The concept of open banking is often described as the free exchange of data with consumer consent, of course. The goal is to anticipate individual consumer needs by feeding AI and machine learning programs with buckets of data. Then, team up with third parties to offer a highly personalized banking experience with more relevant products and services. Sounds great!
While free flowing information is a nice idea, it has no bearing on the actual structure of banks. Much like hospitals are built to stop the free flow of protected health information (PHI), banks protect financial data. They are heavily regulated, anchored by legacy processes and infrastructure, and divided by firm departmental silos.
In fact, open banking is a 180 degree turn from how bank systems were designed in the past. It requires a complete reset on how things have always been done. Predictions indicate big problems for firms that can’t change. According to Gartner, 80% of traditional financial services firms will be made irrelevant by 2030 after being digitally eclipsed. That’s a staggering number of firms to dissolve, a prediction made before the novel coronavirus even existed.
When talking about the much needed digital transformation of banks, there’s a lot to cover. Let’s start with just one aspect—silos.
We’ve talked about how silos kill innovation. Unfortunately, they are are a natural byproduct of any organization. A deeper look into the root cause of issues stemming from silos will reveal a conflicted leadership team. It’s a leadership problem that can physically manifest into communication, data, and technology silos. Breaking them down must start from the top. Open banking may be the radical shift that affords executives an opportunity to change.
One dangerous side effect of silos is fractured communication in the organization. Many times, one part of the company has no idea what another part is doing, what their goals are, nor how their own projects either work to support or dismantle the priorities of others.
As mainframe experts, we work with many companies where decision makers do not know their mainframe guys. Similarly, the mainframe guys have no idea what direction executives plan to go. These days, all businesses are tech businesses and priorities often overlap departments.
For example, the role of Chief Risk Officer (CROs) has evolved a lot over the past 10 years. According to the 10th Annual EY/IIF Global Bank Risk Management Survey, the role of the CRO is shifting toward the management of nonfinancial risks given the significant improvement of financial risks. Notably, the risks associated with severe weather events, cybersecurity attacks, third-party outages, and legacy system failures are all on the minds of CROs.
In fact, 59% of CROs surveyed say that one of their top resiliency concerns is IT obsolescence and legacy systems in 2019, up from 39% percent the year before. Addressing this would require collaboration among CROs, CIOs, CISOs, CTOs and their reports.
Any fracturing of communication delays progress and makes it harder and more expensive to remedy. This is why all relevant parties must be brought into the conversation early in the process. Let mainframers scout relevant vendors and solutions early in the decision-making, versus expecting them to reverse engineer a decision with funds already allocated.
According to the 2020 World Retail Banking Report, most banks are not capitalizing on their data-rich advantages. In fact, their analysis found that only a small amount of banks could manage, as well as leverage, the best and most actionable datasets.
OPEN BANKING: Using Rich Data and Functionality
“Banks have several large data lakes in silos. The result is low interoperability that affects their ability to process the data to drive insights and use it to customize customer service” says Head of Group Strategy Innovation of a large bank in Israel. The culprit is, again, legacy systems that make data management tedious. The survey says that “for large banks encumbered by manual processes, pulling data from multiple channels and siloed business units can deflate information quality and restrict its full potential.”
Open banking, however, would necessitate that data were shared through standardized APIs. This would help drain out the data lakes and improve the quality of the data and confidence of data users across the organization.
For several years now, legacy technology has made it onto the list of things holding traditional banks back. This refers to decades of layered legacy IT systems and processes, disparate apps, and systems of record locked away on mainframes. For one thing, front end applications get makeovers, yet remain anchored by the cumbersome processes and IT systems left over from an era when physical checks were bundled together for mail. Despite pouring money into front end efforts, end-to-end customer experience stagnates.
Of course, it’s no surprise that banks focus on the front-end. Almost 60% of their profits come from origination, sales, distribution, and other customer facing activities. They earn a 22% return on equity (ROE) from these activities, versus only 6% from provision of balance sheet and fulfillment. However, there’s a tendency to choose short term benefits over a long-term vision. Less compatible business models layer onto existing systems. This leads to high maintenance costs and an ever growing complexity that affects customer satisfaction and operational excellence.
In fact, data shows that traditional banks dependent on legacy technology with functionalities divided into silos have an average customer acquisition cost of ~$200 versus $1-38 for new-age banks with data driven business models and automated processes.
According to the same retail banking report, modernization of a bank’s legacy IT infrastructure depends on a well-managed and prioritized cultural change.
In Singapore, DBS changed the culture of its legacy workforce during modernization efforts by establishing an innovation group that reported directly to the CIO. They created a startup culture throughout the enterprise and invested in reskilling and upskilling their legacy workforce, work environment, and project approach.
No doubt, this restructuring led to the dissolution of silos and the birth of collaboration groups. In order to break down silos in an organization, leadership has to have a dog in the fight. The good news is that the demand for technology that brings data and people together is growing. As open banking gains traction with consumers and banks alike, something will have to be done about silos.