AI or not, “data readiness” is the first step to putting bank data to work.
By Ryan Jackson
Every journey begins with a single step, and for bankers whose 2024 goals include exploring the transformative power of artificial intelligence, that first step is developing a data strategy.
Goldman Sachs Research estimated generative AI usage could drive a 7 percent increase in global GDP over a 10-year period, McKinsey estimates that generative AI has the potential to create $200-$340 billion in total value and an Accenture “analysis of operational efficiency indicates a potential to boost productivity by 22-30 percent” in banking due to generative AI.
These figures are staggering, and the value to banks and their customers is becoming clearer with every iteration and application, but AI is only as useful as the data that fuels it—the data that your bank safeguards on behalf of your customers.
At a recent event, Evident AI Symposium, David Rice, the global COO of commercial banking at HSBC, encapsulated the importance of data for banks: “Because of the open-source origin of many AI technologies, there is little competitive advantage in the underlying tech—the competitive advantage resides in your proprietary data. Data is such a valuable asset, it should be on your balance sheet.” (emphasis added).
To ensure your bank is “data-ready” to harness the efficiencies of these leaps in computing power, ask and answer these three questions:
1. Does my bank have a strong, transparent data governance policy? In this case, data governance refers to the overall management of data within your bank. Having a data governance policy ensures that the data is accurate, consistent and accessible to employees at the time it is necessary. One of the initial steps a bank can take to answer this question is to create an inventory of data assets, identifying what data is available, what system it lives on, how it can be accessed and by whom.
2. Does my bank have a strong, scalable data security and compliance policy? Ensuring robust access controls, compliance with data privacy regulations, and data protection (for example, data backup and resilience, disaster recovery and breach response protocols) are just a few of the initial items that should be determined.
3. What is my bank’s data quality process? Having accurate, consistent and reliable data is necessary before any use of the data can be undertaken. This process should apply to both internally generated and externally sourced data to validate and cleanse the data as necessary.
The answers to these three questions are foundational, but each policy should continuously be assessed, enhanced and built upon. Many banks use a mix of internal and external resources (and, yes, this includes some artificial intelligence products) to develop these data strategy elements. For example, as part of a broader digital transformation, Arvest Bank leveraged external consultants who worked with in-house technologists to build out new capabilities. Other banks find it more difficult to commit to a more aggressive data strategy. In a recent Wavestone 2024 Data and AI Leadership Executive Survey, nearly 78 percent of respondents listed “Culture/People/Process/Organization” as the principal challenge to becoming data-driven.
You might think that “my bank won’t be using artificial intelligence,” so you won’t need to create a data strategy. However, the benefits of a data strategy are much broader than the ability to leverage artificial intelligence solutions. Examples include generating insights about current customers, new product development, better board reporting, simpler data access for regulatory exams, more timely financial management and the ability to respond to new regulatory requirements.
Just about every single function within a bank can benefit from a robust data strategy, and that journey begins with clear answers to these three basic questions. With each element in place, banks can explore opportunities to leverage data to drive meaningful business outcomes, including through innovations available through the incredible power of artificial intelligence.
Did you find this article helpful or thought provoking? Would you be interested in joining ABA’s Enterprise Privacy and Data Governance Working Group, which can be a resource for ABA members in building their data strategy? Please reach out to [email protected] with any questions or to continue the discussion.
