A recent piece by Cornerstone Advisors’ Sam Kilmer caught our attention – for a number of reasons.
First, the obvious reason – He talks in part about the recent Q2 acquisition of PrecisionLender, which most of you already know about. (If not, here’s more detail.)
But then Kilmer takes a step back from the deal (as well as nCino’s purchase of Visible Equity) and asks the all-important “So What?” question. That’s when things really piqued our interest.
In particular, he highlights four aspects that the Q2/PrecisionLender and nCino/Visible Equity have in common. You can read them all in the piece, but for the purposes of our blog, I’d like to look a little closer at his first point - which really resonates with our view of the current state of commercial banking.
“Most of the banks and credit unions we speak with are happy with the Visible Equity and PrecisionLender platforms. That may not sound revolutionary, but it really is extraordinary in an analytics world filled with displeasure … (Analytics) is the least future-ready area of the bank and the only one that’s NOT been improving.”
Ignoring the Siren Song
Obviously, we view PrecisionLender as more than just analytics, but I think I see where he’s coming from when it comes to the displeasure part of this. It connects to a point our CEO Carl Ryden made back when we wrote, Earn It: Building Your Bank's Brand One Relationship at a Time. He called it “the siren song of one more report.”
The gist of Carl’s argument was this: Banks do lots of analysis. That’s not the problem. The issue is what they’re analyzing and when they’re delivering that analysis. Too often, the data specialists at the bank are using analytics to generate reports that are delivered after the fact, in a way that essentially says, “Here’s what you did wrong.”
Gee, thanks. No wonder bankers’ eyes start to twitch when management talks about rolling out a new analytics system. To them it feels like another system that’s effectively looking over their shoulder – making their job harder and more stressful.
So how can analytics work its way back into favor at banks? By delivering information that says, “Here’s what you can do.” Note the tense change, English majors – from past to present. When your bank delivers analysis to their bankers in real-time, now you’re using analytics as a tool to help your bankers do their jobs better.
Impactful > Trivial
The other key is to deliver impactful, relevant information, not trivia. Too often analytics can fall in love with the analysis, and not the end product.
Indulge us with a sports analogy. Baseball may be the most analytics driven of the major sports. It’s awash in data, but a lot of it is trivia: “Oakland slugger Khris Davis finished with a .247 batting average four seasons in a row.” Neat, but not useful.
But the data that tells managers how often a batter hits a certain type of pitch to a certain part of the field? That’s impactful. And it leads to immediate action – teams now move defenders to different parts of the field from pitch to pitch.
What does timely, impactful analytics information look like in a bank? Something like the messages that Andi®, PrecisionLender’s digital coach, provides to bankers when they’re structuring deals.
We use our system to illustrate the point, but there are many, many other ways this can be applied at your bank to turn analytics from annoying Big Brother to trusted value generator.
A Better Financial Experience
Kilmer wrote that data-driven platforms with happy customers is an “extraordinary” occurrence in banking. We fully understand the sentiment. We walk into those same rooms, filled with frustrated skeptics. We've found that the problem isn't the data, or even the interface. Both have improved by leaps and bounds in most systems. It’s about whether that data can be used to tell a banker something valuable, that helps them do their job more effectively.
That’s the holy grail of user experience - what Q2 calls “Financial Experience, or FinX” - in the banking world. It’s where the winners and losers will be decided in the world of banking analytics.
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