Data and analytics

There are a number of methods that banks can best leverage the enormous amount and varied types of data through deep analysis.

 

Customer‘s best experiences anywhere become their expectation everywhere and that has impacted banking greatly as consumers can see the pizza delivered to their door and have personalized experiences with their ecommerce purchases.  Consumers then ask why they cannot have those same experiences with their banking interactions.  This means that banks must get much better at providing personalized products and experiences to their customers by better leveraging data and providing transparency and simplicity into everything they do. 

The data to enable such an experience sits everywhere, both inside and outside the bank and its race that has no end as experiences outside of banking will continue to improve and create demands inside of banking. 

Mitch Siegel and Julio Hernandez, in their capacities as advisors to an array of banks, suggest in this video a number of methods that banks can best leverage the enormous amount and varied types of data through deep analysis.   

Mitch Siegel

Mitch Siegel

Principal, Financial Services Strategy Leader, KPMG US

+1 404-222-3263
Julio J. Hernandez

Julio J. Hernandez

Global and U.S. Customer Advisory Lead, KPMG US

+1 404-222-3360

Video transcript



Mitch:

The sales and marketing aspect of a bank today is kind of further complicated by you have fewer people that are walking into branches or stores, and so the client is not always in front of you when you're trying to figure out what products and services they may need. Really, the ability to leverage data and generate insights of things like if I know what demographic you're a part of and I know sort of where you are on your life's journey, I can probably predict what types of products and services to offer you next. It's really getting the analytics down to a more personalized basis so that you can kind of understand where each person is along that life journey. Most of the way that the financial services industry has really looked at data has been from a regulatory perspective or really more about managing their financials. Now there's been a pivot point over the past 12 to 18 months around leveraging that data to be able to generate insights to provide more granular and personalized offers to customers, and that's really kind of changing the game.

One of the adages is that anyone's best experience becomes their new expectation. What we take from our interactions throughout the day when we order something online and it's delivered to us the next day, or the transparency of being able to see the pizza delivered to our door, those are the types of experiences that we're looking for out of our banking interactions as well.

Julio:

There is no way that you can do personalization without data and analytics. I've got to understand who you are. The ability to harness these analytics is really critically important to be able to personalize the experience, to be relevant, to give you the right offers, to treat you in the right way, to make sure that I've delivered against those expectations.

As we talked to clients about harnessing data and analytics there are a few things that we ask them to think about. The first is are you setting the right promise to your customers? What we mean by that is are you explaining to them how you're going to use their data? How you're going to collect their data? How you're going to take the insights from that data and actually apply it? That's the first thing, setting the right expectations with your customers about how you're going to use and harness data and analytics.

The second is really pulling all that data together and interrogating it in such a way that you can actually draw insights from it.

Then the third is actually taking those insights and doing something with them in the channel at the point of contact with the customer, both inbound when someone calls or someone walks into a branch, but outbound when you send a message to them via text, or you send a message to them via email, or you send a message to them via legacy snail mail.

All of these things together really are the way that you have to harness data analytics. Set the right expectations, put the right infrastructure into place, and interrogate the data, draw insights, and then activate on those insights.


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