Enhanced Bank Transaction Data: The Underrated Key to Digital Banking

In our ongoing original consumer research published via our ultimate guides, we discovered that 95% of people say they use a digital channel, with 55% saying they primarily use a mobile banking app and 40% saying they primarily use their bank’s website. 

In short, it’s clear that the future of banking is digital.

So how do financial services companies build the ideal digital banking experience?

It all hinges on getting clean, categorized, and augmented bank transaction data.

What Is Bank Transaction Data?

Bank transaction data is all the purchases each consumer makes every day — both outflows and inflows. As such, the scale of bank transaction data is enormous. 

Why Does Bank Transaction Data Matter to Financial Services Companies?

Bank transaction data shows real-world decisions. Unlike survey data, where someone could say one thing and do another, bank transaction data shows what people actually do. As such, bank transaction data has enormous value, both for the consumer and for companies looking to help them.

Of course, in order for the data to be helpful, it can’t be messy and indecipherable, showing random strings such as “OGIV89 --Wal- 987 Visa.” Messy data like this erodes trust, clogs up your call center with requests for clarity, and burdens your operations teams.

Enhanced Bank Transaction Data Is the Future of Banking

Enhanced transaction data sets you up for success with whatever technology comes next, whether it be voice assistants, apps on a watch or glasses, chatbots, or the next iteration of virtual reality. In every instance, your customers want to easily and quickly access information about their transactions — something they can’t do if the data they see is indecipherable, such as “OGIV89 --Wal- 987 Visa.” You could offer the most intelligent chatbot in the world, and it wouldn’t be much use to your customers if it fed them data like that.

That’s why enhanced data is such an essential part of the money experience. Data is the oil of the digital age, empowering everything else people do online.

And yet, according to our survey of 1,000 random U.S. consumers in our Ultimate Guide to the Money Experience, consumers currently feel frustrated by unclear transcription descriptions, with 71% of consumers saying it’s a frustration they feel at least yearly and 17% saying it happens at least once a month.

How can you offer an ideal money experience if your customers are consistently frustrated like this?

The answer hinges on your ability to follow best practices around cleansing, categorizing, and augmenting your data. Here are critical questions to ask yourself as you look to offer enhanced data:

Clean Bank Transaction Data

• Do your customers immediately know which vendor a transaction description refers to?
• Can they see a logo of the vendor to help them quickly make the association between their purchase and the vendor more?
• Can they visualize the vendors they purchase from in a way that’s simple for them to understand their trends?

Categorize Bank Transaction Data

• Do your customers have the ability to see their transactions automatically categorized?
• If they do, are transactions categorized as “miscellaneous,” or are the categories actually helpful?
• Can they see their spending patterns by category, and is the process at least 95% accurate?

Augment Bank Transaction Data

• Can you easily tell how much money your customers are sending to your competitors from their accounts with you via bill pay, credit cards, a loan, etc.?
• Do you give them location data in a way that’s easily accessible?
• Do they have the ability to see transaction type (bill pay, point of sale, online payment, subscription, etc.)?

Enhancing bank transaction data in this way — through cleansing, categorizing, and augmenting — is critical to your future growth. 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?” You have to lay the right foundation with data before you start dreaming of an advanced user experience.

The Risk of Bad Data

It’s worth noting that a small difference in accuracy can have an enormous impact on the return of investment. For instance, if categorization accuracy rates are 95% and a consumer has 840 transactions per year, then they’ll have 42 indecipherable transactions. If that results in two calls they have to make per year, it’ll cost you roughly $8 per individual annually (at an average cost of $4 per call). That sounds insignificant, but at a scale of 100,000 customers, it can add up to a cost of $840,000 per year. By contrast, having an accuracy rate of 99% cuts that rate dramatically, resulting in a far higher return on investment.

The truth is that enhancing data is not only the right thing to do by your customers. It’s also a sound business investment. As Michelle Evans, Forbes contributor, writes, “The ability to make sense of the avalanche of data will be what distinguishes the winners from the losers in the next decade.”