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Want to Offer a Better Money Experience? Start With Better Data.

October 1, 2020|0 min read
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If there’s a company you enjoy using online, it’s almost certain they use data to optimize your experience. Whether it’s Netflix or Amazon or Spotify or Apple or any number of a hundred leading companies, leading companies use a data flywheel to power everything they do.

The data flywheel works like this: The more engaged users that one of these companies has, the more user data they acquire. This data helps these companies offer a more compelling experience, which in turn drives up the number of profitable users. The whole cycle is a flywheel that spins faster and faster with each turn, widening the gap between these companies and their competitors.

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Unfortunately, the experience people have with their money doesn’t always use this data flywheel behind the scenes. As a result, people sign into their online or mobile banking portal, only to be met with messy transaction descriptions that aren’t nearly as helpful as they could be — a frustrating experience. For instance, in an original survey of 1,000 U.S. consumers, we found that 71% say they experience this frustration at least yearly and 17% say they experience it at least once a month.

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This frustration results in complaints to your call center and a negative perception of your brand. Fixing this problem can result in major cost savings. In fact, when BECU, a credit union in the Northwest, introduced data enhancement into their mobile app, the credit union’s contact center experienced a steep reduction in telephone volume — from 8.8% total call volume growth in year one to 1.5% in year three as more and more people used the enhanced mobile app. 

In addition, messy transaction data does little to help you understand your customers. How can you make use of the data to empower people to be financially strong if the data isn’t clean? If you’re going to fix this problem, you’ll want transaction data that has been cleansed, categorized, and augmented.


When your users can’t understand a transaction description, they don’t get upset with the vendor or the card provider. They get upset with you. They dial in to your call center and drain your employee’s time. You can prevent this problem by cleaning all descriptions.


Your users are looking for help with their finances, and they don’t want to spend all their time tracking their spending habits. By adding automatic categorization to your transaction feeds, you help these account holders better manage their money while improving user loyalty, driving revenue growth, and paving the way for future technology.


When you properly classify transactions, you can see which of your users’ transactions are marked as bill pay, direct deposit, fees, and more — giving you the ability to more precisely target end users. For instance, you might target account holders who use bill pay with your competitors to use bill pay with you instead (amping up your bottom line and building value for your customers).

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Enhancing transactions this way — through cleansing, categorizing, and augmenting — sets the right foundation for not only a better mobile experience but also for whatever the future may bring. For instance, if you want to offer voice-assistance or AI-enabled features, you need clean data. (These features are useless without it.) 

To do things right, you have to lay the right foundation with data before you start dreaming of an advanced user experience. As Ron Shevlin, Managing Director of Fintech Research at Cornerstone Advisors, asks, “If you don't have good data and analytics capabilities, what good will an AI-first strategy do?”

To offer a better money experience and reap the rewards of a data flywheel, start with better data.

The Benefits of Enhanced Data

To see what enhanced data can provide for your customers, watch these scenarios. You'll see how voice assistants, effective marketing, and financial strength all start with clean data.

Voice Assistants

Effective Marketing

Financial Strength

See how MX can help you enhance your data.


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