Along with banks’ own digital transformation initiatives, the foundational enabling industry infrastructures are also advancing to empower banks with new payment capabilities to deliver for customers.
For example, settlement schemes are expanding beyond traditional business hours in line with the 24/7 on-demand global economy. Thus, as the first step of its modernization, the Fed will make its National Settlement System (NSS) more available. This has allowed Nacha to add a third window to better meet the needs of West Coast financial institutions and consumers. As the Fed continues to evolve NSS, this will allow Nacha and TCH to explore Saturday processing hours and settlements.
Despite the absence of formal regulation and official mandates, we are starting to see glimpses of truly "open banking." The recent creation of Akoya and acquisitions of Plaid by Visa demonstrate an increasing focus on securing and managing third-party provider (TPP) access to consumer data.
More broadly, this is an indication that the financial industry is looking beyond transactional-revenue models towards data-driven approaches. For data to be truly valuable, however, it must be machine readable, consistently structured and standardized. The ISO 20022 financial messaging standard, which is being positioned for national adoption in the U.S., delivers on these requirements. The significance of this shift away from proprietary messaging formats should not be underestimated, so expect ongoing evolution as financial institutions work to meet the specific needs of their customers and solve implementation challenges.
On top of the enabling infrastructure, technological advancement can be carefully and selectively deployed to drive transformation.
Forget the "moonshot" use-cases. As the hype-cycle curve flattens, the practical and immediate value of artificial intelligence (AI) and machine learning (ML) solutions to augment people - yes, really - and existing processes is becoming apparent.
A recent panel at the BAFT Global Payments Conference explored how previously skeptical regulators are recognizing AI and ML tech as vital tools to ease compliance challenges. For example, helping optimize fraud detection to reduce damaging and costly false positives (where a legitimate transaction is flagged as fraudulent), or simplify complex regulatory filings.
Ensuring organizational flexibility and agility to seize the opportunities presented by AI and ML, and other key emerging technologies, should be central to any transformation strategy. But only if they truly add value.
The U.S. banking industry, much like the global financial services ecosystem, is undergoing sustained and significant change.
For some, the pace and scale of change will be too much. Financial institutions with simple and practical transformation strategies, however, are well-placed to get ahead of the competition to enable innovative new customer experiences, at lower costs and with reduced risk.
