Banks have seen dramatic technology advancements across the business, particularly in payments. In this blog we discuss digital transformation in the financial services industry and five questions to consider when approaching your strategy, including important topics like competing for market share, open banking and more.
In recent years, priorities have shifted. Almost all banks are now focusing on upgrading their core systems’ infrastructure. In the previous ten years, improving customer experience was the top priority, largely because it was an area non-bank fintech competitors saw that traditional banks were the most vulnerable to disruption. The trend and investments have now shifted to the modernization of the underlying systems supporting these data-centric, front-end user experiences.
With the growth of requirements on financial services firms over the years, banks grew by adding features and functionality to their legacy infrastructures. This layering of ever-larger product catalogs onto older systems resulted in a jumble of interconnected modules and feeder systems that are costly to maintain and inflexible in terms of remediation. The resulting complexity is reliable, but it comes at a high cost and with a very short time-to-market for meeting new client requirements. One of the major trends today, particularly among larger multi-national banks, is to consolidate all of this into new cloud-based payment hubs that are agile and ready to compete in the new economy.
Some banks are much further along in this process than others. Those who are still lagging are often struggling to find their own “niche” in the new world, but these same banks are struggling with a long-term vision to match their desires, and they tend to overstretch where they want to get to, neglecting some basics along the way: namely, that they need the right baseline in the first place, which is why they are struggling. Many banks are still stuck in the past. Dabbling along the way is a good idea: try, quickly fail, learn, try the next one, and so on. But those catching up must be careful not to base their long-term goals on ideas generated by “dabbling,” and must master the fundamentals first.
The overarching goal is agility. It enables banks to reduce operational costs through more flexible technology and testing, as well as to prepare for the uncertainties of the post-COVID-19 road ahead. We live in a data culture and a digital world in which all signals that pass through the banking system have value for both clients and the bank itself. Payments are no longer just about processing widgets; the game has evolved, and data insights are now the primary focus in payments.
Banks are investing in real-time, as we can see all over the world. Many of them already have real-time capabilities or they are planning to launch them in the near future. Real-time is a catalyst that will affect how everything else works in the bank. More importantly, real-time enables the development of new digital payment layers and capabilities, such as Request-to-Pay services, in which many banks are investing. Once you’ve mastered the fundamentals, you can begin to layer on value-added services.
Banks are not thinking broadly enough about the opportunities that ISO standard machine-readable XML payments will bring them in serving their customers and transforming their business models. Big tech and fintech competitors in financial services are all in the data game, while banks view one of the most significant industry initiatives around data as a compliance activity rather than a fundamental development of their value proposition. This requires thinking beyond yesterday’s challenges, such as how to better reconcile payments and invoices, and more about how large sets of linked data can provide real insights and value. Part of this may involve thinking beyond the confines of traditional bank P&Ls, such as payment processing, and more about the value chain of activities in both commerce and family life. Artificial intelligence (AI) and machine learning (ML) for financial services allow banks to broaden how they serve clients in open banking economies.
Non-bank competitors recognize payments as merely a medium for gathering data signals and insights, rather than a standalone fee-based business. This is challenging for the traditional way in which banks have viewed their P&L growth since the dawning of transactions banking as a fee-generating product business in the 1980s. Beyond financial crime prevention, which is the first and best use case for data, banks have tremendous client franchises and domain experience in financial services for which data is the central element. Improved risk models based on real-time data and predictive analytics will be the first big step forward. Beyond that, the role of banks as data aggregators and creators of value-added services provides a tremendous and lucrative trajectory in an open banking economy.
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