By Ajay John, Director of Data Intelligence, Apiture

Using data to guide business decisions should be a key part of every community bank or credit union’s digital transformation strategy. Your biggest differentiator can be how well you understand your users, how they interact with your institution and what are their core needs. This knowledge can help you improve engagement and create more personalized experiences that build loyalty.

Developing a data strategy may seem daunting, but it doesn’t have to be. To get started, consider the following to determine how your institution can gather, store, and analyze the data available to your financial institution.

Know your sources: As a financial institution, you have access to large amounts of data about your customers or members, including transactional information, details about how users spend their money, and interactions with primary and secondary financial institutions. Identifying available data sources is the first step in forming a complete picture of your customers or members; however, you should also realize valuable data doesn’t just come from internal sources. Partner solutions, industry analysis platforms and even government programs like census data can provide valuable information to augment the data you already have.

Manage what you store: Storing vast amounts of data can be challenging. Even with the right partners who can managing storing your data, the quality of your data is a critical factor in developing an effective data strategy. It’s important to assess data quality to identify gaps, inconsistencies, and errors that may impact data analysis. Once assessed, appropriate steps need to be taken to cleanse, normalize, and turn this data into a usable model for analytics. Further, necessary policies, procedures, and controls must be put in place to manage the collected data. Finally, it is important to establish who will be responsible for data management, who can access the data, and how the data will be secured.

Skillsets before toolsets: Data is only as valuable as the actionable insights you can glean from it. There are powerful analysis tools in the market today that can parse through your data and make determinations based on set parameters and goals. But often this is a garbage-in, garbage-out process. More than sophisticated tools, what you really need is a team of experienced data analysts, data engineers and machine learning engineers. Depending on your level of maturity with data and the use-cases in mind, you may even need esoteric skillsets like research scientists and quantitative analysts. These data professionals can use the right tools to explore your data, identify interesting correlations and make determinations based on well-researched parameters to return valuable insights about your users and operations.

Armed with these insights, financial institutions can use this knowledge in a wide variety of ways, such as new customer or member acquisition, cross-selling, retention initiatives, and more. For example, you can serve up financial offers to users at appropriate times or give your users targeted information to help make decisions about financial products or services. Or, by grouping customers or members into segments, you can market new products or services to a defined segment or even personalize the application based on a given segment’s needs.

Many community and regional banks and credit unions prefer to have another entity, such as a fintech or digital banking provider, handle these challenging aspects of building a data strategy and developing a team to execute it. Working with a fintech partner like Apiture can let financial institutions focus entirely on using the insights gained from their data to take the right actions. Data gives you the power to make your customer or member feel known or seen — and a strong data solution can be a useful tool to strengthen digital interactions at a time when users are moving away from face-to-face engagement at the branch. Contact us to learn more about building your financial institution’s data strategy.