Maximizing Your Data with Sandeep Balan

Hey, GonzoBankers. Tony DeSanctis back with another hot take. Wanted to talk a little bit about data.

I think one of the misconceptions out there is we don’t have enough data in our financial institutions. I think the reality is we have plenty of data. What we don’t have is a strategy on how to make the most out of it.

So I’ve asked Sandeep to join us. He leads our technology and data advisory practice here at Cornerstone.

Sandeep, there are five key pillars or key elements to data that you want to let folks think about as they’re building out their data strategy, because there’s plenty of data, right? No one’s lacking for data.

Yeah, absolutely. So when you think about the key areas that banks or credit unions want to focus on, it starts with some of the foundational elements, right? Data strategy, data governance, being able to curate and calculate the fields that they need to actually make sense out of the data.

So that’s the number one foundation.

Okay.

The number two foundation around this is identifying opportunities from that data set. So once you have those different silos of data brought together, how do you identify what’s materially important for you as a financial institution?

Actionable insights, right?

Actionable insights that are going to align with your strategic vision, what you want to do for your members or your customers. What are the key opportunities that you want to focus on in order to take those actions?

Sure.

So that leads us to actually the third pillar, which is, what are those growth actions? What are those key initiatives that they want to focus on based on the data that they have and based on the strategic vision that they have?

Sure.

So once they have gone through those first three steps, it leads into what we call results and feedback.

As you go through that journey and you start taking actionable steps, you’re going to learn and institutionalize that knowledge as to what is working for you.

Right.

Once you identify what is working for you, you step back and think, are we ready to go from predictive models to prescriptive models, where you can bring in additional data from outside data sets?

Sure.

To be able to make those actions more reliable.

Sure.

You are confident in the outcomes, the promotions and campaign precision.

Yeah, yeah. Better precision, more effective campaigns that actually deliver better results for you.

Right.

Nice.

And then finally, I like to think about that leading into what I call a data branch or a digital data branch.

Okay.

So now you have a subset within the organization where data becomes critical, and you are able to take that to all of your channels, your mobile channel, your internet banking channel, your data warehouse may be integrated.

Sure.

Your marketing platforms are integrated. So now you’re able to create that data branch, which is actually one of the best growth drivers within financial institutions.

So those five key pillars are how we tend to think about how you want to execute on your data journey. And it all starts with that key data strategy and the use cases that are going to help you get there. So that’s the number one foundational step.

Excellent. So really, just to recap all of that, I think the punchline here is our clients aren’t typically lacking for data. They just don’t know what to do with all the data that they have.

I’ve heard some people call it data exhaust, right? There’s so much data that it becomes almost a byproduct of your functions. But having that strategy in place is important.

I think the other key thing you mentioned is that iterative learning that comes from the data, because just having the data, if you’re not creating those actionable insights, isn’t enough. Being able to identify the precision that’s necessary in today’s environment to grow your business is so much more refined, and making the most out of that data is an important part of that.

So let us know in the comments, what’s your data strategy? Do you just have a bunch of data that you don’t know what to do with? How are you leveraging it? How are you getting that level of precision and targeting into your customer and member base to get the most out of those relationships and deliver on customer expectations, which continue to be more and more specific based on individual usage and preferences?

Let us know in the comments.