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Stewart: Welcome to another edition of the InsuranceAUM.com podcast. My name's Stewart Foley, I'll be your host. We have a very special situation today for our podcast. We are joined by Erik Troutman and Dave Adams, and we're going to talk about technology implementation into a life company and how that goes. But I want to give you the setup first. We're about an hour ahead of the start of our annual symposium. We've never done a podcast where we're all in the same room together. So today, we find ourselves sitting around a big board table at the University of Chicago's Gleacher Center, and we're actually able to look at each other and say hello. So when I welcome Dave Adams, who's the Chief Investment Officer at Independent Life. Dave, welcome.
Dave Adams: Thank you. Thanks for having me.
Stewart: We're thrilled to have you. And I'm actually looking right at him, which is different than usual. Usual, our guests are on the screen. And to my left is Erik Troutman, co-head of the Institutional Advisory Group at Loomis Sayles. Erik, you are a repeat guest. You get massive downloads. We're thrilled to have you. Welcome, man.
Erik: Thanks for having me back.
Stewart: It's great to see you. And so the topic of the day here is essentially, Dave, when you came to Independent Life, you were looking at a complex set of liabilities and lacking some of the technology that you thought you needed to have for it. And Loomis has been instrumental in helping you put that together. And this is absolutely in Erik's wheelhouse, but can you kick us off by just talking about what you walked into when you joined Independent Life?
Dave Adams: Certainly, and thanks for having me, Stew. So to start with, Independent Life is a monoline structured settlement annuity carrier. We were founded in 2018 to strictly write annuities for injury victims, court settlements, stuff like that. So, when I came into the business, we had grown from $0 on the balance sheet, limited resources. You don't have a lot of scale purchasing power at that point in time, to a balance sheet that was roughly $800 million. And so we were really at this inflection point where our growth was taking off from a volume standpoint and looking forward into the future, the portfolio was going to grow and we needed to make sure that we had the infrastructure, the tools, the framework to really manage that growth and service those assets and ultimately, our annuitants as well.
Stewart: Can you talk about where you came into play?
Erik: So, Loomis has a plethora of technology laying around in different forms. And what Independent Life had was, like many insurers, they have a cobbled-together system of things that don't necessarily all talk to each other. All the data's not in the same spot. And what we have at Loomis is being an asset manager is we do have everything, at least on our books, in the same spot. And what we have also is technology that, unlike other places potentially, is that we have it so that we can actually turn it around and other parties can actually use it and have their own ecosystem set up where they're using our technology, but for their own assets and assets beyond what we're actually managing, or not managing at all.
Stewart: That's super helpful and I think a lot of people may be listening who don't understand how it sounds really simple to go just, "Well, what do you mean you can't look at all your assets at the same time? And what do you mean you can't measure your liabilities against it?" But talk about the realities and you've got a background, you came out of the consulting world, you were with NEPC, so can you talk a little bit about how you were thinking about things when you first walked through the door?
Dave Adams: Yeah. So the benefit of coming from a consulting background is you get to see this incredible cross-section of all different types of carriers and product lines. The learning there is that one size... Everybody knows this, right? One size fits one size in insurance. What's unique to independent and structured settlements more broadly is that there are some idiosyncrasies around lapse and surrender risk. And what that drives from an investment side is more of a buy and hold weighted average life, Macaulay-type duration view of ALM. If you looked and canvased the universe for risk systems, for portfolio management systems, all of those systems are either really good through mark-to-market, macroeconomic, economic factor lenses.
You might have a really good investment system that is decently able to catch book accounting, book income, stuff like that. But to really marry economic risk in the lens of buy and hold that we were really looking for, that's really hard to take something off the shelf, open up the box, and build it to the way you want it to be. So really being familiar with Loomis and having a great partnership with these guys dating back to the consulting days, I was just aware of some of the more creative ways that Erik, specifically, had thought about measuring book performance, thinking about buy and hold, stuff like that. And that's really where the conversation started.
Stewart: I think he's really smart too, and I want to get to him in a second, but I want you to unpack. So this is part of the deal with these podcasts is you kind of signed up for a professor for a day.
Dave Adams: Yeah.
Stewart: So you talked about labs. And just for somebody who doesn't know the annuity side of the business, let's say that they're P&C carriers or they're just new in their career, can you talk a little bit about what the risk is there?
Dave Adams: Yeah, so it's actually the absence of risk on the structured settlement side. So in the retail annuity marketplace, somebody that is purchasing an annuity has the option at different points, to take their money out to get their principal back, et cetera. On the structured settlement side, it's actually an assignment company that owns the paper and then the cash flows are owned by the beneficiary. And so what means is that I don't necessarily care about the discounted market value of a liability today because I know that paper is going to be there on the balance sheet in perpetuity or throughout the life of the contract.
Stewart: And you mentioned... This is going to get super geeky very quickly, but-
Dave Adams: Oh, no.
Stewart: So you mentioned Macaulay duration versus option adjusted duration, OAD, which is how a lot of people think about it. Can you talk a little bit about why Macaulay duration in particular was where you were focused?
Dave Adams: Yeah. And so we actually think about ALM through the weighted average life perspective more specifically, and it's really a function of the fact that it's a very simple float business. Our job is to earn a few basis points over what we are paying out our beneficiaries. And so the threat to our business is reinvestment risk. If you think about option adjusted duration, it's really not isolating when you're going to see that principal come back and when you might have to reinvest it. I think today's market environment is a great example of why that really matters, right? We're looking out and everybody's got their opinion, who knows what the Fed's going to say in a couple of hours here, but it's a question of if the credit risk isn't well-priced over the length of a piece of paper that we're trying to buy, do we want to take that reinvestment risk? And in a world where rates are high and we expect them to go lower, knowing precisely the quantum of that risk is critical to making sure that we're not eroding profitability over time.
Stewart: Maybe I should be asking Erik this. Are you using key rates or how are you looking at that duration? You're not just looking at one number, you're looking at where it is on the curve as well, yeah?
Erik: Yes. So as Dave pointed out, the duration metrics are made for a fair valuing of liabilities and assets, and in his case and in their case with their liabilities, which are, yes, they go up and down with interest rates, everything does, but they don't have lapse risk, they don't have all these risks. They have a very deterministic set of flows. So if I want to look at it in a book space where it's basically I put the money on the table and it pays out, my main risk is as long as the money comes in when it's due, that's great. If it comes in sometime off that, then I'm subject to a reinvestment risk. Either I have to sell it early or reinvest it when it matures before I need to pay it out. So Macaulay duration, all of that, those, you can measure it with the various duration metrics, but basically weighted average life or other metrics are just as easily used in this space.
Stewart: And I want to make sure that our audience knows what structured settlements are. So I almost started to define it myself, but I'm just a little afraid. So can you give it a whirl?
Dave Adams: Yeah, absolutely. And so yeah, structured settlements. I used the example of an injury victim in a court case. So typically what would happen is there is a business or an operation that injures a victim. Typically what'll happen is the P&C carrier that ensures the business will step in, this is loss in L&E, right? And they'll go to court and they'll debate what the value of that injury is. Oftentimes, the two parties will mutually agree to settle the case or through litigation, a judge might say, this is probably appropriate to structure out.
And the reason being is there's a whole host of reasons. It could be faculties after the injury, it could be the age of the victim, et cetera. And the benefit to the injury victim is the tax benefit. So when you put something into a structured settlement, the cash flow comes through tax-free. So that's one economic benefit. The second is the certainty. There's a lot of control around it. It helps to protect certain individuals from predatory behavior out there in the investment space more broadly. And so that's why the policies are typically owned by the assignment company, not the individual, so that nobody can go out and try to chase that lump sum and take it away from the insurance company.
Stewart: That's super helpful. So Erik, when you and Dave first started talking, what was the starting point? Where did you begin?
Erik: With the assets. So, in talking with Dave, and so essentially again, he had assets, various investments, a lot of fixed income, but not necessarily all of them coming into one database or one table, one view of the world. Some are coming say from Clearwater, some are coming from spreadsheets, things of that nature, which is not uncommon.
Stewart: Right, absolutely.
Erik: And also, you don't necessarily have a full set of risk metrics or other things that you desire to have. Cash flows, for example, and so on and so forth. What we started to discuss was why don't we get the assets, the full lay of the land on our system? That's part of this journey is getting those pipes hooked up, which sounds really easy, but again, all the devil's in the details of getting that set up. And essentially we now will shortly have a daily feed from Clearwater for the majority of the assets.
The other assets will for the time being, come in on a more manual process, but it will give Dave and his team a 100% clear picture of what they have as far as assets go. And then once you have that, you can make sure that you have the analytics that you want for the various ones, and then you can build out from there. Then you can step back and say, "Okay, I got the asset picture settled. I know where I am on my asset side. Where am I on my liability side?" Now, his liability, the liabilities that they write are very deterministic, as I said, which makes the analysis setting up of those relatively easy. So we've come up with a system to set those liabilities up so that now you can bring the A and the L part together and through the technology, you can see it on the screen.
Stewart: That's super cool. And the way that I've always thought about this is that those liabilities are basically inverse of bonds. They're just an inverse. In some way, it's just a set of cash flows going out. You can calculate a duration, you can calculate key rates, you can do all of those same things, right?
Erik: Exactly. So the one thing is, the technology people that we have working on this. So the technology was built for total return and all of the flexibility that they needed there, that flexibility allowed us to talk with them and say, "Okay, we have what looks like a bond." It's a liability, we can call it whatever we want. This happens to be a liability, but it's a bond or it has cash flows. Can we put that through Bloomberg like it's an asset? And yes, the answer is. So we've set up a whole mechanism to create these bonds, have an assigned pricing methodology, goes out to Bloomberg, brings back analytics. And the way we've chosen to set it up is actually a big large portfolio of zero-coupon bonds, which facilitates other analysis more easily, but it allows you to basically use the same pricing methodology, Bloomberg and so on, and bring that all back into our system. And then, yes, instead of it being in your asset portfolio, it's in something of a liability portfolio and essentially, you can do, A minus L, and you can view your world in a relative basis.
Stewart: Are you saying that you are looking at each individual cash flow as a zero-coupon bond? That sounds like what you're doing and that sounds like what you would need to be doing.
Erik: Yeah. So what we've discussed is that there's cash flows that run out into the future. Now each liability has its amounts at the future points. The way we said rather than setting up say a new bond for every one of those cash flows, is like, "Okay, we have all these months and we'll just basically put a zero-coupon on all of those months and then that is our portfolio of securities, our universe of securities." And we know we need X, Y, and Z of these various securities, and then we just buy it as if it's a portfolio of bonds.
Stewart: Yeah, that makes sense.
Dave Adams: If I may, I think the significance there, and I think Erik's being really humble. You asked earlier about key rates and getting a little more prescriptive within the liability. A lot of risk systems would say, "Hey, just give us the cash flows and we'll create a short bond position individual." If you think about my comment earlier about weighted average life, if you created a single short bond to replicate or proxy your liability, you would get a single weighted average life, which limits the granularity when you think about assets and liabilities in conjunction. And so the real value and the way that it's indicative of how Loomis is able to partner with people is that my situation is unique to me, not every one of your listeners is going to need this specific challenge solved, is the ability to take the infrastructure that the technology team has in place and port or move that system to where the insurance company is and create those zeros so that we could look at things more on a bucketed basis as opposed to an individual aggregated number.
Stewart: It's interesting. I remember distinctly at the University of Missouri getting my undergraduate degree, professor John Stowe in money and banking, said, "Banks and insurance companies manage their assets versus their liabilities." And I dutifully wrote that down. And 35 years later, you hear how challenging that seemingly simple task is. There is real-deal technology. And so one of the questions I guess I have, Dave, with where you are is: you're the CIO. What was your ask of the actuarial folks to get you those cash flows from your projected liabilities? Were you getting everybody bought into the way that you're going about doing this?
Dave Adams: Yeah, absolutely. As a newer company, I think that our entire group is very innovative and willing to consider new ideas. And so it was really just a function of making sure that we were able to port and manipulate the data that we have for the technology folks to capture. I think that there was no sensitivity to that or reluctance to do that because everybody appreciated that single source of information not only can help to surveil risk, but also inform decisions when we're looking at new monies coming on, what's the aggregated risk of the portfolio today? Maybe we want to offset some of that with the new monies. Maybe we want to take some of that reinvestment risk. And so having that, I'm going to use the term spatial awareness across the entire enterprise was super exciting to a lot of people, not just me.
Stewart: So I have heard this term ‘buy box’ and I'd love to know, what is a ‘buy box’ and how are you using it?
Dave Adams: Yeah, I don't know if it's an industry term or if it's just the vocabulary that I use, but if you think about any institutional portfolio, you've got compliance for an insurance company, regulated entity, there's your DOI regulations, if there's any counterparty agreements, reinsurance, et cetera. There might be some guidelines there as well. And so for our organization, the assets that are available to purchase start with the total investable universe. It gets narrowed through our IPS, narrowed through DOI, narrowed through some other things as well, and it leaves fewer options. With those few options, not each one of our annuities is going to look the same as the last. And so we have to balance those available options with the specific term length of the annuity, how much we're pledging to pay that beneficiary, et cetera. And so internally, I use the term ‘buy box’ to describe that filtered waterfall of securities.
And so what was really powerful with the tools that Loomis has built is bringing in that liability awareness as well, such that we can look at the general yield that we need to hit over what period of time, look at what's in the portfolio, where we have room to add through all that compliance, and then think about some of that reinvestment risk that's aggregated at the book level as well. So the buy box is a theoretical concept in my mind and it's cheeky vocabulary right, but what it's turned into is a series of visualizations and dashboards that can be pulled up on a daily basis and tell me exactly what this 30,000 foot view is, but with all that more specific granularity around any specific asset class.
Stewart: That's super helpful. You've been busy, Erik. You guys have been busy.
Erik: The tech people have been very busy.
Stewart: Yeah. Every time I'm on a podcast, I learn something new that I go, "Wow, I didn't know that was even possible, really." So one of your earlier podcasts that essentially broke the internet was about benchmark snapping, and the concept is a very interesting one because it addresses some of the challenges that insurance companies have with regard to measuring performance. Given all of the things that Dave just talked about with regard to the IPS, investment policy statement, the DOI, the Department of Insurance, the regulatory, the compliance, the liability set and so forth. Can you talk a little bit about benchmark snapping and how you're working with other insurers and how it's evolved?
Erik: So benchmark snapping is an idea that we try to give the insurer the ability to see what they can buy. So it is essentially the buy box in the sense that they will have model portfolios or model allocations that have passed the various hurdles that need to be passed for various products or annuities at the time. And the benchmark snap will come up with the selection universe and then parse it out into various buckets so that you can slot it into your matrix, think of it as a matrix, and depending on the product or the annuity, the length and the duration and all of that, it can tell you what you think you would get. Now the idea is to use a selection universe that's actually buyable because a lot of the universe is out there. If you use indexes, that is an okay step, but a lot of the paper that's in those indexes is not buyable.
Stewart: You can't own it.
Erik: You can't, it's on an insurance shelf somewhere.
Stewart: Right.
Erik: So the 20-year issued 10 years ago is in the 10-year universe, but I can't buy it because somebody else did a long time ago. So we use a lot of filters and trace data and other metrics to filter down universes so that they are tradable and then share, basically pass through that information so that the insurer can then say, "I'm fairly confident with what I think I can get."
Stewart: It's interesting because one of the tenants of a benchmark is that you have to be able to buy it, and you made this point in our last podcast where any given index, all of those components are not buyable. And so if I understand benchmark snapping correctly is that on a given day at the start of an assignment, you're taking a snapshot, which is where the term snapping comes from. It is a snapshot of the investable universe that particular insurance company has at its disposal given all of the things that got filtered out along the way. And that is the opportunity set, if you will, available at the start of that relationship. Is that a fair?
Erik: That is a fair assessment.
Stewart: Okay.
Erik: So essentially it builds a universe that a portfolio manager could buy with the money that you give it.
Stewart: And then you're going to compare what was actually bought to what was available to buy?
Erik: And this gets to the feedback mechanism. Once I know what I could buy, and we did actually for our initial benchmark snapping client that we've worked with, it took a year of going back and forth with their actual portfolio managers to get them comfortable with what we were sending over. There was some pushback. So we went through that and we refined our process with that particular client. But it's designed to say, "Okay, you could have bought all of this, you, portfolio manager bought this." And you can then judge against that.
Likewise, actually, it also gives a feedback mechanism for the allocator themselves. So the allocator is faced with a menu of places they can put money and if they see an opportunity in a particular area, they can over-allocate versus say, the model portfolio. In Dave's case, he could take reinvestment rate risk and choose to put that risk into the portfolio. And with the snaps being as granular as they are, you can actually track that bet as well. So at the end of a quarter or something, you can come back and say, "Okay, my manager's beat and my allocation helped," or vice versa, "Portfolio manager is underperforming and I should have done this and I didn't do that." It gives you a feedback mechanism both at the tactical, the strategic tactical asset allocation level and at the portfolio management level actually.
Stewart: Yeah, it's really a cool approach. And again, a very heavy technology lift, right?
Erik: Yeah.
Stewart: Significant.
Erik: Yes. I will say that's the one thing that we've automated a lot of this. The building of the universes and the sending of data has been automated in the back, but it's not something that is just on the tech side. Also, we have the same process in our own internal construction models. So when we have a buy and maintain or a cash flow matching or other insurance portfolio that comes in, we will use the same modeling technique, actually. And this goes into building a selection universe in the model construction and build a tradable portfolio that we can then discuss with the client as well and actually trade.
Stewart: That's super cool. So Erik, I think one of the things, and Dave alluded to it, given your background, you know this well. You've seen one insurance company, you've seen one insurance company. Even those that look similar on paper, when you really dig into it. I have yet to meet anybody who doesn't say “We have a conservative investment philosophy.” What that means is anybody's guess. So how do you work with insurance companies that can be quite different one to the next?
Erik: Loomis has this platform called In2. That's the thing that we're sharing.
Stewart: What's it called?
Erik: In2.
Stewart: In2?
Erik: Yeah, I-N-2, In2. So that is the platform that we have at the firm. The platform was built over time evolved from, or actually they did away with what was a very monolithic system that had one-size-fits-all, and they wanted a mass customizable solution for portfolio management, risk performance, attribution, accounting. And they built into facilitate that for our internal alpha engines and each one is very unique in how they view the world. Every insurance company is also unique in how they view the assets, how they want the risks partitioned, how they want the assets partitioned, their overall structures are also onshore, offshore, this entity, that entity. They're all very, very different. And what the In2 platform gives us is an ability to, because we've been flexing the system already for every one of our alpha engines, it's adaptable to any... Essentially, it's like a fluid that can fill any form.
So you bring in your view of the world and we will sit with you and sort. Now, we may have some off the shelf stuff that fits the bill, but the beauty of the system is that we can turn around those reports and the reports can also then be you yourselves can go in and tweak them to view. The other thing I will say is that the nice thing is that the data that you... So if you think about it from an end user that doesn't really want to touch the system and just wants reports, and then there's a power user that uses lots of panels, and then there's the data hounds that like to go into the data and pull everything up and do their own stuff. And the data on our platform is consistent across all of that. So if you pull up a number in one area, you will see exactly the same thing in all of it. And so basically we can span the space of users.
Now, initially, we're focused on power users because we don't have a menu yet of reports. That's one of the things in the future, we would like to have a menu of reports that are pre-canned that you can turn out. But again, that comes with time. The panels are very easy to put up. And with the back and forth, the weekly meetings that we have with Dave and his team, we can actually tweak and reconstitute them, and actually now they are quite able to tweak and reconstitute them. And then we haven't gotten to the power users yet with them, but that's on the table where they can actually pull up the data themselves and build whatever it is they want. And so you can have MATLAB, Python, anything, pulling the data and doing whatever models you so choose.
Stewart: That's super cool. So I've got a quick question for you, which is, and I've got a couple more because I forgot to do our normal intro with you, which is just sad. It reflects the fact that I was super excited about this podcast and where we are. So where is Independent Life today and how are you using these systems on a go-forward basis?
Dave Adams: Yeah. So I think where Independent is today is we're deriving massive utility from the hard work and the collaboration that Loomis and the In2 system have brought to our organization. I think what really gets me excited is what Erik was just talking about, is the universe of creative lenses and models and applications that they've created. We're getting to this point where the collaboration is really powerful. So we might come to Loomis and say, "Hey, we're bumping into this problem, or there's this new workflow that we're thinking about, this is how we're thinking about building it out from the get-go." And just through diversity of thought and collaboration, the group might just come and say, "Well, we've actually done something similar for another insurer before. Why don't we look at this and see if we can use the bones and then build it up in the way you want it to be?"
And so if you think about static reporting or visibility on risk within the assets, then you layer in liabilities and then the next step in that is more granular, enriched information on both of those things. We're just now getting to the point where we can weaponize that and leverage that to look more broadly at the competitive marketplace, thinking about new emerging opportunities, different ways to measure and evaluate opportunities. And so it's really the collaboration just as much as it is the system. And we're just starting to find those use cases and examples today.
Stewart: That's super helpful. So I've gotten a tremendous education from the both of you on everything that's going on here and it's fascinating. The one thing I forgot to do is to ask you our icebreaker questions, which I'm going to ask you now.
Dave Adams: I thought I dodged them.
Stewart: I know. You're not. No, you're not. So Dave, where did you grow up and what was your first job? Not the fancy one.
Dave Adams: So I grew up in a very small town outside of Pittsburgh, Pennsylvania, Ligonier, and my first job was roofing construction.
Stewart: That's serious business.
Dave Adams: Yeah. I like this job a lot better. More air conditioning.
Stewart: That's awesome. Well done. So here's the fun one, out the door. I'll give you a chance to answer this because Erik's already answered it and I want you guys to collaborate on one. So we're at the symposium, we've got some folks who are a little earlier in their career, perhaps. What's a piece of advice that you would give a 25-year-old David Adams in the insurance asset management business today? What would you want them to know that you to benefit from your years of experience?
Dave Adams: Gosh, that's a hard one. I think that insurance asset management is incredibly varied, and I think that I got really lucky along the way, being mentored by really smart people, but also listening to and absorbing really smart and diverse ideas. And so what I would say is just soak up every conversation and every viewpoint, think about it, but don't be scared to question it because I think that exercising that muscle and thinking critically about all of the smart ideas, we're going to hear a lot of smart ideas today, right?
Stewart: Absolutely.
Dave Adams: Just really thinking about them from a critical lens and developing your own opinions of them, right or wrong, if you're a young person, I think has really helped me out along the way just because you get a better grasp of things.
Stewart: That's great. And so here's the fun one for both of you. So we're going to have a lunch. It's a table of five, you each get one and you got to agree on one. Anybody you want alive or dead. Who's yours or who's yours?
Erik: Oh, we get to fill out the table?
Stewart: You get to fill out the table.
Erik: Oh.
Stewart: Who would you invite to lunch alive or dead?
Erik: Probably Bill Gates.
Stewart: Bill Gates.
Erik: No, sorry, sorry. Steve Jobs. Sorry.
Stewart: Steve Jobs?
Erik: Steve Jobs.
Stewart: There we go. All right. You've got Steve Jobs. Dave, how about you?
Dave Adams: Gosh, that that's a tough one. Warren Buffett. We'll round it out, all the bright minds.
Stewart: All right, Steve Jobs and Warren Buffet. And then who's the one who you would agree on? You're not in the same sports teams, not given where you're from. That much we know.
Dave Adams: Yeah, yeah. That's true. That's true.
Erik: I don't know. I go science routes, so I would do like a Stephen Hawking type.
Dave Adams: And I like to learn, so I can agree on that one too.
Stewart: There you go. Wow, that's a great table. Steve Jobs, Warren Buffett.
Dave Adams: Heavy hitters.
Stewart: Absolutely. And the two of you heavy hitters. So thanks for joining me today. I appreciate it very much. We've been joined today by Dave Adams, who's the chief investment officer at Independent Life and Erik Troutman, co-head of the Institutional Advisory Group at Loomis Sayles. Gentlemen, thanks for being on.
Dave Adams: Thank you.
Erik: Thank you.
Stewart: Thanks for listening. If you have ideas for a podcast, please shoot me a note. It's Stewart@InsuranceAUM.com. Please rate us, like us, and review us on Apple Podcasts, Spotify, Google Play, or wherever you listen to your favorite shows. My name's Stewart Foley and this is the InsuranceAUM.com podcast. We'll see you next time.
This podcast was recorded on 12 June 2024.
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