about day-to-day operations. It has to show an improvement to the top and bottom line. That means more revenue from producing more with new technology, without shelling out significant capital. It also means lower ongoing operational costs for the equipment itself.
Notably, insurance has a role in that financial case, too, not just paying for unexpected equipment damage but standing behind the overall financial model of an as-a-service arrangement. As more OEMs and end users test these waters together, equipment risk reduction stops being a technology story. It becomes a finance story, and that’s exactly the audience Stokes believes will ultimately drive this shift.
Frequently Asked Questions
HSB and Equipment Risk Reduction
What is HSB, and how is it connected to insurance?
HSB (Hartford Steam Boiler) is a specialty insurer and inspection company founded in 1865, now part of Munich Re. It provides equipment breakdown insurance and other technical risk coverage, with roots in industrial engineering and safety standards rather than traditional underwriting.
How much can technology reduce equipment risk, according to HSB?
In HSB’s own performance guarantee assessments, proven, connected technology has reduced the risk profile on a single piece of equipment by as much as 90 percent, according to John Stokes, SVP of Technology Risk Solutions at HSB.
Why is insurance moving from actuarial underwriting to real-time risk monitoring?
Actuarial underwriting prices risk based on historical loss trends, a backward-looking approach. Connected equipment and IoT sensors now let insurers like HSB observe risk in real time, enabling more accurate pricing and earlier intervention before failures occur.
Equipment-as-a-Service Business Models
What is the “Uber for machines” model in manufacturing?
It describes a shift where OEMs sell equipment outcomes rather than the equipment itself, similar to Rolls-Royce’s Power-by-the-Hour model for jet engines. Customers pay based on performance rather than upfront capital expense, and the model depends entirely on connected equipment data.
What does “equipment as a service” mean for manufacturers?
Equipment as a service shifts ownership away from the manufacturer’s balance sheet. Instead of a capital purchase, the manufacturer pays based on the equipment’s output or uptime, while the OEM retains responsibility for keeping it running.
What’s the biggest barrier to adopting predictive, technology-driven insurance models?
According to Stokes, the barrier is cultural, not technical. OEMs and end users have operated the same way for decades, and shifting from a reactive mindset to a preventive one takes time, even when the financial case is strong.
Keep practicing, keep learning, keep transforming.
To follow more of HSB’s work, visit HSB’s site or connect with HSB on LinkedIn. For another Practitioners Unplugged conversation on shifting from reactive to predictive operations, see Episode 15 on transforming water infrastructure.
To submit a request for a new episode topic from Practitioners Unplugged, visit our contact page.
Explore more about Schneider Electric & AVEVA
View all episodes
By IndustrialSageKey Takeaways
Equipment risk reduction has always been part of HSB’s business. What’s changed is how the company gets there. John Stokes, SVP of Technology Risk Solutions at HSB, joins Practitioners Unplugged hosts Dante Vaccaro and Sree Hameed. Together, they explain why real-time equipment data is turning industrial insurance from a backward-looking payout into a genuine prevention strategy.
An Engineering Company First, an Insurance Company Second
HSB, short for Hartford Steam Boiler, marks its 160th anniversary this year. The company’s founding story has little to do with underwriting. In 1865, steam boilers were exploding at a rate of roughly once every four days across American industry. Most people considered it an act of God, comparable to an earthquake or a hurricane.
That changed when a boiler explosion aboard the steamship Sultana on the Mississippi River killed more than 1,100 passengers. It remains the deadliest maritime disaster in U.S. history, and it became a tipping point for boiler safety nationwide.
In response, HSB’s founders created the Hartford Standards: specifications for how boilers should be designed, manufactured, and maintained. Those standards became the foundation of the codes that steam boiler and pressure vessel operators still follow today. Notably, HSB issued its first insurance policy only after establishing itself as an engineering and standards organization.
That order has never reversed. HSB employs nearly 3,000 people worldwide, and more than half hold a technical or engineering background. Inspection and engineering come first. Insurance comes second.
From Actuarial Underwriting to Real-Time, Observable Risk
For most of the insurance industry’s history, risk has been priced through actuarial underwriting. That means measuring risk based on how losses trend over time. It’s a backward-looking method, and one that depends on getting eyes on equipment in person, which is slow and expensive.
In fact, Stokes describes a shift already underway, one where connected equipment and real-time data start to replace estimation with observation.
“We’re moving away from this model where insurers are estimating risk only through these actuarial principles, and now we’re onto these more observational, observable and measurable risk through real-time insights from connected equipment and data.”
John Stokes, SVP, Technology Risk Solutions, HSB
That shift matters for claims, too. Richer data, Stokes says, will improve the experience for every stakeholder in the chain: the insured, the OEM, and the insurer itself.
Equipment Risk Reduction in Practice: Cutting Risk by Up to 90 Percent
The clearest evidence for equipment risk reduction through technology comes from HSB’s own performance guarantee work. Stokes points to vibration monitoring on rotating equipment as a concrete example. Picture a motor driving a pump in a wastewater facility, or an industrial fan in a data center. Traditional vibration monitoring flags a problem only after it already exists, usually forcing an unplanned overhaul, repair, or replacement. Machine learning applied to that same data works differently. It catches the first anomaly and turns a catastrophic failure into a minor maintenance task instead.
“We’ve done performance guarantees where it’s been in our assessment that the presence of technology can reduce that risk on a single piece of equipment by as much as 90 percent. That is strong and really impactful when it comes to insurance costs.”
John Stokes, SVP, Technology Risk Solutions, HSB
That number changes the calculation for manufacturers weighing a technology investment against its return. Factor in what that level of equipment risk reduction saves on insurance costs and maintenance budgets. The technology can pay for itself well before the depreciation schedule says it should.
The “Uber for Machines” Model: Selling Outcomes, Not Equipment
Stokes draws a direct comparison to Uber’s disruption of transportation. The technology, not a better vehicle, made that model work. He argues the same shift is underway in industrial equipment, with OEMs moving from selling machines to selling outcomes.
“Think about an Uber for machines model where OEMs are not just selling equipment, they’re selling outcomes. Equipment as a service. No capital expense required upfront. The customer is really paying for that equipment based upon how it performs and what it ultimately produces.”
John Stokes, SVP, Technology Risk Solutions, HSB
Rolls-Royce proved this concept decades ago with its Power-by-the-Hour model for jet engines. Airlines paid a flat hourly rate rather than buying engines outright. Stokes sees the same logic extending into manufacturing plants and logistics centers, especially as robotics make automated production lines more common. The model only works if three things are true. The equipment must be connected, the data must be available, and someone on the other end must know what that data actually means. Without all three, Stokes is direct: it doesn’t work financially for anyone in the chain.
“Hope Is Not a Strategy”: Why Prevention Beats Payout
In practice, the obstacle to wider adoption of these models is rarely the technology itself.
“We’ve all heard hope is not a strategy, right? And there’s a lot of ways to plan for the bad things that are gonna happen, and I think insurance is just one of those. The basic principle of insurance is that it responds when something bad’s already happened. Mitigation and prevention are much more important, and that’s where technology plays a role in many use cases, if not all.”
John Stokes, SVP, Technology Risk Solutions, HSB
Relatively small technology investments, Stokes notes, aren’t always easy to implement. That’s largely because of a cultural divide: OEMs and their customers have operated the same way for decades. Evolving that mindset, from “bad things are gonna happen, that’s why I need insurance” to “I have things at my disposal to keep those bad things from happening,” takes time.
The CFO Is the Real Catalyst for This Shift
Stokes is direct about where the decision to adopt these new models ultimately gets made: the CFO’s office. The conversation has to pencil out financially before it goes anywhere else, and it can’t only be about day-to-day operations. It has to show an improvement to the top and bottom line. That means more revenue from producing more with new technology, without shelling out significant capital. It also means lower ongoing operational costs for the equipment itself.
Notably, insurance has a role in that financial case, too, not just paying for unexpected equipment damage but standing behind the overall financial model of an as-a-service arrangement. As more OEMs and end users test these waters together, equipment risk reduction stops being a technology story. It becomes a finance story, and that’s exactly the audience Stokes believes will ultimately drive this shift.
Frequently Asked Questions
HSB and Equipment Risk Reduction
What is HSB, and how is it connected to insurance?
HSB (Hartford Steam Boiler) is a specialty insurer and inspection company founded in 1865, now part of Munich Re. It provides equipment breakdown insurance and other technical risk coverage, with roots in industrial engineering and safety standards rather than traditional underwriting.
How much can technology reduce equipment risk, according to HSB?
In HSB’s own performance guarantee assessments, proven, connected technology has reduced the risk profile on a single piece of equipment by as much as 90 percent, according to John Stokes, SVP of Technology Risk Solutions at HSB.
Why is insurance moving from actuarial underwriting to real-time risk monitoring?
Actuarial underwriting prices risk based on historical loss trends, a backward-looking approach. Connected equipment and IoT sensors now let insurers like HSB observe risk in real time, enabling more accurate pricing and earlier intervention before failures occur.
Equipment-as-a-Service Business Models
What is the “Uber for machines” model in manufacturing?
It describes a shift where OEMs sell equipment outcomes rather than the equipment itself, similar to Rolls-Royce’s Power-by-the-Hour model for jet engines. Customers pay based on performance rather than upfront capital expense, and the model depends entirely on connected equipment data.
What does “equipment as a service” mean for manufacturers?
Equipment as a service shifts ownership away from the manufacturer’s balance sheet. Instead of a capital purchase, the manufacturer pays based on the equipment’s output or uptime, while the OEM retains responsibility for keeping it running.
What’s the biggest barrier to adopting predictive, technology-driven insurance models?
According to Stokes, the barrier is cultural, not technical. OEMs and end users have operated the same way for decades, and shifting from a reactive mindset to a preventive one takes time, even when the financial case is strong.
Keep practicing, keep learning, keep transforming.
To follow more of HSB’s work, visit HSB’s site or connect with HSB on LinkedIn. For another Practitioners Unplugged conversation on shifting from reactive to predictive operations, see Episode 15 on transforming water infrastructure.
To submit a request for a new episode topic from Practitioners Unplugged, visit our contact page.
Explore more about Schneider Electric & AVEVA