Customer Story Transcript:
"My name is Scott McNea and I'm a property and casualty broker for Alliant Insurance Services. And prior to this role, I spent almost 16 years as both an engineer as well as an underwriter. So I have a deep background of the property focus. I worked for a large property insurer for that entire time, so kind of a specialist on all things property insurance, mitigation, and property loss prevention. There was a definite need for that type of focus, specialization and having that technical knowledge on all things property focused as things get worse and worse. When I say worse and worse, when they get more challenging for our clients in terms of natural hazards and secondary perils, things that we haven't modified or measured before, like hail and freeze and wildfire, it really paid to have that deep understanding and be able to help my clients protect their assets and protect their operations and kind of make them more resilient.
I don't really dabble too much in the things that I'm not an expert in. I really want to focus on having that deep level of knowledge. Again, to be able to help the client and work through their solutions. Sometimes, it's not all about risk transfer. Sometimes you can have risk mitigation strategies or put into the budget the means to enhance and strengthen your operations or your protection systems or your construction components. And having that ability to be able to work through that with them is really kind of paramount and I think it sets us apart. And having that engineering background, a lot of the times when we went out to the field, I would do onsite assessments, right? And really, I mean everything from measuring the size of the thickness of the steel deck and the thickness of the insulation and understanding where individual components and really identifying these exposures on a granular level.
And when I came to Alliant and when I came to actually the broking industry, we utilized modeling and I had not utilized modeling before and modeling is – what I would understand it at the time – was the industry's best way to estimate what property loss was going to be in the event of a large hurricane or an earthquake or a wildfire or a flood, rather than going to each and every single little building and saying, it's the water's going to be this high or this roof is not going to withstand the wind forces. We really had to open ourselves up to understanding that modeling. And I think that was one of my biggest challenges, and quite frankly, one of the greatest opportunities that Archipelago kind of helped me understand what we were looking at and what were the data points on that.
We would do the best that we could. We took the statement of values that they had, tried to identify any pieces of missing information as best we could, and then we'd send that over to the modeling agencies, RMS, AAR, and just hope for the best. I hate to say that that's what it was, but if we identified some missing construction or missing latitude, longitude, or being able to identify where critical locations were, we did our best to do that and filter through missing data. But when it got down to if you got 100, 150 locations on your statement of values, we'd try to focus on the top entities: most important buildings, critical operations, things that they needed within their supply chain to be able to help them out the best. But it was very difficult to get all 150 and go through 60, 70 data points per location. It got daunting. And in this business, time is money and sometimes you just kind of do your absolute best and then give it up to the modeling agencies and see what they come out with.
I've been at Alliant here in the position I'm in for a little over a year and a half, and right when we got onto the team, we were introduced to Archipelago. Our company had created a partnership with it and they brought me into it, and I had utilized a lot of the tools before that, CoreLogic and RiskMeter,the worst- in my previous role. So understanding what they were looking for, it was very seamless to me to be able to make that transition. But I love the fact that they would actually go through the data for us and pick out the missing data that we needed. And it was told to me, and I don't know a hundred percent if it's true, but they said, if we don't know, it's guilty till proven innocent, right? If you're near the river, we're going to assume that you're going to flood.
Whether we know the flood, if we don't have that data, we have to assume worst-case scenario. And so there were a lot of issues on these statements of values as we started putting them through Archipelago, where we would find missing data or information that we would need in terms of soft story construction or hazards that could be detrimental in an earthquake or a hurricane. And understanding where those data points, and not only that, but prioritizing what data we needed, which would have the greatest impact on the modeling. And when I say impact, I don't want to say it makes it better because it might cover the dust and we could find out there's problems at the same time. So more importantly, when I talk to my clients, I want them to know that, look, we are trying to get the accurate data and the best that we can for the best results in the modeling, whether that's good or bad, because we want to understand our strengths and understand our weaknesses so we can make the appropriate decisions to protect ourselves.
Without Archipelago it probably would've had a greater comparison data, but I really kind of came in right as we were embracing Archipelago as a company and kind of championed it and really dove in and understood it. But I can tell you that as I started getting more and more statements of values in, and as I started helping out other brokers and other clients, really, I started identify these data points that were missing and being able to enhance that information to get the most accurate results.
I've got a very large client in the Pacific Northwest, we'll just say that part of the country, and we came in, they really didn't have a lot of data. It was kind of piecemealed together, right? There had been previous management that kind of did it their way. And the new management came in, was trying to really build this program up, and the statement of values was very piecemealed. Holes everywhere, really didn't understand construction on that granular level that we were talking about.
And we put on Archipelago, the original statement of values in, and it came up with just a litany of questions and information, lots of priority recommendations for enhancing the data. And we really kind of worked with the client to embrace that and said, here's the information that we need to try to get this model. Not only for the flooding, we didn't really have a hurricane problem in the Pac Northwest, but the earthquake. Things like soft stories and large bays and areas that we really didn't understand what the consequences would be. And the modeling agencies will always default to the worst-case scenario, and we know that. So when we actually started cleaning up the data, we really started to improve that AAL. And when I say that, we started lowering it as well as the aggregate. Not only that, but we started to dive into other information and getting the reports of old appraisals, or not even old appraisals, but appraisals that have been done, but we were able to upload those into the system and it would identify, Archipelago kind of picks the data that we need and populates that SOV.
And man, honestly, one of the best things is as we've done year after year, going into my second renewal with this client, we are continuously improving it. I tell people when we work on Archipelago, it's a living, breathing statement of values. It's something that we don't have to redo year after year. It only gets better. And each year we can prioritize the things that we want to work on, the data we want to improve, as well as what areas that we need to focus on in terms of appraisals or construction efforts or even mitigation strategies with construction loss prevention strategies. So it really does, it kind of almost created us a roadmap from start to finish on where we are and where we want to be, and then understanding those steps that we needed to take to get there so it's not daunting for us and it's not daunting for the client, and it gives them actual steps that they can, it's achievable, but at the same time, we can see those results as they come through, once we do the modeling.
I want to say we pulled it down by about 15%, and that's just off the cuff where I came in. But that's significant when you're talking about millions of dollars of losses per year and understanding what that financial consequence could be. And then again, it allows us to compare that side by side with our limits, our deductibles, and those make way better challenges. Perhaps the client, I'm going to take a little bit more risk, or maybe they need to take less risk because our consequences would be a little more severe. And then through that, we can utilize those data points to understand where to focus our efforts. And perhaps again, maybe it's better data. Maybe we need to start thinking about construction efforts. Maybe we need to think about retrofitting systems or enhancing sprinkler protection, bracing, or these type of things to make sure that we have the absolute, that we're protected from that peril.
I think that this is a program that everybody can use. I mean, I'm blessed to have that technical background, and I do kind of always see it from an engineer and take my engineer hat and kind of still put it on as I'm starting to evaluate what that risk can be. But even if I didn't have that, here's a tool that would walk me through those steps. And then when I train other brokers, I've actually become almost a champion internally for Archipelago. And people will come to me with questions and I can show them how you can enhance your data, what are the recommendations you need to do, what is, in terms of what I call them, the yellow flags and the red flags, these are the things that we should probably look at as opposed to the things that we need to put attention to right now, because they're going to have the biggest impact on the modeling, which then has the biggest impact on premium and terms and conditions from your underwriter.
And this is the information they're looking at when they're making those decisions on what's best for their own pocket and their own book of business. And so it's almost like a team effort, but I know I kind of went around the bend, but I do think that if people were to take the time to learn this and understand what they're trying to accomplish with it, this is a tool that anybody can use. And the best part is, I mean, sometimes the machine does most of the work. Every time you get a fire report, an engineering report, a roof evaluation, an appraisal, anything that has that information on the building, we can feed that into the system and the machine learning and the AI picks that data populates your SOV and then updates the priorities to be able to tell you what it is you need and where you can get better. I would say that it is a way to create, for your client, a living, breathing statement of values that we can consistently work on year after year that makes sure that we have the most accurate data for modeling, which in turn saves money and protects your operation."
