Marla is an experienced senior marketing executive with an impressive track record in multi-unit retail, healthcare and financial sectors. She has extensive knowledge and expertise in the areas of Branding, Strategy, Management, Media Planning, Integrated & Digital Marketing Platforms and Public Relations.
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Steps to Build a Data-Driven and Data-Informed Financial Institution
The path to becoming a data-driven financial institution begins with a strong commitment to leveraging transaction data.
Brought to you by Alkami Technology, Inc.
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Big data continues to challenge technology and transform financial services as banks and credit unions navigate how to streamline and act on its intelligence. Big data, which often involves extremely large datasets that are too complex and voluminous for traditional data processing software to handle effectively, is generated at high velocity and can come from a variety of sources, including core data, financial transactions, credit processors, marketing activities and more.
Big data carries the following characteristics:
1. Volume: It involves massive amounts of volume that can range from terabytes to petabytes or even exabytes of data.
2. Variety: It comes in many forms — structured, semi-structured and unstructured and includes everything from text, images and videos to social media posts, emails and sensor data.
3. Velocity: Big data is generated at an incredibly fast pace and processing is often needed to keep up with the speed at which this data is created.
4. Veracity: The accuracy and reliability of big data can vary with large volumes of data coming from diverse sources.
5. Value: The ultimate goal of big data is to derive meaningful insights and, when properly analyzed, it can reveal patterns, trends and correlations that were previously unknown.
For financial institutions to manage all of the data penetrating their ecosystems, they must build a commitment to the outcomes of specific use cases and embrace the insights and intelligence this type of data can reveal. The transformation into a data-driven institution starts with transaction data as the catalyst.
Embedded in a financial institution’s infrastructure, and packed with rich behavioral patterns, merchant spend and intent indicators, transaction data can inform strategies related to business decisions, marketing campaigns, product gaps and innovation. A 2024 survey by the Center for Generational Kinetics found that digital banking Americans who are satisfied with a financial provider’s capabilities to use their data to make relevant product and transaction recommendations are most likely to sign up for other products at the company.
The Data-Informed Digital Banker
Transaction data is not only the cornerstone of a financial institutions data-driven strategy, but it also paves the way to digital maturity. A study of 215 banks and credit unions in the U.S. found that the most digitally mature financial institutions have a data modernization strategy and report up to twice the annual revenue growth as the least advanced. These financial institutions use data to support an array of business decisions related to combating the fluid interest rate market, product innovation and marketing tactics. By leveraging these data insights across all an organization’s channels, leaders can build data-informed digital banks — well-equipped to deliver personalized banking experiences at scale and adapt swiftly to changing consumer behaviors and economic conditions.
How Regional Community Financial Institutions (RCFIs) Can Build a Data-Driven Organization
The 2024 Alkami Telemetry Data Report emphasizes the requisite to build strategies around transaction data insights and analyses. Financial institutions can become data-informed digital banks by focusing on the following actions:
- Build out a data strategy: Set clear goals for your data strategy, aiming to enhance account holder experiences and boost revenue across all channels.
- Partner with technology vendors: Partners that provide technology solutions can leverage artificial intelligence (AI) and advanced analytics. Recent research that surveyed financial institutions showed that 89% said the first steps in AI adoption will focus on finding insights in large datasets, opening the door to a more data-driven organization.
- Invest in transaction enrichment and a data infrastructure: The collection, analysis and utilization of data has to be streamlined, while account holder transactions should be cleansed and tagged through transaction enrichment. A trusted industry partner can align with the financial institution on this initiative to create easy data analysis.
- Use transaction data and enhance the tech stack: Invest in digital tools where the insights from transaction data can be made actionable, delivering individualized interactions.
- Cascade a culture of data: Foster a culture of data as a foundational transformation that includes collective collaboration and training from all levels within the organization.
Building a data-centric culture, investing in the right technology and partnering with experts will empower institutions to turn the big data phenomenon into actionable strategies and will best position banks and credit unions to have authority in the market and outpace their competitors.