Know Before You Grow: Applying Predictive Analytics to Your Branch Transformation Strategy

Predictive analytics is playing an increasingly larger role in credit union and community bank branching strategy, from understanding the network effect in an area and finding the locations that will give you the biggest impact to uncovering the product demand in your market. These artificial intelligence tools can give your financial institution a competitive edge and give you confidence in your decision-making process even as retail branching undergoes rapid changes.

Using predictive analytics is different from traditional approaches to branch location strategy because instead of assuming that historical trends will continue, it relies on insights from complex machine learning models to balance a vast number of attributes and data points to forecast how a market will change going forward.

We sat down with our market analysis partner, Steve Rymers, to discuss the impact that predictive analytics can have on branching strategy as well the work that goes into developing Momentum’s market studies. Steve is the Director of Applied Analytics for Financial Services at Precisely.

Watch the on-demand webinar “Know Before You Grow” with Steve Rymers and Bob Saunders.

CBC Federal Credit Union Camarillo BranchThe Branch Isn’t Dying, It’s Evolving

With basic transactions offloaded more and more to mobile applications, the core purpose of branches has fundamentally changed. Add to that major demographic and cultural shifts, changes in purchasing power and income between generations, and evolving product offerings, it’s easy to see how traditional ways of analyzing a market based on historical data begin to fall apart.

“Many organizations rely on historical data to set sales goals, but the thing you don’t get when you use historical data is understanding what opportunity you really have in the market,” said Steve Rymers.

Look at Amazon as an example. As Amazon gained a larger market share, analysts proclaimed that physical retail was dying. But today Amazon is pursuing an aggressive physical retail expansion. In their analysis of the retail landscape they came to understand that the digital revolution wasn’t replacing retail but rather triggering an evolution.

Predictive analytics give you the insights that you need to evolve alongside your market, insights that simply looking at historical trends can’t uncover.

🕮 To learn more about our process and kick off your branch transformation the right way, download our Quick Start Your Branch Transformation Guide! 🕮

What Data Goes In, and What Insights Come Out?

There is an absurd amount of data available, including  your own in-house data, industry data, census data, retail trend data, psychographic data… the list goes on. To manually model this data and extract insights would be impossible, but Precisely is able to use machine learning models that can learn from thousands of data points across millions or billions of records to understand the full picture.

The first step in building a market study is working with your team to gather data that helps the models understand your unique market, including your objectives and customer or member needs. With this data, Rymers can run the models and build two reports: one from a descriptive data perspective and one from an analytical perspective.

The descriptive perspective will give you a complete picture of the situation in your branch network today, while the analytical perspective will forecast future branch network performance and identify opportunities in the market.

“With this report, you’re going to understand which branches are likely to experience growth in deposits and loans in the future, which branches you might want to consider consolidating and the financial implication of consolidation, where other opportunities within their market exist, and the overall opportunity from those locations in terms of deposit and loan forecasts,” said Rymers.

These reports deliver much more relevant and accurate insights than out-of-the-box solutions, but there’s still one more ingredient that goes into an optimal market study.

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But I Know My Market, Where Does Human Intuition Come In?

“We’re not saying ‘open a branch in this intersection’ because intuitively it feels like the right thing to do, we’re backing it up with hard data and modeling to answer the question ‘what does it mean to put a branch at that particular intersection in terms of deposit, loan, and revenue forecasts?’,” said Rymers.

You know your market, and your intuition is important to the process. Predictive analytics gives you an understanding of your market and the potential that exists within it, but decisions are not made entirely by the machine.

“Where I’ve seen this process work the best over the years is when Momentum takes that homework piece of it, the piece that we do, and combines it with the institution’s local knowledge and intuition about their market, that’s where you tend to have the best results,” said Rymers.

The market studies that we at Momentum deliver in partnership with Precisely are the result of combining financial institution insights with our expertise and using it as a filter through which to understand the recommendations of the analytics platform.

Making More Informed Decisions

We see firsthand how advancements in market analysis are driving changes at the very core of the financial industry. As this technology becomes more accessible, there is a fundamental shift happening in the way consumers interact with credit unions and community banks. But the same technology driving this shift also empowers financial institutions to better understand and accommodate their member and customer needs.

“This is something we do every day, and it’s something we put a lot of thought and a lot of resources into. We keep refining or process as the market dynamics change and branch transformation continues, and we continue to use our data and experience to find ways to help people make better decisions. At the end of the day that’s really what it’s all about,” said Rymers.

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