What do Peek, Loungebuddy and Bandsintown have in common, and, to amplify the riddle, what do they have to do with banking?

All three iOS apps do something that the vast majority of banking mobile applications don’t: leverage other data streams on the mobile device. They also – and here is the important point – do not require any action on the part of the user in order to do so. Banking mobile applications had better start doing this soon.

Peek, which launched today, is a calendar application; Loungebuddy is a relatively new app to find airport lounges; and Bandsintown, which has been around for a couple of years, helps music lovers find live concerts. And you are wondering, where is he going with this?

Let’s start with Peek. It is Apple-elegant. It sleekly (and that is an understatement) creates a calendar environment that is just light years ahead of the default Apple calendar. And that’s the thing: it leverages the data in the Apple calendar (or technically within the iOS) to create a more elegant experience without the user needing to do anything beyond giving the app permission to do so. I am not aware of a banking app that uses data beyond the “current location” data to help consumers find branches. The upshot: there is other data on the smartphone that banks need to tap. For example, why couldn’t a mobile banking app use the Apple calendar data to facilitate customer service or to mark time-related banking activities? It should. Bank apps don’t.

Loungebuddy, meanwhile, works in a straightforward manner. Its process is to have the user identify: 1) airline flying; 2) departing airport; and 3) arriving airport. But the app does something very subtle. Rather than require the user to enter the departing airport, it prepopulates local choices. In other words, I am located in New York today – when I went to enter my departing airport, Loungebuddy had prepopulated with JFK, Newark Airport, and LaGuardia Airport. You might say, so what? But there is something deeper going on here. Instead of spitting back the data, the app is making an educated guess: If JJ is in New York today, most likely he is leaving from one of the major New York airports. To parallel that to banking, if the user of a mobile app clicks on the “locate a branch” function, the app should calculate the closest branch to the user, not just give pins on a map. Doing so offers some “thinking” for the users, and that’s what I am getting at: apps are going to have to increasingly think for users.

Finally, we come to Bandsintown, which takes the application of iOS data evidenced in Loungebuddy to another level. As indicated above, Bandsintown helps music enthusiasts find local concerts. How? It utilizes two databases, not just one: location and the user’s iTunes music catalogue on the smartphone. And it does this with no action required on the part of the user. The user simply opens the phone and the data is crossreferenced to generate a list of local concerts. In other words, Bandsintown is making two assumptions, not just one. First, it is assuming that if you want to go to a concert, you want to go to a concert near your current location. That’s not a wildly revolutionary assumption, I know. Second, Bandsintown assumes that if you want to go to a concert, you’ll want to go a concert featuring music you like – and your iTunes song lineup will most likely reflect the music you like. By combining these two things, Bandsintown is creating a powerful data-driven service based on likely (albeit not absolute) assumptions.

This is, in my opinion, the goal for mobile banking. There is data constantly flowing through the mobile device that has financial implications: credit to cover dinner at the Katy Perry concert; the need for mortgage information after visiting an open house for a French colonial; the ability to offer more home insurance when a big storm is poised to roll in. All these ideas (and I am sure really smart people can think of vastly more use cases) rely on multiple data streams and would be most effective when the user does not have to “tell” the financial institution about them. It is not enough to just tap the data, it is to intuit services based on the data. This, my friends, is no riddle.