CUs’ Deep Data Lakes

Everyone has heard comments like these:

“Data is your greatest asset.”

“If you don’t learn how to leverage your data, you’ll be left behind.”

“Your number one technology challenge is to get control over your data.”

There are several steps that must be taken in order to harness the full value of a credit union’s data:

1. Create a well-articulated business strategy. This will determine what a CU needs from its data, and indeed all its technology.
2. Build a technology strategy that responds to each point of the business strategy. Such a strategy will almost certainly be data-centric. It will include an architecture that provides access to all the CU’s data, as well as relevant data available from outside the CU. Elements may include:
   • a data lake, which is a collection of all the different sources of data without focusing on format and structure. This data may be a mix of structured and unstructured data.
   • a data integration platform that will validate, cleanse and transform data. This will make sure the data is usable by transactional systems and the data warehouse environment.
   • one or more data warehouses to provide a general structure to all related pieces of data.
   • data marts and analytical views of the CU’s data. These provide a window from the perspective of particular business functions (e.g. marketing, sales, finance, risk).
   • visualization tools that create functional views of the data. These tools allow the building of reports, dashboards, interactive web pages and insights to realize the data’s full value.
3. Bring in data experts to build out and execute on the detailed steps. It doesn’t make sense for a CU to build a data core competency. This is a good area to outsource. However, due diligence, strong contracts and rigorous vendor management are essential. Data is one of a CU’s most critical assets and must be protected accordingly.
4. Get help from your data experts to design new data-driven customer products. This might include using artificial intelligence to analyze the data. These products will differentiate the CU from its competition (both CU and non-CU). For example, use your customer’s data to build out cash management products that will allow a CU to meet the needs of larger commercial customers.
5. Continue to maintain, manage and leverage data as more becomes available. Create new views and visualizations as market conditions and customer needs change. Ideally, outsource this to the same firm that builds the data stack in the first place.

Credit unions should be getting more from their data—it can transform their businesses.

Graham Seel, a 30-year banking veteran, runs BankTech Consulting. He is an expert in commercial banking, and provides strategic insight and innovation consulting to smaller banks and credit unions. He also works with fintech firms, facilitating their partnerships with financial institutions.