Hi everyone. I am Phil Colling, VP of Product Sales here at Orion. I covered the northeast and enterprise side for our risk intelligence and compliance tools. What we're going to be looking at here today though is smarter mall management using the Risk intelligence platform. And so some of the pieces that we are going to be looking at is 1 what is over on risk intelligence 1st and really give you that baseline of where are we starting at in this process and how is the tool used by many firms out there. At that point in time, we'll jump into risk intelligence and mall management and be able to look at what that looks like in action. Throughout the platform and how you can use it day-to-day when reviewing the different models that you have. And then from there, we're going to look at some key tools and integration points that we have between Orion and risk intelligence as well as where does all this live within the fiduciary flywheel that we have here at Orion. And so to really start off, let's look at what is Orion Risk Intelligence. Around risk intelligence is a tool to be able to use with prospects, clients and models from a risk analysis point of view. And so the first piece there on the prospect and client side is really providing you with a workflow, being able to go in, get a risk score for those prospects and clients, being able to see where they're actually at today versus where they're supposed to be with that risk score. Creating a recommendation for them using your different models that you have out there and at that point you're going to be able to create different proposals whether it's a long form or short form is how we typically look at for firms of let's dig into the weeds with this particular client or prospect where this one we may need to just give it more high level overview of what are we doing for them and why are we doing it and then that third component outside of the prospect and client. Is that model piece that's going to be the main focus of our conversation here today. How do you review your models and how do you go through some of those hypothetical testings within the platform as you're looking to make changes within your models? And so when we're looking at that model management piece, some of the pieces that we're going to touch on are the simplified workflows that we have out there for model management and making changes. Being able to go out there and do stress testing after you've made those model changes, as well as being able to go out there and do some reviews of what does that change look like for a model and is that the correct change? And so to really start off, let's look at our insights tool. The insights tool is going to provide you with many different ways to go about making model changes. One of those is going to be our interactive editor, our model optimizer and then our blend models. Interactive editor, it's going to be more on screen in line editing, risk optimization. It's going to be changing the risk score of that model to really match where you're expecting it to be. And the last one being able to add in SMA's or even blend your models together and then from there testing out those changes before you actually implement those. And so the first piece is that interactive editor as you can see here on screen, what we're really doing is in line editing. If you're going to go out there, change the quantity, particular securities within your model or maybe we are going from one security to another as you can see on the screen here, we made a change from Microsoft to Apple, just being able to see what that could possibly look like. And then really the last piece is just removing securities. So if you're noticing that particular securities need to be taken away from your model being able to easily do that. Without having to disrupt your client's portfolios and being able to test it out before going in and doing those rebalances. The next tool is our model optimization tool or as I always like to look at it, it's our risk optimization tool. We may have models out there that are currently much higher than what they were expected to be or much lower. For this one here we're looking at a downside of a - 26. And it's really on our stress testing side of things where we can change that risk score on the downside up or down and we can have the system go a few different routes where we can either auto allocate out the current holdings within your model to have the system get as close to that new risk score that you're expecting, we can also have. The system set up in a manner of asset class and being able to put in your tolerance bands for each of those different asset classes. And then lastly is at the security level where you would also be able to go in set your bands on the Securities of where do you expect each security to be as we're doing this optimization. So if you know. There's particular securities in there that you're going to allow them to get much higher than what we would be doing from the automation process. You would have that ability to do so. Then lastly is the model blender and as you can see within the name, it does allow you to take a model, select securities now that you want to keep in there, but then blend those together with all the existing models that you have out there. So that way you can take two models and really combine them into one. And the other route is being able to take a model and put estimates into that model to create an even more enhanced model for your clients to be able to get out there and utilize as you are doing your rebalances and making sure that that is the best fit for them. And so with that, let's go ahead and actually take a look at how these tools work within the platform. And how you'd be able to use those on screen here. All right. So let's go in and let's take a look at one of the models that we already have in the system and how you can go through and those different tools that we just talked about as well as how you just review models within the risk intelligence platform. And so right here we're looking at our one level model where you're going to be able to come out see what are the holdings within that model. You're going to be able to look at downside versus upside of this model as well as performance and then some of the other data points that we have out there. Now with these data points, we are taking this model against a benchmark that you've associated with it out there. And so as we're looking at those risk measures or if we're going to look at some of those style box reports that we're bringing over from Morningstar, you can click into any of these you can actually see what does that look like versus that benchmark are we? On target of where we're expecting to be, are we a little higher or are we too low at that point in time? From there, you will have the ability to change up your asset allocation levels that you're also looking at as well as the time frames, especially in regards to the risk majors and the performance history of your models. But then when we get into those improved tools that we were talking about just a little bit ago. Now you have the option to be able to go in and pick and choose which route is best for what you're trying to accomplish. If it is the interactive editor, and that's where you're going to be able to easily come out, select the interactive editor and then from there easily go in and make those model changes. So making that model change here to Apple, we can do so. Or if we want to change the quantities of any of these securities, easily be able to do inline editing and then once we save out any of those changes that we've made. It will take us right to our comparison tool to actually be able to see are these the correct changes that we were looking for. So now we're looking at what is the model as it is today and versus the model with the new change that we've just made to it by adding Apple into that model. And a lot of those data points that we saw on the risk profile screen a little bit ago are all going to be here for that comparison. One really nice piece is we are going to highlight. Where each model is doing better in which category? When we're looking at our different risk measures as well as from a stress testing standpoint and being able to see how can each of these models react to those different scenarios, you're going to be able to see some of the performance history, the analysis and then those style box reports again just for you to be able to again do an indepth review of those changes before going out and rebalancing. Now the other routes are going to be that mall optimizer tool that we discussed. We're currently today we're looking at a downside of May of 24 within this model here if we wanted to take this down or up from that 24. So if we were actually expecting this to be more in that 30 range, we can make the change here and have the system auto allocate to get as close to that new risk score as possible. But if we did want to go in. And we wanted to add some min and Max to each of the asset classifications. We could do so as well as all the way down to the security level. Now once we have the system auto allocate out and we're going to hit that optimize there again, we're going to go right back into our comparison tool just so that way you can see those side by side comparison anytime you make any type of change within a model. And so now we're going to see model today versus model with those changes and are those the correct changes or not. And then lastly is going to be our blend models function where it's being able to go in and select what are we actually replacing within here. And so if we know we are only going to be replacing it just a few or most of our securities, we can check that box and now we'll just uncheck which ones do we actually want to keep within here. Once we've done that, it's going to pull up a list of any malls that you have out there, any estimates that you have out there and be able to go in and select which route you want to go here. So if we want to go 100% allocation into just another model, we could do so or we can start going in and creating different blends as well between these two models and combine that with what you're wanting to keep from the model as it is today to create. That new model portfolio for your comparisons at that point in time, once we've gone in and we've made the changes and we feel that those are the correct changes and we've gone through our comparisons, that's where we can take those and put those into our trading platform to start rebalancing. Now some of the other pieces that we have out there are going to be in regards to stress testing on your models. So and so this just provides you even more insight. Into where is this model at today and are there certain things happening within the economy or major headlines out there that we're seeing that we feel this model should be really helping us against. And so with that in our stress testing, we can open up our model, see all the underlying holdings within there. We can also open up all of our levers and with those levers you do have the ability to do free hand stress testing. Being able to see how could this mall react if the SP were to go up 10% as of right now or down 10% as of right now or maybe you know there's a lot of oil in this model and be able to see how oil going up and down would reflect in regards to those possible changes within the environments here. And then lastly is our actual scenarios or our scenarios, we are building these out each month. It's based off major headlines. And what's happening within the economy. And so now you can go in and see how could this model react to these different scenarios where if we want to focus on artificial intelligence as one of our newer scenarios, you can see we had three different scenarios actually built into here. And what does this model look like? If for artificial intelligence, we're seeing on the ugly side and they get a 15.7%, how can that affect this particular model? And what do those levers look like and what securities are truly being impacted? If you feel that when you're looking at the scenario though, and it's having a major impact on your model and you want to possibly make some changes to help with this scenario, we do have what we call the hedging wizard. The hedging wizard will provide you with those same stats on the screen to be able to see what securities are being hit the hardest by the scenario. Be able to go in and pick and choose from those actual securities at that point in time to where now we can hedge against those. And we have a hedgy wizard where it's really coming in selecting what security types are we looking at. So we're going to do ETF's and mutual funds from there. We can look at by country or region, by sector or by industry. We can also add in some different search criteria. Now we can have the system show us what are hedgy options at that point in time. Once we've gone through that, we can start setting up our allocations to those and then finalize and review. So just like we did for the models in regards to inline editing, risk optimization or even in our blending of models, it's going to provide us with some of the same insight, but from a stress testing standpoint here. So now we can open this up, see those securities and be able to see, all right, what did our hedging options actually do here for us. So you can see this one's really helping us out at this point in time. But with that and our model management within risk intelligence, all of this is available for you to be able to use when you're using the risk intelligence platform. It really does play a factor in regards to how are you going out there and helping your clients the best you can when you're going out and creating and recommending those different models to them. All right. So with that, once we've gone through and we've made those updates to our models and done our reviews, the other piece I want to hit on here is just integration with Eclipse. So if you're not wanting to always go into risk intelligence to do model reviews, that's where the Eclipse platform, you can pull up any model that you see out there today. And currently this is really going to be the screen that you're looking at where you're going to be able to see what is the model, what's that model made out of. With risk intelligence you would also have what is the risk profile of that model to be able to do high level reviews. And so that way you can also see you know are there changes that we need to make out there to this model to be able to go into risk intelligence and make those changes. And so within here we will still have that downside and upside. We're going to have our correlation risk as well within here as you can see with this particular model we are we are definitely moving more towards that not diversified. Within here that maybe we do want to look at some of those changes as well as some of the style box reports. And then the last piece is going to be just in regards to our stress testing and how does stress testing work at that high level of being able to go in and pick and choose. Maybe it's just our baseline scenarios where we're not going to have those levers out there, but we'll allow you to see over a one year time frame if these scenarios were to happen. What are the effects on this particular model at that point in time? Again, just a nice place for you to be able to do high level reviews as you are reviewing your models inside of Eclipse and looking to make those possible changes out there. And so with that I do want to jump into how does all this work within the Orion fiduciary flywheel and where does risk intelligence really come into play? All right. So when we're looking at Orion risk intelligence inside the Orion fiduciary fly wheel that we have out there, there's really 4 components too, and that's prospect plan and best achieve from the prospect standpoint. That's where we have our prospecting tools out there for you to be able to bring a prospect into the system, add their holdings, get a risk or create a recommendation and hopefully move them forward as a client. After that, we have our plan. From the plan standpoint, really what we've talked about here today, it is really putting that plan together of where are you looking to get this prospect to, but also how are we planning for those different scenarios that they are truly focused on day-to-day invest. That is definitely the model piece of being able to go out there, maintain your models in one spot, do the hypothetical testing on those models before actually going out and rebalancing those. And if all those tests play out how you're expecting them to or close to how you are looking at them and then from there implementing that into the Eclipse platform and going through and doing the rebalance process within each of your accounts with that, that is the model management using risk intelligence. And where our platform can really help your investment team out in regards to reviewing and maintain those different models that you are using with each of your clients today. For those that would like to learn more, please reach out using the QR code here in regards to getting a demo schedule with myself and my team and we'd be more than happy to dive into the weeds a little bit more with you. _1714114492241