Ep. 231: Transforming Complexity into Clarity: Financial Planning Data Insights with Mark Evans

Come on in and sit back and relax. You’re listening to Episode 231 of the WealthTech Today podcast. I’m your host, Craig Iskowitz, founder of Ezra Group Consulting. This podcast features interviews, news and analysis on the trends and best practices, all about wealth management technology.
 
My guest for this episode is Mark Evans, founder and CEO of Conquest Financial Planning. Conquest is not Mark’s first software startup rodeo prior to founding Conquest 2018 He was a co founder of financial planning vendor Naviplan back in 1995. Naviplan eventually became one of the top three most popular Financial Planning applications in our industry, focusing on higher net worth, ultra high net worth, estate planning other very complicated capabilities. So Mark knows a lot about building out very complicated financial planning tools. We spoke about some interesting topics one was jurisdictional independence, meaning operating in multiple countries which Conquest does. We talked about their strategic advice manager tool (SAM), which is an interesting product. You’re going to hear all about that and their initiatives around generative AI.

But before we get started, let’s talk about tech stacks. At Ezra Group, we’ve seen tech stacks of hundreds of RIAs and let me tell you, most of them are loaded down with tech debt. So you shouldn’t feel too bad about yours. But let’s face it tech debt is like a giant anchor, holding back your business growth. If you want to free your firm for exponential growth, you should run, not walk to our website EzraGroup.com and fill out the Contact Us form. Our experienced team can evaluate your current tech ecosystem, deliver targeted recommendations, optimize your existing systems and operations or run an RFP and help you implement new software to take your firm to the next level. You can take advantage of our free consultation offer by going to EzraGroup.com.

Topics Mentioned

  • Learning From Experience
  • One Engine for All Client Segments
  • Transforming Data Into Insights
  • The Future of Financial Planning

Episode Transcript

Craig: All right, next up, I’m excited to introduce my guest is Mark Evans, CEO of Conquest Planning. Hey Mark, welcome.

Mark: Great. Thanks for having me.

Craig: Man. It’s great that you can be here. I know you have a super busy schedule.So happy to have you here to talk all things financial planning technology. Where are you calling in from?

Mark: I’m calling from a barrier island called Anna Maria Island in Florida. Just outside of Tampa Bay in north of Sarasota.

Craig: Oh, that sounds nice. I’m in New Jersey looking outside, just west of the Turnpike, and looking outside of this rainy day.

Mark: I’m looking outside a nine hole golf course.

Craig: Way better. Alright, so let’s kick things off. Can you please give our listeners a 30-second elevator pitch for Conquest Planning?

Mark: Sure. Conquest Planning is our approach to revolutionizing financial planning and advice software. We’ve taken approach one engine across all consumer segments, designed to help the advisor select the best strategies. So we have a built in strategic advice manager, intelligent assistant, and it’s designed to provide holistic analysis across all goals, retirement accumulation, decumulation, estate planning, life insurance, disability analysis, long term care, and so forth all of those integrated into one platform with an easy to use user experience and detail analysis.

Craig: That was a good 30 seconds. I appreciate that. So one of the challenges you’ve had is you started in Canada, very successful there, a lot of big clients, but then trying to break into the US market with a Canadian based product. Can you talk a bit about the jurisdiction independence you built in your engine and how that works?

Mark: Sure. So as you are probably aware, I was the founder of the Naviplan tool.

Craig: I’m slightly aware that yeah, that does ring a bell.

Learning From Experience

Mark: We developed the Naviplan tool back in the 90s and when we did that, we built it in the Canadian system first. So we launched in Canada in 95, built that through, in the early 2000s we brought it to the US. But when we did that we ended up with two different applications. We had an application for Canada, an application with a US which shared some code base. We redeveloped Conquest starting in 201, one of our goals was to have one platform, one engine and plug in the different jurisdictional nuances for Canada for the US the different retirement vehicles for those jurisdictions. We’ve got a UK version in production, a Canadian per version of production. And now we’re launching the US version and we’re continuing to extend that.

Mark: So we want one end of this so that when we add agnostic or generic functionality, all of the jurisdictions automatically inherit that and that was a key aspect for us. We’ve also used an agile development approach now. So we launched in production in October 2020 In Canada, and we’ve done monthly releases every month since so we’re coming up on three and a half years of monthly production releases that it’s not just bug fixes and little nuances, but major new functionality every month in all new jurisdiction.

Craig: Time flies, man, it’s already three plus years since you launched in Canada.

Mark: We started the company in the fall of 2018. We are in production in Canada two years later in the fall of 2020. Production in the UK in early 2022. And now in early 2024 we’ve launched in the US market.

Craig: So incredible, that’s the benefit of a startup. You don’t have all the legacy, that’s one thing we talked about a lot is when you’re very successful, Naviplan was very successful. The more successful you are the more legacy clients and legacy code you’re building up.

Mark: And the other aspect is we’ve built our second time doing it so we’ve learned from our wins and our mistakes the first time around. One of the key things was it is for the long run you are going to be doing this over a number of years, you have to build the right foundation so that you can continue to build on top of that. When we build Naviplan we kind of did it blindly. We didn’t know what was going to be asked for it next somebody asked Okay, yeah, dysfunction. Sure we can do that and if you build something that over time, the foundation is pretty shaky. And this time around, we put the hooks in and the plows in so to speak to build this knowing that we’re going to eventually have to add additional functionality and allowed us to continue to do that without rocking the foundation to a point where it became brittle and would break.

Craig: You mentioned decumulation that caught my ear. Can you talk a bit about how that works because there are some companies that just do that. That’s all they do is deliver a decumulation, we call that we look at that as somewhat of a portfolio rebalancer is yours a rebalancer and portfolios, or is it some other type of decumulation calculator?

Mark: It’s designed to build into the plan to allow you to say okay, you’re going to build wealth up to a certain point in time, and then you’re going to draw down from that wealth. And the key is there is to look at, obviously from a tax planning perspective, what’s the most tax effective way to draw that money out in order to balance your taxation over your lifetime to look at different aspects that could be impacted from that. So our engine does all of those all that analysis and that SAM intelligent assistant I spoke of looks at different strategies for the advisor instead of having the advisor have the trial and error different approaches.

Mark: We do it all in the background for you and show you which is best for that particular client because it’s very client centric in terms of what client holdings do they have, do they have Roth IRAs, 401k’s what kind of non qualified plan and so forth, and what amounts and in over their lifetime of their retirement, how should they maximize that in terms of making their funds last as long as possible, but then that also depending on the client bottles into estate planning where do they want to leave wealth and from an estate planning perspective and so forth.

Craig: So is that more similar to how a portfolio rebalancer would work but just in reverse, or is it some other type of tool?

Mark: It’s not the portfolio rebalance, it’s more looking at from a strategic perspective at a holistic level on the accounts that you have and saying, okay, the asset allocation is a separate function that flows into that, but we want to look and say we need to draw it down. There’s obviously minimum distributions that need to be taken out a certain age points. But there’s points for example, if you’re going to delay your Social Security, so you get more paid out, but you want to retire previous to that start date, you got to pull money out to fund that gap, until you start getting your Social Security.

Mark: And then once you get Social Security, what money should you be taking out at that point in time and then the taxation levels and the different tax brackets and so forth. So it can be a very complicated calculation, and it changes if you start doing things during the accumulation phase for a client that could change the distribution of the assets and the different types of account balances. Okay, now, how does that affect how you’re going to withdraw? So we’ve integrated all that together.

Craig: That’s impressive. That’s a that’s a lot of work, having helped some firms do that. There’s a lot going on in the back end of that. Can we talk a bit another thing you mentioned was life insurance. So that’s a big issue for a lot of our clients and trying to integrate that into the planning process. How what approach did you take to doing that?

Mark: We’ve got a simple approach where you can just ballpark and say, Well, okay, if someone was to pass away, what would the shortfall be? But we also have an integrate right into the plan. Where you we can simulate someone passing at a certain point in time, it could be today, 5 years from now 10 years from now, and then we showcase what happens from a cash flow perspective. In terms of okay, we’ve lost their income sources if they were working. Do we want expenses to go down a bit because there’s only one person left in the family or to go on expenses to go up a bit because now you need childcare? Because that person who passed was the parent looking after the kids.

Mark: There’s all these different functions that levers that you can pull and you can simulate that so it becomes like a way of integrated into the plan and we showcase Okay, here’s what the impact is, and then we can calculate, well, here’s the kind of insurance coverage you would need to fill that shortfall in that gap. And then once you put that in into the plan, the premiums and so forth become now expenses into the plan. And then so that’s that’s from a typical looking for well, the risk of somebody passing in a shortfall but you can also look at it from a strategic wealth building perspective, okay, I want to buy a universal life policy, so that I will have wealth transfer. That’s it that’s insurance pays.

Mark: Well, normally the premiums of those are going to be much higher than term insurance and so forth. So now you want to see whether or not you can afford those premiums to buy that policy that has to be injected into the plan. It becomes it might even span into the retirement period. And you want to be able to show the client that they can support these, what appears on paper to be relatively large premiums, but in the end, that’s going to fund your investment on the insurance policy.

Craig: That’s complicated. We have all those capabilities. And can the advisor also buy the life insurance or life insurance or other insurance products through the platform?

Mark: No, we don’t do any of the actual fulfillment. But what we’ve done is we’ve converted the plan into a series of to do so all the strategies translate into dues actions, whether it’s set up a new account, like for example, if you didn’t have a Roth IRA, set up a new Roth IRA and start making this red regular contribution to it. So then we push those actions and we integrate those actions into the ecosystem of the organizations we deal with. So that they can be pushed out as fulfillments that ideally can be executed electronically, and away we go. And then, for example, life insurance, I didn’t say well, we need a policy of this size for this individual push that out to a life insurance tool that can now go through the process of validating the exact cost of that particular follows.

Craig: Do those action items go out to the CRM?

Mark: They can in the implementation they’re often pushed back to the CRM because that’s the system of record and that’s where the actions can be tracked. And then they get integrated into other actions you may have associated with particular clients. So that’s typically the approach that happens. There are some cases where they get pushed out into electronic fulfillment components and then pushed back into the CRM as well.

Craig: Interesting. You mentioned expense gaps, do you also support annuities?

Mark: Yes, we support annuities and showcase and that’s part of our stochastic analysis. Does that shows the benefits of annuities right obviously if you have a portfolio that is very aggressive and you showcase the stochastic impact of changing return rates based on risk and so forth over time, that’s going to be much more sensitive if you start layering in fixed income products that have guarantees to them, now all of a sudden, you’re insulating the client and you can match that up particularly if you can match that up to their non discretionary expenses.

Mark: So if I can cover your non discretionary or mandatory expenses with guaranteed income sources, and then I have your non discretionary expenses, generated or supported by your discretionary assets that allow flexibility and are more volatile, but also you’re now matching up to things that you have the choice of, I’m not going to spend that or like I spend that that particular year. We do all of those that type of analysis as well.

One Engine for All Client Segments

Craig: Stochastic analysis is no joke. You also mentioned building this and using the same calculation engine across all consumer segments. That’s also not common. Why would you do that? And how do you manage because if you’re talking about a higher net worth clients segments, very, very different calculation and requirements and mass affluent.

Mark: First of all, our strategy was, there’s too many people that are not getting access to advice, because the current model where you typically sit down with an advisor, one on one just doesn’t scale, as you get down below a certain level of wealth. It’s just not the kind of fees involved revenue involved with the organization or the advisor. So they’re pushed down to another group, whether that’s another set of advisors that just don’t have the experience with the training, or they’re left to use some calculator tools that are available.

Mark: What we want to do is come up with a solution where we can use technology to make things much more efficient and effective. So we built this engine that’s sophisticated, but we allow the engine to scale down by just shutting off certain strategies that are not applicable to those lower end clients, and allow that to be delivered in a self directed or hybrid advice approach.

Mark: So we have a platform that allows clients to go and access it directly. And then if they need to, they can reach out to hybrid advisors that can give them advice collaboratively, and then once they are recognized or determined that these these clients need more deep than in depth advice, we can move them into the traditional advisor relationship. So that kind of moving across there during their lifetime. And that can happen over a series of years or it can happen quickly. If they inherit wealth, or they sell a business and all of a sudden they’ve got a lot of wealth, they can move from a simple clients situation to a more complex one.

Mark: A key way of doing that is the strategy centric approach that we have. For a high net worth client there’ll be a whole list of strategies that could be applied to them because their situation is more complicated. For a more simplified client that doesn’t have a lot of wealth, doesn’t have a lot of moving parts in their plan, the amount of strategies that are applicable to them are it’s much smaller, and our engine automatically determines the applicability of these strategies and serves them up to the client so that we can keep it simple or go to more in depth depending on the sophistication of the client plan.

Mark: In several situations now where large organizations are having that and we don’t do self directed ourselves? We do it through organization. So we have a self directed capability they can either brand out of our platform or they can use our API’s then construct their own user experience and control that embed that into their existing client affordance layout to expand the advice capabilities that they can build.

Craig: Can you expand on clients accessing your calculation engine directly? Where would they do that? Through the advisors website, through the portal?

Mark: Usually through the organizations that we deal with, they either the platform that out of the box, we provide it or if they if they’re a bigger organization, they’ll tailor it and embed it into their ecosystem. But they access the client portal, either the client portal they already have and we’re exposed within that client portal or if they don’t have a client portal, they can use our out of the box portal and they get access to it and they can do either a single goal or they can do multi goal capability.

Mark: So the director client can have a simplified retirement capability. You’re going to look at debt management, you can look at funding education, and so forth. And that can then migrate to advisors when they discover that, oh, this client has more wealth than we thought they had they’re “worth our investment” to move them to a deeper relationship. And the whole, the whole planning process allows organizations advisors to discover this about clients and to have a better understanding of what that client represents in terms of potential revenues, but also potential deeper relationships.

Craig: You mentioned hybrid advisors, that can mean a couple of things. What do you mean by a hybrid advisor and how do you move them to the traditional advisor relationship?

Mark: Hybrid advisor usually what we do there is when you’re dealing with a self directed set of clients, you want them to have some sort of support. So there’s typically a call centers or a set of advisors, that they don’t have dedicated clients, any of those advisors could work with any of the clients at any given time. And that allows you to have that flexibility that the self directed clients that they run into issues or questions they have or they want some more in depth advice.

Mark: The hybrid advisors can jump in collaborative platform can either be in real time or asynchronously and they can layer in additional strategies, expand on the strategies the client is already playing around with and they can also then say, Oh, I’ve discovered this, this client needs a deeper relationship so they can move them through the platform to a dedicated advisor or a higher network advisor that can deal with their more in depth needs.

Mark: And the beauty is the experience for the client is seamless. They see the same platform, all they’re seeing is more in depth strategies being served up to them in that traditional approach in organizations like this, the first self directed experience would be a set of calculators, then it might be oh, I’ve got a retail tool that I deal with. And then I get to oh, now I’m going to a high net worth twice three different tools that the client has the experience might even start from scratch in terms of the planning process each time and then our situation is no we just migrate you across to the next best level of advice for you, and who should deliver that advice. But for the client, it seems like I’m just getting more in depth advice in the same platform, same experience that I’ve been used to from day one when I started with this organization.

Empowering Advisors with AI

Craig: I want to pivot on to something you mentioned the strategic advice manager or SAM and the underlying AI engine that helps advisors choose strategies. Can you explain how that works? And how is it better than the way advisors are choosing strategies now?

Mark: So the way advisors choose strategies right now is they’ll typically be able to simulate or emulate any kind of strategy, whether it’s lanes or security that we talked about earlier, saving more moving money from one type of qualified asset to a non qualified asset, adding insurance, changing your expenses, changing your retirement date, and so forth. So all these different ways that they can modify the plan or consider strategies.

Mark: The problem right now though, is the advisor when they put load all the data in for the client, either electronically or manually. Now they have a starting point. Now they want to look and say, Well, what strategies are best for this client? Well, they have to play around with that. Let’s try what would happen if we save more to their 401k? Okay, we see what the impact is, well, what if we saved some or all of that to a Roth IRA instead? Or what if we save that into a non qualified investment? What if we made them work for a year longer? What if we downsize their house five years after they retire, or 10 years after they retire? They all this takes time for the advisor to try these things out. See what the impact is.

Mark: What SAM does is runs all these strategies in real time in the background and serves up the list of strategies for that client. And what the relative impact is for each strategy, how much it moves the needle on retirement or education goal, or your legacy, what your net estate will be and so forth, and shows them all that you pick the strategy that you want to choose from that list apply it that changes the plan and recalculates all the strategies again and shows you the next best set of strategies. And you can pick that strategy doesn’t have to be the top one on the list. It could be something saying well, I don’t want to pick the top one, because that’s downsizing the house and they don’t want to do that right now. So I’m going to look at well, what if we were to reduce your retirement expenses slightly? What would the impact be and show them those aspects of it? So it’s this real time showing the impact of a series of strategies so you can get guidance as to which strategies are best for the given client you’re working with?

Craig: That seems handy to have.

Mark: We think a bit like a caddy relationship, that SAM is not building the plan like the caddy doesn’t take the shots, the golfer takes the shots but the caddy is there saying, we’ve got wind coming in here, we’ve got a green that undulation is going this way, there’s a sand trap in front. These are things that we should consider. I think you should either choose your six iron or your seven iron on this. And ultimately the golfer is going to make the final decision and take the shot. The caddy is there make sure that, there’s a slope on the back of the green there. If I hit this too far, it’s gonna roll right off the back.

Craig: So caddy, uses his or her extensive experience playing those courses and how that the golfer they work with shoots and how they how they play to decide what club to use and how to play a certain hole. What is the underlying technology behind SAM, what is the AI is machine learning predictive analytics, what are you doing back there?

Mark: We built our own solution on this so we built it. It’s more of a brute force AI to generate the search space of possible solutions and the impact of that. And then what we’ve done the benefit of this is all of these strategies when you apply them, the plans that are in the database for an organization have a series of strategies and we know which strategies were applied for each client. And we know the impact of those strategies. So we can now do analytics across the organization across clients to say, Well, how many clients delayed their social security and what was the average impact of delaying Social Security for clients?

Mark: We can also do things like, oh, which clients haven’t believed their Social Security, inject that strategy into their plans, hypothetically, and show them show us which ones would benefit the most. populate that list though, and fire through a CRM allow the advisors now to know which clients to reach out to saying, Hey, we’ve got a good strategy for you here. Looking at delaying your Social Security, just an example. And we know it’s going to have an impact for them, as opposed to let’s call or our clients and talk to him about delaying Social Security. They come in the office and we go doesn’t work for you, Frank. I got some other stuff for you. So this way you can do the analytics in depth using the engine and provide that kind of insight for advisors and for organizations.

Craig: So is that something the system would remind advisors to do is at the advisor level or the firm level where it says here’s the client –

Mark: Right now we’re doing the firm level, but it will be pushed probably sometime next year down to the advisor level so the advisor will be able to do those analytics themselves.

Craig: It seems more useful at the firm level because then you want to nudge the advisor you’ve got 13 clients that could delay retirement, here’s why they should do it.

Mark: And it also allows organizations to do compliance for us electronically because we can say, Okay, are there strategies out there that have not been provided to clients that should have been provided to clients, right, that kind of analysis is not provided any other tools out there without doing a manual audit of a particular plan, and if it’s good enough for this client

Craig: Does it run automatically to say, hey, there’s these clients every six months or so to say, hey, these clients should be doing so security should call them?

Mark: You can do it either automatically, or you can do it as needed. Like you just say, I’m gonna run this analytics. So we’ve got a whole bi business intelligence interface that allows organizations to run out of the box reporting that we provide, but they have access to the engine for bigger organizations that want to integrate those analytics into their holistic view of their organizations as well. So it’s very flexible capability.

Craig: Do you know what the underlying tech is on that BI capability, is it third party or did you build it yourself?

Mark: It was third party, but it uses our data. It’s a third party capability that we provide we didn’t want to build that analytic. That you can just use the tool yourself if you want to as an organization and expand what we provide. All we do is take the data we provide that data we extract that data and all the relevant components of that into a database that can then be all the analytics are run on it, use a third party tool.

Craig: That’s a smart move. Do you know what that tool is, that BI tool you built on top of?

Mark: Slipping my mind right now. I think it’s a Google product.

Transforming Data into Insights

Craig: No worries, just wondering. Alright, so let’s wrap up with one final bit. You mentioned you’re doing some work with generative AI and LLMs. So how is that going to be fit into your platform and helping advisors?

Mark: So what we’re looking at was when sort of the ChatGPT craze started off last year, we looked at how can we leverage this kind of technology to further enhance the usability of our tools? So the first thing we’ve looked at is how can we use something that’s called semantic search. So we allow the user to have a voice interaction and they can type it in if they want to get into interaction with SAM, or they can just speak to SAM and have SAM speak back. So you can say things like your building plan and go Well, what if this client lived longer, live 10 years longer? So we have a wealth of capability and a tool where normally you would have to go to the stress test session. You’d have to pull the sale. Yeah, well, look at what else you’d have to sit people live longer. What if and set it to 10 years and then you’d see what the impact was?

Mark: But if you just say it to SAM, you’re anywhere in a system you say what this client live longer, it automatically interprets that as a live longer what if strategy or stress, sets it up, generates it shows you on screen right there, the impact and with all our What ifs shows the type of strategies that would be applicable to maybe reduce the exposure or enhance their ability to do fun, living longer. So that kind of capabilities. The first thing we build that’s going into production in about two months.

Mark: We’ve also been working with large language models, so that you can ask questions about the plant. Okay, so I’ve got all this detailed information about the plan. I’ve got all the strategies in there and I can see the impact. But if I see a graph where you know normally you’d get these graphs were an area graph, it builds up its retirement and it starts to draw down during retirement through to life expectancy most of the time, and ideally you want that drawdown to go past life expectancy, in order to show that you can fund all your retirement. But there can be boots on the ground.

Mark: So for example, there might be all of a sudden the graph is going down and then it pops back up again and it starts going out. Well what’s happening in that clip, you can ask, well, what’s happening in that graph where it all of a sudden spikes up, and it’ll do the analytics come back and say, Oh, you’re downsizing your house is the strategy you had there. And it’ll analyze the information and say, you’re downsizing from a million dollar house to a half million dollar house, you’ve invested the $500,000 and that increased your retirement savings from $750,000 to $1.25 million at age 80. And that’s allowing you to find your retirement. So all of that information is there in numbers.

Mark: But using a large language model, we can fire all that information to it and it’ll come back with a nice client friendly explanation. And that explanation is not just for the client, it’s also for the advisor because they might not be aware or forget that oh, that blip is due to the downside strategy. And they also want to know, well, what are the details? How much is that house worth projected out at that point in time?

Mark: What is the net capital that we’re going to get when we downsize? All that information is available if I ran a bunch of reports, but if I run a whole bunch of reports, I need to know which reports to runs. The clients at head is spinning when they see all these reports flipping up on screen and all I want is five or six key pieces of information and present it to me in a nice user friendly fashion.

Craig: Isn’t that all anyone wants? Just give us everything in a nice user friendly fashion.

Mark: Exactly. And the problem is, the more sophisticated the plans get, the harder it is to do that typically. And what ends up happening is you just run more and more reports. And that becomes harder and harder to understand. The beauty of these large language models is they can take large amounts of data, find the interactions with them, and they can present it in a client friendly, adviser friendly fashion.

Craig: Technology is getting better and better and think about we’ve only had general AI working for a year and a half and look where we are so far.

Mark: And the beauty of that is that they continue to expand that capability, right so our engine can is doing all the calculations. The generative AI models aren’t doing the calculations, but we’re leveraging them to take all this complicated calculations and present it in a very friendly fashion. And the other thing we’re looking at later this year is to be able to generate our client report or client presentation automatically by asking you Okay, generate me a summary level presentation, PowerPoint presentation, it’ll grab all the pieces, build the presentation, show it to you right there on the screen. So you as the advisor don’t have to build a presentation.

Craig: I can’t wait to see that put me on a list for a demo since that’s what we’ll do. Awesome. Mark. You’ve sent it all here. Where can our listeners find more information about Conquest Planning?

Mark: Come to our website ConquestPlanning.com, or they can contact me directly at mark@conquestplanning.com

Craig: You are accessible. Thanks, Mark. Appreciate your time.

Mark: Great, great talking to you Craig.

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ABOUT ME

The Wealth Tech Today blog is published by Craig Iskowitz, founder and CEO of Ezra Group, a boutique consulting firm that caters to banks, broker-dealers, RIA’s, asset managers and the leading vendors in the surrounding #fintech space. He can be reached at craig@ezragroupllc.com

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