#ItzOnWealthTech Ep. 69: How Engines, Automation & Data Are Changing Wealth Management

It’s another fantastic day in the wonderful world of wealthtech. Welcome to episode 69 of the Wealth Management Today podcast.

We’re going to try something a little different with this episode. I’ve been guest writing on Michael Kitces’ monthly FinTech column about the latest news in wealth management and advisor technology. We’re going to go through some of the top news stories that came out for this month and I’ll provide my input on them in a bit more detail.

Normally these little snippets on Michael’s blog, Kitces.com are just 700 or 800 words, and I really can’t get a lot of information in there. So what we’re going to do is pick a couple of stories out, and then I’m going to go into little more detail about them, and then we’ll we’ll see where things go from there.

Companies & People Mentioned

Topics Covered in this Episode

portfolio management software

Franklin Templeton Launches a Model Optimization Engine

So first story is Franklin Templeton launches an optimization engine to unbundle 401k target date funds. This is an interesting story, we’re seeing a lot more asset managers get involved in technology. A lot of them are buying technology. You know, we saw State Street bought Charles River, Jemstep was bought by Invesco. Invesco also bought a portfolio management system called Portfolio Pathway, and they recently bought a portfolio rebalancing software called RedBlack. And Franklin Templeton had just launched their own internally developed software. It’s a goals-based engine, goals optimization engine and their acronym is go, G-O-E, which was interesting. And, you know, everyone’s looking to solve for retirement. We’ve seen a lot of tools, a lot of technology beyond just financial planning software, trying to solve for retirement in different ways.financial advisor technology

There’s been a launch of a number of different tools like IncomeConductor and other tools. I’ve just focused on retirement income and how to deal with that. LifeYield also started out with decumulation, how to optimize taking assets out and selling down to decumulate. So this optimization engine is a way to do both. They’re looking to both maximize the returns in your accumulation phase by creating custom asset allocations and then do it on the downside as well. So it becomes sort of a dynamic model and it’s bespoke, allegedly, the way it should work, if it works the way they claim, where it optimizes each investor’s time horizon sort of a customized target date fund for each investor, rather than a generic target date fund that you put categories of investors in.

If this really works the way it says it works, then you would get a much more bespoke solution around each investor, but it’ll be automated so it would scale. And of course Franklin Templeton can populate the models with their own funds. And they say it’s going to be open architecture, but it really what’s the point of an asset manager spending all this money on technology if they’re not going to increase their distribution, if they’re not going to push out more of their product? They’re basically working for free. And no one works for free. I mean, I do these podcasts not for free, but for marketing in hopes that broker dealers, asset managers and FinTech firms come to my consulting firm. So it’s a free service, it’s marketing, that I’m hoping to get business out of.

So these asset managers must be doing the same thing, in my mind, putting out software that they’re selling for a lower cost or often for free, with the understanding that there’ll be some sort of benefit on the other end. But this tool looks interesting. And then Franklin Templeton, it looks like they’re going to combine this optimization engine with other technology they purchased, which was AdvisorEngine and AdvisorEngine was one of the first digital onboarding tools. We’ve been talking a lot about digital advice, digital tools, just in a number of panels I’ve been on just today I was on two panels, one with Tegra118, a FinTech firm, and one with the Money Management Institute and on both panels, digital advice solutions came up. And digital advice start out from robo advisors like Betterment and Wealthfront, and then firms like AdvisorEngine, Jemstep, Oranj and others launched their own white label, digital advice or digital onboarding, electronic onboarding for advisors, broker dealers, asset managers, or other RIAs and other firms. So they’re taking the robot solution and making it into a B2B tool.

But these firms didn’t stay onboarding for long, they started adding more functionality. AdvisorEngine bought Junxure, a CRM tool and started building out other technology, did some tight integration with Smartleaf rebalancing because they realized companies were coming to them and saying, “Great, thanks for the onboarding. We love it. But now what do we do? We have these clients that need to get portfolios, have portfolio construction, have models, have rebalancing, have reporting”. And other firms are building those things out. Jemstep also saw that or rather Invesco saw that, their software Jemstep had some success in the banking space with onboarding and other digital aspects. They were getting a lot of calls for rebalancing on the broker dealer and RIA side. So they went out and bought RedBlack, which was really good. We’ve done some reviews of RedBlack. Very powerful, very strong portfolio rebalancing software, one of the few standalone software vendors that are still on the market now and they snapped them up. Also RedBlack has very good trade order management, which a lot of rebalancers don’t have. Even some of the largest tech firms that are known for portfolio rebalancing don’t do a good job on order management, and being able to tightly integrate those saves a lot of time in operations. So I thought that Invesco buying RedBlack was a great move for them, assuming that they’re going to combine it with Jemstep. That’s my recommendation, which no one’s asked for, but that will be my recommendation.

Another interesting aspect of the Franklin Templeton announcement of their optimization engine is they’re partnering with NextCapital. And NextCapital is also in the news, we’ll get to that next. NextCapital is kind of a robo platform, B2B robo platform that automates managed account solutions in the defined benefits space and 401k space.

So definitely an interesting take on things, interesting pitch for their software and Franklin Templeton is partnering with them with their optimization engine that will be implemented by NextCapital. So again, they didn’t have a lot of details, but the way I see it, an advisor would start the optimization engine, enter a lot of information about the client and then the engine would generate an asset allocation. And then feed that over to NextCapital, which would build a discretionary managed account portfolio, which could include Franklin Templeton funds. It could include separately managed accounts, ETFs, anything really, and then they would manage it and then take a feed from the Franklin Templeton optimization engine. Can I call it GOE? Would that be confusing, the GOE Engine? It’s hard to say what the acronym is going to sound like, the Franklin Templeton GOE Engine.

And as the client ages and goes through life, the engine we’re optimizing will continually tweak the asset allocation to give them the highest probability of reaching their goals. That way it works kind of like a customized target date fund for that particular investor. And for that particular goal, right, it could be a retirement goal that could be a philanthropic goal, it could be an educational goal. So I imagine the software is scalable and should be able to handle any number of goals.

Franklin also claimed which I didn’t include in the in my writeup because I couldn’t verify it, that it’s driven by machine learning. And I hear a lot of firms throw the machine learning buzzword out and say, “Oh, we’re backed by machine learning”, but they really aren’t. And I don’t know that for a fact about the Franklin Templeton product, so I left that out of my writeup because I couldn’t verify that it really was based on machine learning. Cause we hear a lot of that, and there’s no data about one client that you can build a machine learning interface with, or use any machine learning techniques to gather you need millions of clients’ data points in order to feed a machine learning engine and develop insights that you can use. So maybe they’re looking across their entire client base of all Franklin Templeton’s accounts, but then how do you know what their goals are? It was just very fuzzy to me whether they were really using machine learning or not, but hopefully they can take advantage of it in some way, make the optimization more successful. After 40 or 50 years of this application running, they’ll have a lot more data points, but not right now.

So interesting optimization tool, interesting way to approach the target date defined benefits 401k market with something to differentiate because advisors need to differentiate. There’s a lot of competition, both from robos, fintechs other online retail focused consumer products, consumer companies. And they’re going to be nibbling away at advisors’ business, taking a bit here and taking a bit there and it’s going to hurt. It’s going to definitely start impacting advisors’ competitiveness and ability to make money. So any way that they can offer something that other firms don’t have, the Franklin GOE Engine, I like that term, could be very successful.

NextCapital Raises $30 Million for Their 401k Managed Accounts Robo

Next up is NextCapital. As I just spoke about, Franklin Templeton is partnering with NextCapital, but NextCapital’s in the news on Kitces.com. You can check out The Latest in Financial AdvisorTech News (October 2020) is the article and I’m guest blogging with Michael just this month. So NextCapital. They’ve been around for a while, at least the core of the company started over 20 years ago with a company that was doing something else in the retirement space. And then the same team pivoted and started a new company and really wanted to focus on the defined benefit space. Somehow being able to automate IRA rollovers into 401ks, it’s a great idea be able to do that would help a lot of advisors scale their business. And NextCapital just raised another $30 million, which is a nice chunk of change to help them build out their platform, do more marketing, and hire more smart people.

financial advisor technology

I think their funding is up to $85 million now, not a bad amount and they’re they’re doing more partnering like with Franklin Templeton and really trying to work their way into the defined benefit space and sell to advisors who do 401k plans and manage other types of retirement plans where they can automate a lot of that functionality.They interface with record keepers and are a paperless IRA rollover solution. They auto-populate all the forms and the account opening documents, because that can take a lot of effort for advisors, a lot of pain for them. So using NextCapital’s tools would allow them to automate a lot of that function, and automate a lot of what they do for 401k plans, and allow the advisors to focus on building out their models, providing good customer service, and putting their value into the plans.

There’s not a lot of firms are in this space. So that’s interesting. They have a lot of interesting clients, they’ve gotten some big clients like MassMutual and John Hancock which definitely validated NextCapital’s business model, that it has a value and is definitely scalable. They’ve got some competitors, definitely like Morningstar and Edelman Financial Engines, Financial Engines being the world’s biggest robo, which not a lot of people realize that Financial Engines was a robo before robos were robos, except they only focused in the retirement 401k space. They automated the entire process of managing a 401k plan for a client, they did all the asset allocation, the securities based on a really relatively simple and rules based engine.

I built one of these for one of their competitors, and the the underlying core is relatively straightforward when you put together the rules of how old is the participant, younger being more aggressive, older, being less aggressive, which isn’t always true, but using this type of rules based engine, you make that assumption. What type of pension fund are they in, what 401k are they in? What are the benefits from it? What’s the company match, you know, like the first rule is, “Are you maximizing your company match?” If the participant isn’t boom, you just recommend that right off the bat. You come up with their expenses from the proposed risk expenses in retirement, based on their salary, current salary, you figure out do like an 80% roughly, but it’s actuarial tables that show you how much their retirement’s going to be.

And then based on that, you run a bunch of Monte Carlos to see whether they are going to be able to retire, and if they can’t, if they aren’t in the Goldilocks zone percentage probability of retiring, you make recommendations like retire later, lower your expenses you know, increase how much you’re putting into your fund so you maximize the company match. So there’s only a couple of different widgets that you have to work with in these 401ks or other defined contribution plans, but it’s very helpful. And it’s very profitable for the firms that provide it because they can charge a couple of dollars a month per employee, and if your client is FedEx with a hundred thousand employees, that’s a couple hundred thousand dollars a month, it adds up you know.

I think NextCapital’s got a great future, they seem to have a lot of traction. Even though there are still microcap in the space, they’ve got about $2 billion in assets versus Financial Engines with a couple hundred billion I would think, they’re pretty big. But they’re growing, and there’s always going to be an opportunity for small players that have some unique value proposition to take some niche business from the established players. Cause everyone wants an alternative. There’s always a niche. You know the 80/20 rule, there’s always 20% that don’t want what everyone else is using and are looking for an alternative. So there’s definitely room for NextCapital to grow. They could take that $30 million they just got and keep building out their platform, keep finding new ways to differentiate. Maybe it’s more partnerships like Franklin Templeton’s GOE Engine that can give them the opportunity, but there’s definitely room for NextCapital to grow their business and land some of the big clients.

Invest In Others

Envestnet | Yodlee Launches Consumer Spending Insights

Okay, next up, “Envestnet | Yodlee Launches Consumer Spending “Insights” APIs As Financial Planning Goes Holistically Beyond The Balance Sheet”. It’s a long title. So this is an announcement by Envestnet and they’re Yodlee division that they’re offering API access into their consumer insights data and analytics. This is really the future of wealth management. What we keep hearing the term holistic being thrown around, such a buzzword. So tired of it. A lot of firms don’t know what it means. They think they’re holistic and they’re not. It’s just something they throw out there as a marketing term. “Yes, we’re holistic”, but they don’t really provide a complete view of a household’s financial life. And that’s got to include not just the assets, which most firms in our industry, it’s all they care about, but liabilities, expenses, cashflow, insurance you know, other types of interactions with finance that are rarely touched by most of the other products out there. So Envestnet | Yodlee’s APIs should give access to this massive trove of data Yodlee has available and some really strong analytics on what consumers are doing. And they match them up with an advisor’s clients to say, Hey, you know, Craig Iskowitz is your client, here’s his assets. But by the way, he’s got these credit cards, which he’s given you access to of course, you have to get approval from the consumer, and here’s there’s expenses. Here’s where he’s spending his money. Here’s his insurance, here’s his annuities. Here’s his subscription services and all the things he’s working on, or the thing, all the things he’s paying for all the other aspects of that can be pulled from these data aggregation providers, and actually take that data by pulling it through the APIs and pumping it into other systems, using it to feed other tools and analytics, to give advisors a better view of what they’re doing and also to customize models.financial advisor technology

So you could build a better model for a client. If you knew more about them, you could build better reporting for clients if you knew more about them, you can make other recommendations. You can nudge them in ways that would improve their financial health. And it’s more than just, “don’t buy that Starbucks latte”, it may be, you know, you need to do a better job saving for retirement. You may need a better job saving for education. You need to maybe look at the mortgage, even that level of detail, and say, Hey, you know, we saw your mortgage and you can get a better rate, or you’ve got these student loans, you need to pay them off. And here’s why, or maybe you don’t pay them off. Maybe those student loans are great because there’s such a low interest rate, you should pay off some other things instead.

There’s a lot of opportunity for taking this data around liabilities and other things that the clients are going to be owing in the future or insurance, and being able to merge them and pull this data. Of course, once it’s an API, which is an application programmatic programming interface, only the biggest firms can do this. Firms that have tech staffs that understand what an API is, understand how to pull the data and have their own systems that they can put the data into. Just because you have data, if you have nowhere to put it, if you have nothing to process it, nothing to analyze it. It’s useless. Data just sits there. It doesn’t do you any good at all. So you’re going to need only firms that have developers, programmers.

People who understand how to call an API, that have systems that can take the data and do something with it are going to find value. But those firms could really set themselves apart in how they provide holistic financial planning to their clients, feeding this data into other tools and other planning systems that can make their advice more bespoke and more customized because every client wants to feel like they’re getting a customized service. Everyone, whether they want to buy a Volkswagen or get a Mercedes. They want to have a low price, but then get the best kind of service. So using these types of tools that can not only provide the data, but provide it in a way that should be more integrated with the advisors’ and broker dealers’ existing technology. So you’re not bringing a home to the platform and assuming they’re not currently an Evnestnet customer, they could just these APIs and then feed the data into their existing platform and the advisors who are using it wouldn’t know the difference. It looks just like another piece of their current platform yet it’s giving them better insights.

I know one large wirehouse was doing things like taking the MLS, the real estate and multiple listing service data and comparing it to their existing clients and breaking it down by advisor and saying, “Hey, Mr. or Ms. Advisor, you know, one of your clients has just put their house on the market. You should call them, they’re moving. They’re going to have expenses, maybe they got a new job”, those types of things, very small. And that’s not really AI, but it’s just taking existing data, crunching it, analyzing it, and then taking action on it or giving advisors a quick next best actions list to make it easy for them to know what to do so they can focus on serving the client, getting to know them, doing the things that are value added from a human point of view and leaving the number crunching and other wrote work to the tools.

I’ve always liked the purchase of Yodlee. I know it was it was roundly trashed when they bought them back in 2015, that it was too expensive, but they’re laughing all the way not to the bank, but to better software and more clients beause they’d be able to integrate it more tightly into their platform. Every vendor, every data aggregation vendor has to integrate whether it’s you know, Yodlee or ByAllAccounts or Covo, or Finicity. They offer integrations, but it can’t be as tight as when you own the software. Right? So Envestnet now owning Yodlee, it becomes way more of a seamless experience, much tighter integration at the lowest level, as opposed to just plugging something in. Even if it’s plugged in tightly, it’s still not gonna be the same. It’s not going to be as good. And it’s also a decent revenue generator again, a small piece of Envestnet’s overall revenue, I think it’s like 10%, but it’s still churning out cash, and it’s something else that can sell existing clients, which they need because there’s such a such a high market share in the space.

And so the insight solutions, they have another platform which they’re using for mortgages and and other lending. So they’re using the insights. They’re gaining from data to provide alternative approvals for mortgages and loans that’s not based on the credit score, it’s based on other data. So that’s a sort of a quiet thing Yodlee’s been doing to get into other spaces and generate other revenue streams by leveraging the data they have in new ways. And that it helps them learn and be able to provide other aspects and other outcomes. So by offering the solutions, not only are they monetizing the data they’ve already got in different ways, they don’t have to build any interfaces, which is expensive, building all the user interaction. That’s a very expensive part because clients are constantly tweaking it and saying, I don’t like it, and I don’t want to do it this way, do it that way. Every client wants their own unique, bespoke solution on the user experience side by delivering on APIs, Envestnet doesn’t care. Hey, Mr. Client, Mr. Broker Dealer build it any way you want. We’re just gonna give you the data and then we’re going to charge you per transaction, per data however it works, and it’s a steady revenue stream.

But they can plug into anything. They can plug into the competitors, right? So if I’m a broker dealer, I’m using a competitive tool, if I’m using Vestmark or Tegra118, or to Charles River I can take my Yodlee data and plug it into that platform and it doesn’t matter. And that gives me as the broker dealer more power. Cause if I’m a broker dealer, I want to build layers. I don’t want to have one vendor own everything, right? Then I’m stuck with that vendor and if I change that vendor, I’ve got to change everything out. If it’s a layer, an onboarding layer, data access layer, if it’s a rebalancing layer where each tool, I control it, I can unplug one and plug it in, plug something else in, I build my own hub and I’m in control. I can say, Okay, Envestnet, I’m tired of you. I’m going to bring in Tegra118 and I can just plug and play with that rather than ripping the whole thing out and then having to put in a whole new platform, every single piece of the way.

So I did a podcast a couple of weeks ago with Brian Ross from FIX Flyer about the API economy, where tools like FIX Flyer, which is an order management solution, can now deliver their entire platform API only. So you can do order management via APIs, which was unheard of. That was another big lift. We’d done some of those system implementations, which were a nightmare trying to put in a new order management system and all the connectivity, but if it’s just an API or a group of APIs is much easier to unplug, plug something else and I’ll put something else in side by side.

A great opportunity for Envestnet | Yodlee here to also make their clients stickier, right? If you’re just a tech vendor like Envestnet’s competitors that don’t have their own Yodlee which none of them do as far as I know, they’re just offering tech, you’re not as sticky. If you’ve also got these insights where the broker dealer is building into your APIs, makes you a little stickier, right? You’re using more. You’re building it more tightly into your system. And again, this is the opposite of what I just said that using APIs makes it less sticky, but it also works in the reverse that it’s giving you more things to sell to clients and more ways to find out what they’re doing and how they’re working. It can, it can work in the opposite way as well, depending on how it’s positioned. I’d love to see how the Yodlee insights continue to improve and what new stuff they come out with to help their clients provide more holistic, really holistic, not just air quotes, “holistic” advice.

Okay. Last story in the news this month on the Kitces.com website for October, 2020 is “YCharts Expanding To Larger RIAs And Broker-Dealers By Adding SMA Data To Their Expanding Portfolio Analytics Toolkit”. I really like YCharts and just full disclosure, my consulting firm has done some strategy work for YCharts and I should also do full disclosure on the other stories, we’ve also done some work for Envestnet in the past but not Franklin Templeton, no work for them, but there you go. There’s your full disclosure. So what I like about YCharts and even before we did some work for them we followed them, because this is our job, right? We keep track of all the technology in the space and we do a lot of research. We’ve got a research arm of Ezra Group run by our head of research, Jean Sullivan. And we do a lot of competitive analysis reviews, market analysis, client segmentation, revenue potential, product market fit, and YCharts was interesting. It started out focused on charting and technical analysis, but they expanded into more portfolio analytics and built a really nice solution for advisors who are more into their investment strategies and want to focus on delivering bespoke investment solutions to their clients. So they use the portfolio analytics of YCharts to do filtering and criteria across a wide range of products. But up until now, it’s only been ETFs, mutual funds, and equities. And now with this launch, they can also do separately managed accounts. That’s a big move, especially in the broker dealer space because broker dealers all support SMAs.

And one of the big reasons is they’re good for higher net worth clients, but also they need them to be able to capture breakaway brokers, advisors leaving wirehouses, almost always have some sort of SMA assets. And if you’re a broker dealer and you’re trying to bring those advisors over, you want to bring their assets over without repapering, without changing managers. So you’ve got to have a pretty broad range of managers, SMAs, on your platform because no advisor wants to call their clients and say, “Yeah, I’m changing broker deals and you have to sell all your stocks so I can put you in a different manager,” not a conversation any advisors want to have. So by offering this tool from YCharts, they can go to more broker dealers and say, “Hey, you know your advisors who are building their own models, they’re doing Rep-asPM. They want better ways to filter and look up criteria of separately managed accounts”.

I think there’s more than 8,000 or 10,000 I haven’t checked the numbers recently, strategies from however many, 500, 600 asset managers in the space. That’s a lot, there’s a lot of data there and it’s not the same as looking up equities or mutual funds or ETFs. Yes, looking at SMAs is very different, the data you look at is very different, and the way you compare them is very different. So it took a while for YCharts to build that and I haven’t seen the interface, we’ll get a demo hopefully in a couple of weeks to see what they’re doing to make it easier for advisors to sort, filter and pull out the SMAs that work best in their portfolios. It’s usually doing complimentary analysis saying, “I’ve got this gap in my portfolio. I’m looking for an SMA that does X, you know, whatever that particular kind of SMA is, large cap, small cap, mid cap, international”, whatever, the, whatever the particular criteria sectors is it a Brazilian fund, is it APAC, you know, and to trying to fill gaps with specific SMAs, you need a good screening and filtering tool to look up things like performance, risk allocations, exposure metrics when you’re exposed to different sectors, exposure in different geographies, manager tenure fees, benchmarks. So those types of things you want to be able to filter and screen on across the entire universe of SMAs. And YCharts gets the rest of my data from Morningstar, which is not a big surprise since Morningstar is an investor in YCharts, which is also interesting because YCharts competes with Morningstar direct, which does a lot of portfolio analytics and a little bit with Morningstar Workstation.

So I guess Morningstar doesn’t want to have all their eggs in one basket and wants to keep their finger on the pulse, by investing in someone who is a competitor, and maybe there’ll be buying them at some point in the future, but they’re certainly gaining some insights into what they’re doing. So that’s interesting and it also gives them access to other types of clients. So maybe higher net worth RIAs that have a larger percentage of their assets in separately managed accounts. So I think this is definitely a good move by YCharts building out their platform, making it more robust, making it more accessible and making it more interesting to broker dealers and other firms.

For example, LPL just added YCharts to their vendor affinity program and LPL has a number of levels. So it doesn’t mean they’re recommending YCharts or forcing their advisors to use YCharts. Not at all. It’s just supported which I believe is what the vendor affinity program means, but they still have to go sell it and the advisors have to select it, but there’s 17,000 advisors in LPL. So it’s not a bad thing to get access to that and be able to use it. There’s other charting that have news capabilities, screening capabilities. I believe YCharts also already has client communication tools that allow advisors to build custom presentations to advisors, to explain why they picked certain assets, why they built certain portfolios, which is really cool because anything that can add more value and create more touch points and make it easier for an advisor to communicate with clients is going to be valuable. And it’s another reason why advisors seem to love YCharts and their product set.

And that’s it for our new format. We’re probably going to be doing these news roundups once a month. So please let us know what you think of this format. Do you like it? Do you not like it? Is this something you want to see more of or hear more over other let us know. I’ll make sure to subscribe to this podcast on iTunes, Spotify, Stitcher, or wherever you listen to podcasts and share it on your social media. Give us a five star review and we’ll look forward to talking to you all next time.

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