Celent’s parent company, Oliver Wyman, recently published a paper on the transformation of banking using AI (The AI Revolution in Banking). It is a good read that provides insights to how AI trailblazers are effecting systemwide adoption of AI across the enterprise.
One of the four pillars is “Transform the technology behind the data brain.” Quoting from the underlying report:
“At its very core, AI is about data. A successful AI transformation necessitates having high quality “raw material” available at the right time. This, in turn, means a bank must have the right data infrastructure in place. It may be necessary to move to the cloud to enable real-time AI applications; it will almost certainly entail establishing the necessary data governance, stewardship, and data quality frameworks.” (Oliver Wyman, September 2022)
I could not agree more. Despite the advances in data management within banking, much of the investment has been driven by defensive strategies to meet regulatory demands to improve data quality and lineage. If anything, the rapid pace of investment in new solutions has complicated the “data mess” many banks are digging out from. New payment systems, virtual accounts solutions, and open banking further complicate the data landscape. If a data strategy is not implemented holistically, AI at scale will be difficult to achieve.
In corporate banking, the same data asset is used for operational execution, regulatory reporting, business analytics, and for the creation of new solutions. This asset must be controlled and structured, yet also accessible and malleable. Acknowledging these different perspectives, needs, priorities, and qualities of the same data asset is a first step in forming a data road map. Unfortunately, competitive tension between these drivers can slow transaction banks from delivering an effective data and AI program. If the characteristics are viewed independently, or developed without regard to the other needs, execution of a data strategy will stumble and get stuck in a rut.
If there is lack of agreement on scope and expectations, and/or investment is reallocated away on a regular basis, laggard banks will fall further behind the curve. In addition to the aspirational paper from Oliver Wyman, here at Celent we have produced two research reports that can help you on this journey.
Oceans of Data: Recognize the Perils in Corporate Banking Data Transformation (August 2022) describes the technical and cultural challenges in moving the data strategy forward. Banks will recognize the symptoms that can cause a data strategy to go awry.
A companion report, Navigating to Value with Corporate Banking Data: Recommendations for Managing Data Strategies (August 2022) provides tangible ways to rethink the value of data and how to drive a data platform forward.
