How Users of Data-driven Money Management Increase Profitability: A Mountain America Credit Union Case Study

Read the whole case study here.

Users of Data-driven Money Management Increase Savings By 20% Over Four Months

Financial institutions that offer data-driven money management are not only enabling visibility around one’s finances through aggregation, budgeting and alerts, but also building financially strong account holders who increase their savings rate.

Mountain America Credit Union recently compared the savings behavior of account holders using MX’s solution, branded as My Money Manager (MMM), with that of non-users. Mountain America wanted to know what would happen to a savings account when someone became a user of MMM and contrast that with a non-user over a four month period (August-November 2015). Users of MMM increased their savings rate by 18 percent in that time frame while non-users demonstrated a 2 percent decrease in savings — a difference of 20 percent. The analysis was conducted using a log-linear model with fixed effects, stripping away any reverse causation (i.e. people that are more likely to save are more likely to use MMM) and controlling for age of the user, amount of money in their checking account and amount of money borrowed in Mountain America loans. 

These results sounded almost too good to be true. What would happen if we looked at another four month time span, particularly one where account holders had holiday shopping bills to contend with? For December 2015-March 2016, Mountain America found that users of MMM increased their savings rate by 20.08%. This only served as further evidence that a statistically significant behavioral change was underway.

As we inspire a new generation of financially savvy super savers, there is a benefit for both financial institutions and their account holders. The financial institution benefits by attracting higher deposits that ease the balancing of the books, and the account holder more easily qualifies for quality loans, a win-win for both parties. Savings activity within a financial institution also carries an advantage over emerging third party apps. A savings app like Digit doesn’t pay customers interest on their money, extracting what would’ve been earned as a fee. In contrast, customers of institutions like Mountain America get to keep that interest. 

Satisfy Your Most Important Account Holders

Users of MMM do carry some unique attributes, as they’re younger, more affluent, have higher credit scores (by a margin of 53 points relative to the overall member base, meaning MMM users are prime candidates for the cross-selling of loan products), hold more accounts with Mountain America and generate more profitability. This is not a suggestion of causation — where a user would suddenly start accumulating more products and generate more profitability as they begin using MMM — but we do know that we are serving some of our most profitable customers when we roll out data-driven money management. 

Through data-driven money management Mountain America is satisfying users who hold the most products and are the most profitable for the institution. Mountain America is also investing in the future as millennials are the most likely of any generation to remain active users of MMM. As these customers mature in their financial lives Mountain America will be the hub of their financial activity. 

If you’d like to learn how you can help your account holders increase their savings, aggregate their accounts and become more profitable for your institution, talk to an MX representative or visit Contact us at (801) 669-5500 or

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Introducing FinSmart: Hyperpersonalized Advocacy for Account Holders

Brennan Knotts, Product Lead at MX, introduced FinSmart in our most recent webinar, which you can watch here. (Brennan's section starts at 26:15.)

We've also written out a slightly condensed and edited transcript below:


The MX Platform

At MX we build money management tools that empower the end user, which ultimately drives profitability for banks and credit unions. We’ve done this in the past with some traditional tools that you might recognize from the PFM era. But we’ve also built some digital money management tools that are completely new to the age of advanced analytics. What’s more, we’ve done it all on top of a platform that has the best external aggregation and industry-leading categorization accuracy. We take a lot of pride in that.

Today we’re going to see the fruits of building that powerful platform as we walk through a specific example of personalization. We’ll see some of the current functionality that MX offers to our clients, how we deliver it, and what it ultimately means for the end user.


Introducing FinSmart

We’re going to walk through a feature that we call FinSmart. FinSmart is all about personalization. How do we take all this information we have about the end user and deliver a message that keeps their interests in mind?

Let’s start with a user who we’ll call Ashley. Ashley logs into her mobile banking app and checks her balances. You can see that she can also deposit checks, pay her bills, and transfer money.

In addition, if you look at the bottom of the screen here you can see that she has a notification, a FinSmart notification.

She scrolls down and reads this high rate warning: “Your rate is 19% higher than your peers. That’s an extra $438 a year in interest.”

Now there’s a lot going on here. Let’s look at the first bit of data: “Your BankAmericard rate is 21.24%.” This is very specific to Ashley, and that’s important. FinSmart is a marketing tool, and the end game here for the financial institution is to drive new account holders. But it shouldn’t look like an ad.

Right out of the gate, Ashley can see that this message is specific to her because she knows she has a BankAmericard credit card. She can see right out of the gate that this message is specific to her.

So what? Why should Ashley care about this message? Because Epic Bank can save her $438 a year. Again, this part of the message is very specific to Ashley at this point in time. Which raises another question: Why is Ashley receiving this message? We’re not showing this message to all users since that wouldn’t be very targeted. What about Ashley’s situation allows us to know that this is the right message for Ashley at this time?

There are a few things going on in the background.

First, we’re listening for certain data points, and in this case we know that Ashley has an externally held credit card. She’s got this BankAmericard credit card, but she’s also banking at Epic Bank. And Epic Bank might even be her primary bank given that she’s opening their mobile app.

Second, we also know that this credit card has a higher interest rate than the rates that Epic Bank is currently offering.

Third, and perhaps mostly importantly, we know that Ashley is carrying a balance on this credit card from month to month. If users pay off their card every month, they probably don’t care what their interest rate is, and so with FinSmart they wouldn’t see this notification.


How We Get the Data

We’ve just looked at the first touchpoint with Ashley. We’ve let her know that we have this specific message for her. Now she can click into it and learn a little bit more about what is her scenario.

Again, this is designed and optimized not to look at all like an advertising experience. The idea with personalization here is to deliver a new feature to the end user. So Ashley can see here why you are delivering this message to her and how are you arriving at this idea that you can save her $438.

Let’s look at these different data points, starting with the current APR on the BankAmericard credit card. Where is MX getting this? The majority of the time we’re actually getting this directly through an aggregation feed. So Ashley doesn’t have to do anything. This rate is automatically pulled in. We’re automatically using this to tell Ashley something she may not know about her financial situation.

This next data point is the estimated interest cost. This is key in understanding how much money Ashley could save. We’re getting this from the transaction data. We’re able to look at Ashley’s past transaction history and see that every month she’s getting hit with a finance charge on her BankAmericard credit card, which tells us she’s carrying a balance. And the amount of that finance charge allows us to extrapolate and understand how much is she actually paying every year to carry a balance on that credit card.

Then we get to these next portion, which is where Epic Bank gets involved and tells the system a little bit about their offering so that Ashley can understand how Epic Bank can help her save money. In this case, Epic Bank tells us that their interest rate is 7%.

With these three data points we know how much money Ashley could potentially save if she transferred that balance to this lower rate credit card. And of course down at the bottom there, we have the Apply Now button. So what is the call to action? Ashley is seeing that there is an opportunity for her to save money here and she cares about that. $438 a year means a lot to her. What does she need to do next? This will lead her to the online application page. This is what the experience is like for an end user like Ashley.


Why the MX Platform Matters

What makes this possible? How are we able to deliver this today to the end user, and how could you potentially do this within your own organizations? The first key component here is the external account aggregation. This is what allows us to understand Ashley’s full financial picture. It allows us to understand that she has that BankAmericard credit card. Not only that, but we have specific data points about that, like that interest rate. Without that information, we really can’t tell her how Epic Bank might be able to save her money.

Another part here is what we at MX call the 3 C’s. The 3 C’s stand for cleansing, categorization, and classification. You might have all this data — it could even include external data — but you can’t get a lot of value out of it if it’s not clean. It might be inaccurate. You might not be able to understand that this is a transaction at a grocery store, while this is spending at a gas station. Those nuances matter if you’re going to build a personalized experience that the user is going to want to take action on. So we have to get all of that right and in this specific instance the transaction data we care most about is that finance charge. We see where Ashley is getting hit with different charges and what those mean about her past history.

The third part of this is dynamic targeting. This is what takes an experience that is lackluster and gives it a little wow. In this case, I mentioned that Ashley receives this notification and no one else does. And the timing is also critical. If Ashley paid off her credit card yesterday we don’t want to show her this message. So the system needs to automatically recognize that scenario and drop Ashley from the segment of users it will show this message to. Or if Ashley charges up her credit card a ton yesterday — maybe she bought a couch — then her real-world savings could possibly be a lot more than what we were presenting yesterday. In this case FinSmart knows how to update that information in real time. This happens every time Ashley comes in and looks at her finances. In fact, even when she doesn’t open up the app we’re still updating that information in the background.

Another key component of this is the dynamic messaging. Even if you get really good at understanding the user and pushing them a message at the right time, they’re going to zone out if you don’t make that message specific to them. They’re gonna ignore it the same way they ignore banner ads in the sidebar of their favorite news site. It’s not enough to say, “Yay, it’s Friday!” or “Happy Birthday!” since those are a little personalized, but not enough to catch your attention. “Yay, it’s Friday!” is not specific to Ashley. She’s going to tune that out almost immediately and move on. So it’s very important in the way we deliver this message that she gets right away that this message is specific to her.


Simple to Launch

We’ve looked at what the experience is like for the end user, but let’s be honest. If you’re going to take advantage of this functionality at your organization it needs to be easy for your different team members to use. You need tools that make it easy to configure the personalization with your own institution’s information, but you also need to track it easily. How are you justifying the time spent here, or the money invested in delivering personalization? If you can’t easily track it, you can’t justify it. It comes in danger of never getting off the ground or being dropped eventually.

Behind the scenes, there’s a data repository and a lot of hardware that processes all of the transaction information that’s coming in. We’re talking about a big data marketing platform that’s concerned with governance capabilities, security, data preparation, data maintenance, and more. And there’s Forrester research that says if you build a big data marketing platform in-house, you’re looking to spend between $25 and $50 million dollars just to get it off the ground — not to mention ongoing costs. You can implement FinSmart with a small fraction of that cost.

Now let’s look at the experience we’ve built for the marketers at your institution. What are they going to see when they’re using this functionality?

We call this tool Insight & Target. Insight lets you quickly track internal and external data and Target lets you create campaigns within minutes.

Target is where the FinSmart campaigns are configured.

You can see the low interest credit card savings campaign here.

Let's look at how to set up this campaign.

First, you select a product name. Second, you choose the URL you want them to visit to apply for the credit card you're offering. Third, you enter your interest rate. Fourth, you add a little eye candy — an image of that credit card to associate in a user's mind an image of what we’re talking about. Fifth, you preview and launch the campaign.

Just like that, people like Ashley will start seeing a hyperpersonalized notification about switching her credit card to Epic Bank.

Tracking is pulled in automatically. You’re going to be able to review this FinSmart campaign that you launched, and you’re going to be able to see how many users actually fit this campaign. How many have already had an opportunity to view it, and how many have actually clicked on it and had an opportunity to take action and hopefully apply for a credit card.

Again, the whole concept here is to make this super easy to use, and make this automatic. Once you set this up, no one needs to come in and manage the segment, or update the segment of users who are seeing this. All of that is happening automatically in the background, and it’s always on.

So far we've only focused on the credit card example, but there are many more.

You can look at mortgage scenarios where users have a mortgage with you, but may now qualify for a better rate since they've improved their credit score. Or maybe you can see that they have a mortgage with a competitor and again, maybe for the same reasons, maybe they have a higher rate than what they could potentially get today.

You can do the same thing with debt consolidation. Through external aggregation you can see users who have loads of debt and ask how can you help them consolidate that. Personalization makes it possible to do that without having to involve a lot of human resources. The software is going to handle that directly for you.

But even getting beyond just looking at the products and services you can offer the user, why should they engage with your platform beyond that? You can tell them things about their spending. In terms of providing personalization, at MX we have a philosophy where we don’t want to come in and lecture the end user. We don't say, "Stop spending money at coffee shops," for example. Instead we want to point out relevant data. We might say, "Your spending in this category is more than your peers’ spending in this category." We raise these interesting points for the end user to ponder so they can feel like they have a better pulse on their financial situation without having to sit down and do a deep dive with an Excel spreadsheet. The software does it for them automatically.

In conclusion, why is personalization really important right now? It really comes down to how you’re going to grow your financial institution. In the past, one great method to grow your financial institution was through acquisitions, especially when there were some distressed assets available at a low price you could grow through acquisition. In the past you could also grow through really aggressive traditional marketing — really pouring a lot of money into direct marketing campaigns or TV advertising. This didn’t necessarily yield the highest percentage conversions and could be really expensive for not really knowing what your results were going to be.

Today the traditional advertising model feels a little broken, which has led other industries and the financial industry to a more data-driven approach. And that’s what we’re talking about here with FinSmart and personalization. How can you use the data to retain more users? How can you use the data to encourage them to use more of your products and services? And also to win more of those held-away accounts that they’re currently banking with competitors.

So I’ll end on a quote that I think sums up a lot of what we’ve been talking about today in terms of mass personalization: “Mass personalization tied to a permission-based money movement is going to change this industry so dramatically that we will not recognize it within the next decade.” This comes from Bradley Leimer, Head of Innovation at Santander. It's one man’s opinion, but it also happens to be MX’s opinion. If what I just showed you is possible today, think of what’s possible within the next year, or two years. Let alone the next decade. I think it’s truly going to be remarkable and it’s going to completely change.

Picture this scenario: Users log into online banking to see what their balances are, and you tell them the action they can take to change their finances for the better. That's what the future holds.

MX Appears In Forrester's Vendor Landscape: Pick The Right Digital Money Management Technologies

MX Appears In Forrester's Vendor Landscape: Pick The Right Digital Money Management Technologies

MX appears for the first time as a featured vendor in Forrester's Vendor Landscape: Pick The Right Digital Money Management Technologies. The March 17 report advises FIs to deeply integrate money management capabilities into digital banking and look for a partner who understands their business objectives rather than just a technical fit.

The 5th Age of Banking: A Panel at the MX Fintech Festival

Last week at the Sundance Resort in Utah, MX held the 5th Fintech Festival, an exclusive event for the most innovative companies and thought leaders in financial services.  

To launch the discussions about financial services, Don MacDonald, CMO at MX, gave a presentation about the 5th Age of Banking. He demonstrated that since the early 1800s, banking has had four major inflections points and that we’re on the cusp of the 5th: The Age of Advanced Analytics. In this age, financial institutions must learn to use analytics to better serve their account holders on the digital front. You can read a summation of MacDonald’s thoughts in this piece for The Financial Brand.

MacDonald then introduced a panel of thought leaders with specialties spanning the industry. The panel consisted of Jim Marous, Owner & Publisher of the Digital Banking Report and Co-Publisher of The Financial Brand; Steve McLaughlin, Founder & Managing Partner at FT Partners; Pete Chiccino, Executive Vice President & Chief Information Officer at Bancorp; and Seth Wheeler, Guest Scholar at Brookings.

In addition, MacDonald polled attendees in real time to get a sense for what they thought about the state of the industry. In the first question, he asked whether attendees agreed that banking is at an inflection point. Here are the results:

fintech survey

This poll was followed by another, this one about the biggest hurdles facing the industry today:

fintech survey

Jim Marous noted that although many financial institutions say that banking is at a major inflection point and that digital transformation is their biggest hurdle, they don't act in accordance with those beliefs. "Many more resources are being dedicated to regulatory and less to digital transformation," he said. "This happens despite the knowledge that digital transformation is of prime importance."

Steve McLaughlin added that consumer demand is the central drive behind both the inflection point and the digital transformation. "People aren’t going to wait for the banks," he said. "They will find someone to help them get what they want." This change indicates that financial institutions must increasingly focus on growth and relationships, priorities reflected in our question about that topic:

fintech survey

Seth Wheeler commented on the complementary nature of growth and relationships, saying, "We’re in an era where most of the change will be consumer and small business friendly. Institutions will be forced to compete on delightful customer experience, transparency, low fees." According to Wheeler, it's by nurturing these relationships that growth will come. 

Jim Marous agreed that advocating for consumers will lead to growth, but he pointed out that the definition of advocacy is changing. "Advocacy is now being defined differently," he said. "It's no longer just about being friendly in a branch. Instead it's about knowing your account holders, looking out for them, and rewarding them. It also includes the ease of transaction and the user experience."

The attendees generally agreed that advocacy is critical going forward:

fintech survey

To best advocate for the end user, financial institutions must invent completely new strategies. "Throw away the old strategic plan," Pete Chiccino advised, "and stop acting like financial institutions have all along." Chiccino added that this requires "a blend of both partnering with fintech companies and knowing what you’re good at and owning that in house."

Most attendees agreed that the secret to success depends in part on partnering with fintech companies — especially when it comes to improving analytics.

fintech festival

Pete Chiccino said mastering analytics is pivotal to advocacy, saying, "We need to do a better job of understanding consumer data, building analytics around that, and marketing to the consumer based on what we know about them. Look at who’s hitting the market today and who’s worth billions of dollars, and it’s those companies that are best figuring out data analytics."

For example, we might look at Netflix and Uber, two companies that have mastered analytics to better serve their consumers and provide a seamless personalized experience. Panel attendees agreed that the future of banking will largely head in this direction:

fintech survey

Of course, there's something potentially disheartening about bankers acknowledging that the future of their industry may belong to new competitors who master analytics.

Fortunately, there's potential for financial institutions to pivot on their own terms, master analytics and advocacy, and own the future. As the panelists at the Fintech Festival outlined, it's the best hope for financial institutions going forward, and even though it requires hard work, it's certainly possible. For more on this topic and how financial institutions can keep their lead, read "The Future of Banking: Uber or Apple?"

FAQ: How Do You Measure Adoption And Engagement?

In 2012 research firm Celent reported that only 4 percent of online banking customers at the top 50 banks were active users of personal financial management (PFM). Selling you a product that no one will use is not a sustainable business model. MX believes that PFM is dead.

MX has pioneered the move into a new category, data-driven money management (DMM). DMM keeps your users coming back, whether analyzing their spending or cash flow, revising monthly budgets or charting progress toward a long term financial goal. We accomplish this with a world-class user interface, multi-source aggregation that ensures constant connectivity to one's financial data and superior cleansing and categorization of transactions, providing an accurate view of one's financial picture.


How does MX define and measure adoption? We identify the percentage of users created in MX out of total online banking users

In the past many FIs utilized a tabbed approach where users opted in but MX is driving more deployments where all users are pre-loaded, enabling them to immediately start using data-driven money management. This takes adoption off the table as a worry since everyone can immediately use DMM.

Mountain America Credit Union (MACU) experienced great success through a full integration, where all users were pre-loaded and an MX mini widget — sharing a user's spending breakdown — was integrated into the main online banking homepage to supercharge engagement. Tabbed PFM was almost hidden and siloed whereas data-driven money management is front and center.

The number of users seeing MACU's DMM solution increased by 600 percent in the move from a tabbed approach to a full integration. The number of external accounts being added daily more than doubled. As users add more external accounts there is a greater opportunity for MACU to cross-sell financial products, extending better offers to its members. 

MX has also produced 5x the historical PFM adoption rate — more than 40 percent adoption — by working with FI partners to craft creative marketing and customer education campaigns. 

Farmers Bank & Trust, which saw 50 percent adoption within a year, encouraged its employees to become active users of their DMM solution and share personal successes with customers to drive interest in the technology. Whether sharing stories about how they trimmed their dining expenses or paid off their student loans in a shorter time frame, employees created a deeper bond with customers as they explored the tool. The bank also ran a sweepstakes that incentivized customers to log in or add external accounts.

ATB, which had 46 percent of its online banking customers adopt within six months, promoted their tool as a free upgrade with a video explaining its functionality. Customers could then say yes or no to trying it but the bank continued to engage those who said no with messages like “Ever wonder how your spending adds up?” This drove customers back to the upgrade page with a better chance of adoption. When working with its partners, MX has always encouraged creative promotions that drive higher levels of adoption.


Banks commonly use a 60 or 90 day term when referring to active users and engagement. Here are some of the ways we measure engagement at MX:

  • What percentage of users are going into online banking and visiting the master widget (or opening up MoneyDesktop in a tab)?  
  • What percentage of users are aggregating external, or held away, accounts? This is a crucial piece for FIs wishing to view a customer's held away accounts — be it a mortgage, credit card or auto loan — and compete for that business.
  • Aggregated accounts per user. If a user on the MX platform has added at least one external account, we find that they average 5.2 accounts. This suggests that once you get users to aggregate, they don't just stop at one account and call it quits; it's easy to make the addition of external accounts a repeatable process. The more successful you are in getting your users to add accounts, the greater opportunity you'll have to win their business.
  • Sessions by product type, be it master widget, mobile or alerts widget.
  • Feature visits: This would include visits across accounts, transactions, spending, budgets, trends, debts, net worth and goals. FIs are eager to see which features are proving most helpful for their account holders in managing their financial lives.
  • Monthly active users, defined as users who've loaded a piece of MoneyDesktop, be it mobile app or widgets. Some FIs seek to measure engagement within the tighter monthly time frame vs using 60 or 90 day intervals.
  • Sessions per active user per month. While overall engagement levels are important, even a smaller number of power users who are hooked on DMM can speak to the success of your implementation. Javelin Strategy & Research notes that DMM is a "magnet for consumers who monitor and manage their finances vigilantly. That list is topped by Moneyhawks, who actively use online banking, mobile banking and pay bills through their primary FI." Moneyhawks represent the most profitable account holders for an FI; more than half of the consumers who use bank money management tools are Moneyhawks. While they only account for 13 percent of the population, Moneyhawks control a staggering 41 percent of deposits and a third of investable assets. 
  • Total users and total mobile users. FIs frequently compare online vs mobile usage as they seek to understand their customers' preferred channels and how they are trending over time.