“The data consumption model has changed over the years from primarily web based access to a lot more API’s and direct feeds. The processing of the data has evolved as well, whether it’s for performance reporting or direct to investor, as the needs of the user to view a net worth of their accounts. That’s going to influence what we do to the data and how we make it available.”
— Don McHenry, Senior Product Manager, Morningstar | ByAllAccounts
- Trends in Data Aggregation
- How Processing Held Away Data Has Changed
- Data Aggregation via APIs
- What is Data Enrichment?
- Comparing Data Aggregation Vendors
Craig: For this episode, it is Don McHenry, Senior Product Manager at Morningstar, ByAllAccounts. Don, welcome.
Don: Thank you. Good to meet you, Craig.
Craig: I’m glad you could make it. I’m glad we’re having this discussion. It’s all about data aggregation. This is a topic we like talking about. We’re consultants, we’re always looking at products and platforms and applications and working with a lot of vendors and working with a lot of broker dealers and large RIAs. Data aggregation comes up all the time, whether it’s client portals or reporting. Now we’re caught where advisors are able to directly trade some of these held away assets with some vendors. There’s lots going on. It’s a fast changing part of the industry, and something that everyone needs, table stakes now. So let’s start it off. If you could give us the elevator pitch for ByAllAccounts.
Don: ByAllAccounts is the only aggregator that’s focused exclusively on the investor, the advisor and the platforms that support them. So we were built specifically to deliver high quality enriched data for the purpose of complex investment use cases like performance reporting and portfolio accounting. And what that means is that we are enriching the transactional data that we aggregate for the demands of a reconciliation use case. We’re providing highly configured data output options so that our data can meet the unique needs of our customers systems, helping reduce operational overhead, and also consistently matching positions to their correct identifiers, which sounds like a fairly obvious and easy thing to do, but it can be quite challenging. And our system has really only become more sophisticated over time. We were founded about 22 years ago, acquired by Morningstar in 2014. And that has really given us access to an incredible depth now of investment product data that we can really use to power our enrichment capabilities in differentiated ways.
Trends in Data Aggregation
Craig: That’s what it’s all about. Everyone wants to differentiate. Everybody wants to figure out how to stand apart from the crowd because there’s so many products out there. Let’s talk about what are you seeing in trends around data aggregation, what’s new and interesting in the data aggregation world?
Don: So there’s certainly an industry wide move to open banking. We’re very bullish on that and believe that is where the industry is going. So we support these sources today, and it’s really a high priority for us to support more as they become available. And what open banking allows aggregators and account holders to do is really bypass the need for aggregators to store client credentials. Instead, during the account setup experience, we route the user to the bank site, where they actually log in directly to the financial institution and manage the aggregator or the app consent there. So we don’t need to store client credentials. We’re not subject to account breakages because of multi factor authentication. It’s quicker to connect because it’s an API, and then customers have a lot more control over who can access their data. They can log right into their security center of their financial institution and see who they’ve consented access to their data. So that’s certainly one trend.
Don: We’re actively involved ourselves as ByAllAccounts as members of various consortiums that are really beginning to set the standards for open banking API’s and data and it’s really great to be at that table with our focus on the advisor and the investor use cases we’re able to really speak up for their needs, help influence standards from the perspective of serving their use cases. So, what data points do they need? What account types is the API model for, investment transactions suitable for portfolio accounting.
Don: That’s certainly a prominent trend and that kind of also brings up a point of connectivity types, right. A lot of different ways that aggregators connect to financial institutions to collect data for account holders. Certainly, the preferred method would be direct connections. But you know, you need to be prepared to support all types of connections as an aggregator it’s a very fragmented universe. So most connections, there’s 10, 15, 20,000 connections out there. Most are still web connection, but most of the volume is coming through API’s. So I mentioned we would prefer the direct connections. They are a supported delivery mechanism, the user experience is typically better, no multi factor authentication that the user has to deal with when connecting accounts, less breaking.
Don: But one thing that’s kind of important to keep in mind is that the core intrinsic data quality is really a matter of what the financial institution has stored. So what I mean by that is bad data kind of manifests through any channel, whether it’s an API or website. So while the API connections are always preferred, they don’t guarantee better data. And that’s why it’s important to participate in these forums where we can help influence the data that’s available through these channels. And where an aggregator you know, can really stand out is really the use case driven enrichment that they provide to the data. So where there are data shortcomings independent of the collection channel, and really asserting your subject matter expertise, your technology to make that data, accurate, complete and actionable for your customers.
How Processing Held Away Data Has Changed
Craig: I’m going to ask a few technical questions. But first, can you talk about the way you manage and process data how that’s changed?
Don: Absolutely. Certainly the data consumption model has changed over the years from primarily web based access to now a lot more API’s and indirect feeds available. The processing of the data has evolved as well. Really, it’s driven by use cases, whether we’re processing data for performance reporting, use case or direct to investor use case that just involves the need for a user to view, a net worth of their accounts, that’s really going to influence, what we do to the data and how we make it available. For instance, we support both API and batch delivery for data files, again, really use case driven. So a firm that’s interested in daily, back office reporting, they’re probably consuming batch files from us. Whereas a firm that’s interested in more user engagement, the real time API’s would be preferred. And that has evolved, over the years to have more of a focus on delivering use case driven API’s. For those user engagement purposes, making sure those API’s are performant understanding, what endpoints you need to provide for specific use cases. And balancing the completeness of the data with the speed and the performance of the endpoints that you’re making available.
Craig: That’s a great point. Can you talk about some of the parameters you evaluate when you’re balancing data and speed with the performance of the endpoints? I think clients want both, they want it completely accurate and right now, but how do you do that and which trade offs are you making?
Don: Sure. One example is, let’s say it’s a complicated use case where the there’s an end client portal where an account holder is interacting with the aggregation service, but the advisor also wants that data into their power reconciliation and performance reporting platform to provide holistic performance for their client. When the client goes in and connects their accounts, they really just care about real time seeing the bounce of those accounts, seeing their net worth. So it’s not really that important at that point in time to go and collect three months of transactional data and slow down the experience that the users having to gain access to those accounts and to see that data.
Don: So that operation may be tabled for an overnight operation or for something that happens subsequent to the users gaining access to that data in real time. And then making of course the additional scope of data available and enriched for the daily back office, batch import for reconciliation and reporting. Kind of bifurcating those two use cases but still serving the greater enterprise.
Craig: Indeed. So you guys have been around a long time. One of the the oldest vendors. So as you’re seeing the industry change and data sources changed, how has the way you manage and process data changed?
Don: I would say that the way that we manage and process data, there’s the need kind of like I mentioned before, to bifurcate the aggregation experiences so you we still need to serve the the back office use cases that require data prior to data available first thing in the morning for performance reporting, but we also need to be able to serve use cases of investors that require data on demand with little friction, and balance those two things to still be performant and still deliver a service that is acceptable.
Craig: Well, we want it to be more than acceptable.
Data Aggregation via APIs
Craig: Indeed. So, are you seeing an uptick? You mentioned moving from websites to API’s. Is that really moving, are your clients pushing that? Are they are they asking for more access via API’s?
Don: Yes, certainly, as I mentioned before, there’s the perception that the data is better through the API. It’s our stance that it’s really what the aggregator brings to the table in terms of how good of an output you’re going to get for the enriched data, whether it’s coming from an API or a website, but certainly we would prefer the API connections from a user experience perspective as with our customers, there’s less downtime in aggregation. There’s less need for the end user to be involved in repairing a connection. So it’s certainly the wish of our customers and the objective of us too, as it is with every aggregator to adopt all the API’s as they become available and be on the forefront of of that.
Craig: Oh, yeah. It’s in everybody’s best interest and we do a lot of work with that as well. We’re working on some integration scoring for vendors to show how well they’re moving away from manual interventions or manual connections and towards more automated real time connections, like through API, so we’re big proponents of that.
Don: If I could ask a question if that’s alright, I’m just curious what kind of scoring criteria do you use?
Craig: Well, for example, it’s based on three primary criteria. One is the breadth of the integration. So how many different integrations do you have? And then the depth of integration I think breadth is like 15% of the score, depth is 60%. So what’s that 75%, and then the last 25% is ease of use. So you can’t just tell them, you can just build a bunch of single sign ons and flood it and say we’re going to get a good score because your depth is going to be zero or one, right? And we’re also looking for the core applications that most advisors use. So the top three CRMs, the top three or four portfolio management tools, the top three or four financial planning tools, so we really want vendors to integrate with all the top vendors so they’re all meshed. Then the ease of use, all the API’s are documented their sample code, we call a couple clients, ask them how it’s working. Yeah, it was easy. So that’s going to be part of it because if you have API’s, but they’re hard to use, or you require a developer from the vendor to help you every time we try to use it. Well, then it’s certainly very helpful.
Don: Yeah, that’s interesting, that’s good to hear. So thank you for sharing that. And I think one of the things that firms have to think of when when selecting an aggregation vendor, to your point is, what markets are they committed to, what data are they collecting? Is it actionable for their use case, specifically, and do they cover the right sources for me.
Craig: Oh, yeah. And the right sources can be different for different vendors, different clients.
What is Data Enrichment?
Craig: So we talked about data enrichment you mentioned that, can you can you go a little bit more detail about how you guys enrich the data, and what does that mean?
Don: Absolutely. So, as I mentioned, at the top, we’re really focused on on delivering high quality, enriched investment data for the purpose of of performance reporting in this case. Now we certainly also collect non investment data, we provide transaction classification as well for non investment data. But when it boils down to at the core of our service, we look at the transaction we don’t just see it really as a $5 expense at Starbucks. We look to understand the impact that the transaction has on the underlying positions, on cash in the account, on cost basis, and there’s a lot of core enrichment that we have dedicated towards that.
Don: Some examples are, transaction synthesis, so creating accompanying transactions in order really to minimize share breaks, cash flow issues that would otherwise be experienced. A basic example of that is if you look in your 401k account, you’ll see a contribution every pay period, into each fund, right? So it’s just a single transaction contribution into your fund. From a portfolio accounting perspective, that’s not really that helpful, because what’s really happening is there’s a positive cash and then a buy of the underlying mutual funds. So you need to reflect that in order to have the account reconciled properly and to deliver a suitable data for that use case. And there’s other examples for transaction synthesis that I won’t get to too much detail in. Subtyping is another really important thing. We populate a subtype field to include additional transaction type details, which are important for our customers systems.
Don: Another thing is that financial institutions really are not always consistent with their transaction signage. Even for similar transaction activity, we normalize transaction signage, and this really helps disambiguate the effect that the transaction has on on cash flow and position changes. So those are some of the core enrichment that we provide in there. There’s many more examples happy to discuss if you’d like. We also provide a lot of customer specific enrichment options. And this is really what helps differentiate us as well and positions us very well in the wealth management space.
Don: Similar transaction synthesis available for customer specific needs. What I mean by that is for a fixed income trade a customer may wish to see the sale of fixed income include the sale of the accrued interest in a single line item they might want to separate it. Also when it comes to dividends, they may want a single reinvestment dividend or they may want the separate transactions to represent that reinvestment like a dividend and a buy. So we certainly have that option. Also, for a customer specific enrichment, we have a lot of control that we give the customers over the data output. And this is extremely important because twe integrate off the shelf with many major platforms, but there’s also proprietary systems that leverage our service and they need to be able to easily plug into their platform, so we allow them to really customize the data output in ways that help reduce the integration costs, allow also a lot of really ad hoc translations and filters of the data so we get feedback from our customers. Our normalization will decide the best transaction type but maybe our customer systems have special handling that requires some kind of unique modification to our default handling. We take that feedback as just a normal part of our service and can deliver ad hoc translations for our customers.
Don: Also off the shelf, deliver the need or the ability to filter out positions in transaction. So if there’s certain transactions our customers don’t want to see, let’s say they have a trade order management system, they don’t want the buys and sells they want all the other activity. We can filter those out. There’s information or journal transactions, they don’t want those, we can filter those out. So those are some examples of the customer specific enrichment. And really, all of these things that we do, what they aim to do is help reduce the cost of leveraging a data aggregation provider for these advanced reporting use cases. So there’s typically a lot of back office costs that go into poor data quality, right, and there certainly technologies that are involved in this but there’s also a lot of individuals that that touched data when it comes into a back office platform and the more poor the data quality is the more individuals and the more time they need to spend in preparing it for for their customers. And poor data, of course, erodes the trust between an investor and advisor also between the advisor and the platform. We aim certainly to to help avoid those tough conversations of bad data quality.
Comparing Data Aggregation Vendors
Craig: One thing that I found is difficult when it comes to data aggregation vendors is comparing them. It’s very difficult to look at the output because it’s not like this report. I can just run to show me which one’s better. It’s mostly run over time, looking at hundreds or more of different data sources under different conditions, different times of the year, times of the month. So what have you found when you’re comparing yourself to other vendors? What were your strengths or weaknesses?
Don: Sure, like I was mentioning before, you know, in general, when selecting a vendor, you want to understand what market is that aggregator committed to? What use cases are they enriching the data for, is it for payments? Is it for credit decisioning is it for investment purposes as a foreigner spending? Did they cover the right sources for you? So those are all really important questions to ask when, when selecting a vendor, one of the other things that really helps that’s set ByAllAccounts apart, of course, is the fact that we are a Morningstar product. So really, the aggregation and engagement solutions that we can deliver with use of the Morningstar ecosystem is really greater than a sum of its parts.
Don: We have the ability to collaborate across teams within Morningstar that serve a whole cross section of the financial services industry. So the products that serve the investor products that serve the enterprise products that serve the advisor, and we have a lot of great internal partners that use our aggregation service in these products. So we can actually see how our data is being used, what works, what doesn’t work, where do we need to invest to make enhancements?
Don: So again, from our perspective, we’re really committed to the investor, the advisor and the platforms that support them. We certainly have have great external partners as well where we can get this feedback but it’s a big benefit to have this in house. And also, as part of the morning story ecosystem, there’s all sorts of great tools and data available to help us really create a flywheel effect with our products. Certainly we have customers that use our aggregation and their Morningstar services and kind of integrate those together themselves. And one of the things that that we’re investing in now and in the near future is kind of delivering even more turnkey aggregation solutions that involve other Morningstar data and other Morningstar analysis capabilities. To provide really a level of depth that differentiates us amongst other aggregators.
Craig: And back to differentiation that’s what it’s about. Let’s talk about something fun. So let’s talk about the buzz we’re hearing what is going on, there’s so much talk about acquisitions and more mergers, and we of course, we had the Plaid attempted acquisition. What are you hearing around the buzz in the industry?
Don: There’s quite a lot of buzz I think you mentioned the Plaid attempted acquisition, I think at the time the valuation was was $5 billion, which was quite a surprise for many and I think their valuation has even increased many fold since then. So really a of this buzz is attributed of two main areas, so competitive pressures and advancements in technology.
Don: So, from the competitive perspective, fintechs are really accelerating digital transformation for older wealth management enterprises. What I mean by that is that, you know, customers can really use free services to see a 360 degree view of their financial lives. They expect this now with their advisor, their money manager to have the same capabilities, because if they don’t, someone else will. So when an advisor uses aggregation to gain access to all of their customers data that really makes a highly compelling and customized and personalized experience so they can deliver. And then on the advancements in technology side, aggregation is no longer really just about an overview of accounts, right. It’s how is that data being enriched and how is it made actionable for use within the enterprise. Everything from simple network delivery to end users to suitability, business intelligence, customer engagement and marketing. And now with with open banking, customers, our consumers data is portable, right? So belongs to them, that they can share this between apps and as an aggregator now we are at the intersection of all this. We’re the intermediaries that bring all this data together between stakeholders and we grow with the ecosystem.
Craig: There were reports a while back, banks shutting off access to third party data aggregators because they were screen scraping the websites, and they didn’t like that. Is that still happening and if so, how are you dealing with it? I imagine the open banking API’s link into that somehow.
Don: Certainly. We’ve engaged like I said, we’re live now with open banking API’s with with a number of institutions and we’re engaged in building connections with others. Part of the the deal here is that we’re getting off the website. We’re not agreeing for the website any longer with banking API’s are available. So there’s certainly quite a bit of operational internal migrations that need to happen and collaboration with our customers to make that work. But typically, institutions are giving us a deadline, right? Okay. Here’s access to our making API’s. Great. We have a direct relationship with you and now it’s time to move to that channel. And we will essentially block the website connection at this date. We’re definitely seeing that and we’re working together with the financial institutions and abiding by their needs for that.
Don: And then there’s also kind of the more rogue situations that you’ll see where they’ll implement certain technologies that just simply block aggregation all together and make it very difficult to aggregate accounts and erode the user experience. In those cases there’s two things we can do. One is we attempt to make our technology as adaptable as possible and have the best messaging to our user about connecting accounts and setting up accounts. And then the other option of course, which is always what we attempt to do is connect with the institution, establish a relationship with them, and discover alternative means for collecting data.
Craig: Cool, very cool. So one other thing that we are seeing on our end, is the concept of aggregator of aggregators, and it seems like it’s gaining momentum at some firms, especially larger firms, larger broker dealers that can afford to build out their own technology, or other vendors that are building tools to connect to multiple API’s or multiple aggregators. Are you seeing that as well and how do you see that changing the way aggregation is used?
Don: I think the biggest thing to keep in mind for that is that it’s really important for the aggregator to own the whole aggregation experience. Ultimately, it’s about delivering a compelling user experience, keeping the client engaged, and by owning the whole, from the connection, to the enrichment, to the delivery of the data. You’re providing more value than someone that doesn’t provide that service. Can you know there there are certainly some advantages of aggregator aggregators in terms of being able to point shoot at different institutions, but at the end of the day, it’s not them that has control over the technology, the connections and being owning that yourself is a major benefit.
Craig: Can you share some of your product roadmap what’s coming down the pike for ByAllAccounts users to look forward to?
Don: Sure, we’re really focused on on three areas. Those three areas are investor engagement, advisor ROI and workflow automation. So from an investor engagement perspective, I mentioned this ecosystem, Morningstar capabilities, we have an our data is really plug and play into this ecosystem. One of the things I failed to mention earlier when I was talking about our enrichment is not only will we map, all positions that we aggregate to their accurate ticker, CUSIP, we actually also map them to the internal Morningstar ID. And that really unlocks a lot for our customers. We have many customers that are also Morningstar data customers, and they can really easily correlate the aggregated data with the Morningstar data.
Don: So we’re now taking the initiative to make some of these services a little more turnkey for our customers. Adding things like if you think about a customer aggregating their portfolio through our services, hey, we can add the portfolio risk, or we can add the CIS, excuse me, sustainability rating. This is great because investment behavior really has changed for younger investors. So if you’re trying to go more downstream with your users or reach a larger audience, they’re looking for more editorial content there. They want to make sure that their portfolio aligns with their risk and their values, understanding the holding and sector kind of exposure that their portfolio has. And these are all things we can really deliver off the shelf with all these great Morningstar capabilities we have so certainly investing more than that in the realm of investor engagement.
Don: Also in that realm, financial wellness tools. High level kind of view of financial health married with guidance. We have a great team here of behavioral scientists that are really helping us innovate and drive and these tools and bring them to market so they’re less focused on being in the budgeting weeds, and take more of a holistic approach and financial wellness.
Don: What I mean by that is how much income are you allocating towards debt for day to day consumption verse the future and is that balanced according to your goals and maybe our recommendations, how is your savings from a short term and long term solvency perspective. Are you prepared for an emergency event, losing your job, how close are you to financial freedom if you’re an older individual closer to retirement. So those are really exciting, financial wellness tools. And then also in the investor engagement side, we’re committed to delivering, the broadest set of data connections for investors and advisors. So, that means connecting to new asset classes, right. So cryptocurrency is something that is in high demand, we have customers that that need access to these sources because their clients have this data, or in some cases, there’s turnkey asset management platforms that advisors are beginning to use. So we’ve engaged in relationships with them to deliver direct feeds to provide that data downstream to platforms.
Don: On the advisor ROI side, really trying to highlight the interoperability of our data. Not only can we serve the portfolio accounting use cases, but we can also really deliver advisor and investor alerts and insights from our data. Some examples might be, hey, there’s idle cash in this investors portfolio let’s let’s open an account. I can engage with that investor and open an account. Their risk exceeds the risk profile. That’s a discussion for diversification. They’ve changed their job or their income has changed. Hey, let’s update your savings and contributions. These types of insights and alerts can really help give the advisor more time to offer their client trusted, personalized advice in a way that a robo is unable to do so. The third was the workflow automation and onboarding. So investing in some tools, the capabilities there to help enterprises facilitate asset transfers and onboard clients quicker and excited about that as well.
Craig: Fantastic. Well done, man. You covered everything you did it, you killed it. Time is up. Can you tell us Don McHenry, senior product manager where people listening can find out more information about Morningstar ByAllAccounts?
Don: Certainly. So, we have a website. So I would start there, there’s information on how to contact us, certainly reach out to me, if you want on LinkedIn, I could route you to the right channel. I’m happy to answer any questions you have.
Craig: Awesome. Don, thanks so much for being here. Appreciate it.
Don: Absolutely. Craig, thanks for having me.