Hidden Connections That Can Turn Risk Into Catastrophe

Pete Miller [00:39]: Welcome to the podcast. Today we’re joined by Moustafa Naiem, founder of Resiliocs Intelligence, a climate data and risk analytics company helping asset owners worldwide understand and respond to climate risk.

Moustafa’s path here is an interesting one. He holds a PhD in resilience prediction, conducted digital twin research at Cambridge, and did climate adaptation consulting at KPMG. All of it pointed him toward building the tools he felt the industry was missing.

The Resiliocs platform goes beyond identifying climate risks. It tells asset owners why those risks exist, what they’ll cost, and exactly what to do about them.

In our conversation, we explore why climate resilience attracts a fraction of the investment that decarbonization does. We look at how his spatial twin technology delivers asset-level loss predictions without expensive sensor networks. And he describes why true Black Swan events aren’t just big storms — they’re cascading failures where everything goes wrong at once.

Moustafa also talks about why Resiliocs feels a duty to strengthen the resilience of entire communities, not just the premium assets of those who can afford to act.

Pete Miller [02:01]: Moustafa, welcome. Appreciate you taking the time to come visit with us. So as a start, maybe you could give our listeners sort of a high-level introduction to what Resiliocs does.

Moustafa Naiem [02:13]: Hey Pete, thanks for having me. Of course, Resiliocs Intelligence, we are a climate data and risk analytics company, but we provide asset owners with the insights onto how weather-related events impact their individual assets and their portfolios at large. But we don’t stop there. Instead of just giving them indices and risk scores, we go a few layers deep. We tell them exactly what the financial losses associated with these events are and we tell them how to prevent them. So we give them a list of adaptation investments and we tell them these are the actions that you can take to protect the value of your investments and the value of your assets. This is how much is it going to cost and this is how long it takes before you get your money back.

Pete Miller [02:54]: That’s great. It’s a very interesting concept. So, you know, in doing some research, you have a fascinating background, right? You have a Ph.D. in resilience prediction. You worked on digital twins while at Cambridge, and then you did climate adaption work at KPMG. So what was the moment where you decided to start Resiliocs?

Moustafa Naiem [03:16]: I started my Ph.D. working on community resilience prediction. So we’re trying to understand the behavior of communities at large, including social systems and infrastructure systems and physical assets. And we were using different new methodologies, machine learning models coupled with engineering models before AI became a thing. And all of this was enabling us to predict with very high accuracy the impact on those systems.

But I always felt that there was something missing. I needed the models to generate the decision support, to tell us what to do about those things. And that journey led me to beyond predictive analytics, which was at that time, digital twinning. And I did some research at the time. I remember I found a center at the University of Cambridge called the Centre for Digital Built Britain and they were housing the National Digital Twin Program and they were setting the standards worldwide for digital twin technologies in urban environments. So I reached out to them, I had some time left in my Ph.D. and I did have some funding from some grants and awards that I received. So I decided to take up all that what is left and just go there, try to learn as much as I can. And I did so, we delivered on a couple of projects to a few partners. It was a very enriching environment for myself, for the journey, and I was determined to deliver all of that impact that I learned and the newer technologies into the hands of the people that actually need it.

So I came back to Canada and started working in consulting space, as you mentioned, for a couple of years working in adaptation projects. But I always felt that there was something missing with the tools that we were using to provide our customers with the insights that they needed. Without these proper tools, it felt as if I was trying to solve a problem with both hands tied behind my back. And that was the moment when I realized that this status quo cannot continue if we really need to drive actionable intelligence into the industry with products that would lead that wave, instead of relying on expert opinion and in writing on the traditional consulting method with opinions that are honestly based on a climate that no longer exists.

So I decided then and there to just start to do some research onto the tools that existed. And when I didn’t find the one that really was delivering the value that I knew could be delivered, I decided at that time to start capitalizing on all the experiences that I’ve gained and build the tools that would be needed and used in that space.

Pete Miller [05:48]: So you say a lot of them were built for a climate that doesn’t exist, right? So, you’ve made the statement that climate resiliency is often hijacked by the race to net zero. So what does that mean to you? Why is this adaptation gap such a critical problem for insurers and asset managers?

Moustafa Naiem [06:07]: So, I historically from working with a lot of people in the clean tech space and the climate space, all the regulations and all of the reporting mandates that are being issued and the investment incentives that are being issued to other people all revolve around the trade to net zero, decarbonization, hitting our targets. And that is critical and it’s needed and it’s absolutely necessary so that we can avoid a worse future than what we have right now.

But where we are right now is pretty bad enough. People are losing their homes, people are losing money, the insurers are pulling out of entire markets and people are being evacuated. I remember there was an event that happened in Quebec and New York City a couple of years ago and over 100,000 people were left without power for a few days, let alone heating, let alone all of these systems that depend on that critical infrastructure.

All of that because the risk wasn’t accounted for. All of that because we were trying to do other things rather than increase the resilience of our built environment. So, I looked into it and I realized that for every dollar spent on adaptation, at least five are spent on mitigation or decarbonization and so on. So it felt like a huge gap and people are losing money and businesses are losing operation and people are being affected, their livelihoods and the quality of life being affected due to the lack of adaptation investment and our capacity to protect what we hold dear, which is the way of life.

So at that moment, it became clear that the conversation needs to shift and looking into physical climate risk and its impact on physical assets and performance at large needs to be something that everyone at least once needs to look into. Even if they look into it and they realize that they’re good, like there’s no nothing for them to be scared of. That’s fine, but at least look at it at least once.

Pete Miller [08:03]: You mentioned a little bit ago about digital twins. So, for our listeners who are unfamiliar with that, can you talk about a digital twin and how it’s different from traditional flood or risk models that have been used for a while?

Moustafa Naiem [08:19]: Yeah, well, digital twinning as a term or a technology, as a concept, it’s been there for quite some time. It’s being used in manufacturing and in other industries, but it was never adopted at a built environment scale because of the lack of computational tools that would allow us to do so. Not anymore though. But digital twinning in simple terms, it’s when you have a digital replica of the physical asset that is connected to it and mimics the exact behavior and mirrors the current conditions of the physical assets. So you have a few components. The physical asset, which is the building or the infrastructure system that you have, a virtual asset that represents its behavior, and a bridge that connects the two together so that any changes in the physical asset would reflect directly into the virtual asset.

Once you have that, you unlock the power to do predictive analytics way advanced, more advanced than anything else we’ve had because we would have enough data onto the history of the individual asset and many other assets like it that we can draw insights from and include in the decision support or decision making for that system that we created. So in a nutshell, that’s a digital twin.

Instead of where when people use proxy data or mathematical models to model certain behaviors, I say we often lack the insights to look at the wider system behavior when we do that. doing the digital twinning concept onto that space allows us to unlock what is called systemic risk. And systemic risk is how, think of it as a domino effect, how one impact at one node or asset within your portfolio, you can cascade to catastrophic events or catastrophic impacts across different assets or components within your system.

I always start with this example. If you have a commercial building in a downtown area, this commercial building has a server room, it has some offices, and then a flood event happens like the one that happened in Mississauga twice last year or downtown Toronto. This event happened. The water doesn’t really damage your building, but it knocks out the power of the entire district or it cuts access to your building. Now, you are left without power. You lose business opportunity and you’re subjected to certain vulnerabilities that you didn’t account for. And now you lose access to the building as well. So you can’t get enough diesel to generate, to like fuel your generators so that your server rooms can stay up and running.

So it really results in a catastrophic failure throughout your entire system, but your building wasn’t damaged. It’s just the way it operates and the way it relies on other systems. This type of cascading failure in general is only achieved or looked into when you have a true system representation. And that can be done by digital twin technology or a proxy of it, or something that adopts certain features of a digital twin. If you don’t want to be instrument intensive, for example, installing sensors everywhere and whatnot, but that same methodology or idea needs to be applied so that you’re able to capture this impact.

Pete Miller [11:26]: As somebody who went to high school at the south end of Mississauga in Port Credit, Moustafa, I had heard there was one flooding event. I didn’t hear there was two. I’m sorry to hear that. You talked a little bit about sensors and the importance of sensors. And I know that many digital twins, because as you say, they’ve been around a little bit of a time, but they do require a lot of really expensive IoT sensor with real time, continuous synchronization, but you have a different model, right? I think you call it spatial twin. Can you tell us a little bit about that framework?

Moustafa Naiem [12:00]: Yeah, it was a research project that you worked on that we were trying to adopt that into what we were building at Resiliocs. So Spatial Twins is basically pulling out all the features of a true Digital Twin and then removing all the blockers that would allow you to deploy at scale. So, for example, Digital Twins require, as you mentioned, IoT sensors, they were Internet of Things sensors to be installed everywhere with continuous Internet access. They have to be synchronized and that can be very expensive to deploy. It can be a roadblock to achieving the benefit that you need to do. So we came up with a way of instead of doing all of that, we can look at the features that we need for our analysis and extract that from a spatial data set perspective, then apply the same system architecture, but without the integration of IoT sensors. But we use, for example, satellite data, we use other climate science or climate modeling in this specific geographies that allows us to pull in the features that we actually need to get the value that we want without it being too expensive for us to deploy at scale.

Pete Miller [13:08]: Cool. So many commercial property owners, like they don’t have access to the same tools that insurers have, right? So, and I think Resiliocs changes that. So can you say what that change looks like for, you know, like let’s say a real estate commercial property owner with a

Moustafa Naiem [13:25]: Well that’s a good question. The tools that are created in in that space are tailored as you said to insurance and insurance they have a specific use cases for that type data so they use it for other things so to them it’s an insight and an input it’s not an output asset owners they behave differently the way they make decisions relies on a different layer of data and to address that we built Resiliocs not added as a data company per se but as a decision support tool.  We added all the layers to the output that the asset owners can and should use. So, we predict the risk. We don’t just tell them what the risk is We tell them where it came from why it is the way that it is So if you’re expected to lose five million dollars in the next ten years, we tell you why Why are you losing ten or five million dollars in those number of years?

And in our models, there is an entire adaptation module that explains to you what are the drivers that cause this loss and disruption and impact to your overall system. What are the measures that you can use to reduce these losses? How much is it going to cost you to implement those in whatever format? And then what are the short and long-term benefits across your entire portfolio, not just this single asset?

And we allow you to pick and choose based on your budget constraints, which measures makes the most sense so that you can get the highest ROI, not on a single decision, but on a mix of decisions so that you can have coverage across your entire portfolio, given that the insights we provide, we provide at an asset basis. So, all of that was built with the vision of the asset owners actually using that platform to inform capital allocation decisions, and inform the way that they manage their portfolios.

Pete Miller [15:18]: So, one of the things you mentioned was data and machine learning and different statistical techniques. So, I think one very interesting thing about your platform is you can do what-if scenarios like Monte Carlo simulations, right? So can you give us an example of how a municipality or insurer might use this to make decisions to prevent damages before they happen?

Moustafa Naiem [15:37]: Yeah, well, I’ll give you a scenario that we ran through with one of the municipalities that we did an early engagement with to test all the models that we were building. We built a model that predicts the impact of like flooding, for example, they had a river in that city. So we built a model that predicts the water level changes and the impact of extreme rainfall at the rivers catchment onto the basin of the river or to the actual city. And we deployed that model with that city. And in doing so, we were able to capture with a significant lead time, seven to 10 days, what is actually going to happen in that location? What is the flood intensity and what is the footprint or the floodplain? And in doing so, we were able to ingest into the platform all the municipally owned assets and assess their vulnerability to that flood event.

So, we looked specifically at the time at the emergency response network, all the buildings that are used for evacuations because this city was disrupted multiple times before and people need like over 150,000 people left their homes, I remember at one of the events. So, we assessed all of the locations that are being used for those evacuations, schools, stadiums, hospitals, anything that is municipally owned that we had access to. And in doing so, we were able to overlay socioeconomic data onto this layer of assessment.

So, in a nutshell, what we did is that we assessed the resilience of the entire community, not just from a physical aspect perspective, but also from operations and disruption perspective. What we did there, we were able to accurately capture the impact of that event on all of the municipally owned assets, the associated disruption and damages that are predicted from that event, and the robustness of the emergency response network. And we created an emergency plan for them based on this. And we identified the vulnerabilities in that network that we developed an adaptation plan and gave them, if you implement those recommendations, your resiliency would jump from the point you are now to like, five-fold or like four-fold in the next five years. If you start implementing those adaptation measures onto these specific assets that are very critical in that situation. And yeah, so that was one way that we did that with different municipalities.

And in the platform, even though we haven’t deployed it yet, but we built an entire platform for asset owners in the public sector. So all municipalities, all different levels of government can access that platform and can assess the overall community resilience of certain cities and the socioeconomic disparity or how different neighborhoods with different characteristics are impacted adversely from these climate impacts.

Pete Miller [18:32]: So, does the number of layers that you apply to a property vary depending on location and perils and their vulnerabilities?

Moustafa Naiem [18:42]: Well, yes, each location has its own properties when it comes to the climate it’s subjected to and the different drivers that would cause the impacts on losses. So, yeah, that definitely is, but we are not, I mean, it’s an important distinction, but we’re not, for example, on homeowners, for example. Like if an individual comes to us with a home address and tells us, that’s probably not, we’re not the right tool for them to be using right now, at least. So, we work with institutional asset owners, people who own, as you mentioned, about a billion in a portfolio at least. And then we work with them on protecting the value of all of the assets under the management.

Pete Miller [19:20]: So your pilot projects show pretty remarkable and awesome results, like 87% prediction and $3 billion in projected savings and multi-hundreds of ROI. So how do these numbers change the way the insurance companies, price risk, or municipalities invest in infrastructure?

Moustafa Naiem [19:40]: Well, I’ll tell you from the actual aftermath of the pilot, what we did is that we presented all of that information to the city officials and we walked them through how the numbers were calculated and what were the drivers for the losses and we benchmarked against recent events where there was a hail event and the city lost, say, $8 billion dollars and we talked to the insurers in that space and I think one of them one of the major insurers carriers, lost $1.8 billion in that single day, single event. There was already insurable losses like that from property and casualty insurers. That was it. And the lack of capacity to be able to predict those, I think is the main driver for such losses on both sides.

People aren’t able to accurately assess the impact of those events so that they, as a result, wouldn’t be able to accurately price them. And as a result, wouldn’t be able to actually underwrite them. So having this foresight onto how these are going to impact specific locations that are previously thought uninsurable or thought that it’s not going to ever reach that point, that definitely changes the way insurance does things.

And also we realized in those conversations that insurance uses an umbrella approach. All the homes in a single road will have the same insurance if they have the same properties. But what they fail to look at is that the level of the street at the top of the street is completely different than that at the bottom of the street. And this home or this house or this asset is not going to be flooded when an extreme rainfall occur. But the two at the bottom, they’re done, they’re toast. And they don’t account for that. So they lose in some location, they win in some location, but there’s a level of whether this is fair or not. It’s a conversation that I think the industry needs to start having.

Pete Miller [21:25]: That’s a really good example. I’m sure we can all visualize that. I live on the top of a hill and it’s a steep hill. And I know you don’t do residential, I don’t want to live at the bottom of the hill in a flood. That’s all I know. So anyway, one of your key differentiators from what I know is a focus on systemic risk and cascading failures. So can you explain what that means for climate risk and, why that’s what actually makes a Black Swan event a Black Swan event.

Moustafa Naiem [22:58]: Yeah, if you remember in 2008 when the economy collapsed in North America, across the world actually, it failed because of systemic failure. It wasn’t a single event that resulted in this. And people who study these type of financial systems understand the impact or understand the fact and footprint of cascading risks and cascading impacts.

But it was never adopted in any other industry. And when you look at the different events that occur, you say, you hear a lot of people talking about black swan events. And a lot of people in their minds, black swan event is the tail end event, that the ones that with a high intensity flood, for example, that’s a black swan event. But in reality, that’s not the case. A black swan event isn’t just a high intensity hazard. A black swan event is when everything that can go wrong goes wrong at the same time.

So when you have a flood event that takes place that knocks out the power and because there is no power, the transportation network is disrupted. And because the transportation network is disrupted, ambulances can’t get to their hospitals. And because that happens, people die. That’s a black swan event because all of these systems failed on top of each other. Not that the rain was too much.

And that is the main driver behind systemic risk. When we started looking at community resilience rather than single asset or single portfolio resilience at the research like 10 years ago, when we started looking at it, we came to that realization. It’s not a single system. It’s not a single thing that causes all of this damage and all of the disruption to our livelihoods. We need to start studying all of the interdependence between the system. So in a way, it’s a system of systems.

And that is one of the key drivers that were the questions that we were really asking at the beginning of our research journey. And that lens led us to cascading impact and cascading failures and how we can use that to increase the resilience to climate change. And the example that I gave on the different systems failing at the same time or earlier when I talked about the commercial building in a downtown area, all of those are examples of cascading failure.

And I will give another example that happened in our alma mater actually, like the university where I my Ph.D. They have an interconnected system where the heating comes from a certain reactor in one side of the campus, but it covers the entire campus. And when I think one time there was a flood event, but it exceeded the capacity for the sewage network and the main one erupted, it flooded the underground for one of the children’s hospital we had on campus. And at the same time, this reactor room was flooded.

So, they had to shut down and half of the campus was left without heating in the Canadian cold, mind you, for a few days until they were able to fix it. That’s a systemic collapse. And it happens not at a fault of a single asset, but these different components were built at different centuries even. So having the capacity to look at the entire system at the same time is something that I don’t think anyone ever thought of looking at. And we wanted to be the first to start probing people to look at it from that perspective.

Pete Miller [25:12]: You mentioned a little bit earlier communities and I think your website says, kind of highlights how vulnerable communities often get left behind while high valued assets get protected. So how does Resiliocs address this and why is that important from a risk management perspective?

Moustafa Naiem [25:31]: Well, think of it that way. If we keep on protecting the dams or protecting the data centers and we forget to protect the systems that ensure that the people who work in those locations are able to do the work that they do, are able to live a decent life and not worry about their mortgage and not worry about the way that their children will go to school, for example, or whatnot. You kind of realize that it’s all parts of the whole picture is all part of the same thing. And to increase the efficiency and the value of one thing, you have to look at the entire system and bring it all up instead of just focusing on the high value items within that location.

And that was kind of, I want to say the vision, it was, you know, the duty that we felt when we first starting this, that’s why the first pilot we ever did was with the public sector client, because we wanted to prove the value of it. Of course, for a startup, working directly with public sector is not the most survivable way for us to hit our goals and targets and grow. So, we had to pivot to private sector and work on individual assets with larger portfolios and then work our way to that. But it’s part of our obligation toward the communities that we live in is that we account for the wellbeing and the livelihood of the people around it to make sure that what we offer we don’t just offer to the people who want to protect certain assets but to the ones who want to bring the whole community up.

Pete Miller [27:00]: Well, it’s certainly impressive what you’ve done, certainly to date, and many more exciting things, I think, going forward. When you do look going forward, so what’s your vision for Resiliocs, and how do you see sort of the market for client adaptation changing over the next five to 10 years?

Moustafa Naiem [27:21]: When we think about Resiliocs in years from now, we think of it as the climate-informed layer for all capital allocation decisions. So all the asset managers and asset owners, want to make capital allocation decisions, they want to protect the value of their investments, they want to do asset management, regardless of the nature of that asset. And we want to be the layer that informs the climate piece of that decision-making. How to make sure that you account for climate extremes and weather events when you’re making your capital allocation decisions on your balance sheets and on your budgeting and on all the things that are related to your physical assets. So the vision is to become that layer that informs all of these decisions. That is where we think we’re going and that’s the vision that we’re working towards five years from now.

Pete Miller [28:12]: I know you’ve done work around the world, and I’m just curious, how does the acceptance or view of climate adaptation change in different areas of the world?

Moustafa Naiem [28:25]: Okay, well over the past couple of years or a year and a half when we started working on Resiliocs and we started having the conversations with the asset owners and the people in the North American market, we realized that the entire market is based around insurance because it carries all the risk. And insurance is a very tough nut to crack. It’s built in a way that makes change in it very hard.

But when we believed that it’s not going to be the same way anywhere else, we ventured outside and started talking to people in Hong Kong. We started talking to people in the Middle East or in Asia or in Europe. And we realized that the behavior changes wherever the geography is. So not all the industries are built the same way. And some other locations, people want to manage this themselves. And people don’t rely on insurance as much in certain geographies because the market is not as mature as North American market and so on. And these locations are the ones that are, one, very vulnerable, two, more and more investments are being poured into.

So as more investments and more development and more growth are being poured into these markets, they need the support to start looking at that early on. Learning from the experiences that most of the people have seen in North America where they started looking at it retroactively after they’ve been hit multiple times or have been damaged multiple times. So that is something that we noticed and try to be part of those conversations wherever we go. So we started having the conversations in the different geographies and now we have a couple of pilots in Hong Kong. We have an engagement going on in the Middle East. We’re trying to build the business case so that people can look at it from early on, early days, before it becomes an issue that they would have to retroactively deal with.

Pete Miller [30:14]: Thank you very much. I’m really grateful. think what you’re doing is pretty great. I think it was very interesting.