How to be an intelligent bank?

Someone said to me this week: what do we need to do to be an intelligent bank?

It seems like a simple question, but the answer is incredibly complex. After all, the first step is to be a bank with digital at its core. This is something I’ve written about for decades, but the big theme is to have a bank born for mobile access from day one. That’s a difficult ask for banks born for branches a century or more ago.

The second step is then to question how digital is the bank? Is the bank fully committed to open banking API access? Has the bank consolidated and refurbished its back-office systems to be totally open and digitally online? There are a lot more questions here but the biggest one, for me, is that you cannot be an intelligent bank with dumb data, something also blogged about a lot.

The third step is then building the intelligence layer. It begins with the data the bank currently stores about customers. I just wrote the other day about my awful experience with AMEX. Here is a financial firm that’s dumb. Intelligence is collecting and collating all data about a customer over time and, not just that, it is analysing that data for predictive service. This will be the biggest battleground in banking and finance over the next decade

Predictive services.

We have predictive markets but where are the companies delivering predictive services, and what are they?

My first experience of a predictive service was with Bank of America in the 1990s who were tracking customer data for indicators of a house move, so that they could offer a mortgage. What were the indicators? Regular trips to a new location based upon visits to gas stations, meals in a new place on a regular basis, visits to DIY stores in a new place and similar.

It’s a little bit of guesswork but, with today’s AI, is far more accurate.

Another example of predictive service can be seen with Monzo. The challenger bank told me a story about analysing the use of their cards and realising that they could offer discounts on the underground and trains, based upon people’s payments behaviours.

In this instance, you would get a note in the app prompting you with the fact that the bank noticed you were buying a ticket every day on the train – don’t you know you could save 25% if you bought a season ticket?

Now, most people didn’t buy the season ticket because they never had enough money in their account to buy one, but Monzo’s offer was to swipe and you get the season ticket. What you’re actually getting is a loan.

From the customer perspective however, Monzo has just saved me 25% on my daily commute. Thank you, bank.

And this, for me, is the core of predictive financial services where the customer feels you are their friend. Their thank you bank.

So, as we move into the intelligence era, it’s all about financial services that are predictive, personal, intimate and aimed to assist, advise and support.

But then, I always caveat this advice with the story of Target.