Banks best Big Tech on trust, but not much else

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As some of Silicon Valley’s biggest companies launch retail banking products and projects, banks should acknowledge where they lag in the digital-first race, says Sonny Singh, senior vice president and general manager of the financial services global business unit at Oracle.

Banks maintain an edge over Big Tech in terms of customer trust, Singh says, but that will quickly erode as long as banks continue to attempt “piecemeal software development” in their current systems.

Trying to outmaneuver Big Tech in application development is an uphill battle for banks, he says, as the technology pros are simply better and faster at it.

Oracle, which sells an enterprise core platform to financial institutions, has struck a number of software deals with banks around the world. It faces fierce competition from several vendors including FIS and Fiserv.

In an interview with American Banker, Singh discusses where banks should focus their development efforts, how they can upgrade their technology more efficiently and the best way to break down silos in data sharing.

The following conversation has been edited for length and clarity.

What’s your take on the recent emergence of Big Tech, i.e. Google and others, in the banking space with their pilot projects? How do banks respond to the initiatives by some of your Silicon Valley peers?

SONNY SINGH: What’s occurring in banking among Big Tech is a natural evolution. Companies are always looking for ways to expand their offerings and evolve their business through disrupting incumbents. Big Tech is always focused on further monetizing their data relationships with customers, and banking is the next frontier after retail, media and travel.

The real question is, how will Big Tech manage the regulatory piece of what’s required? How do banks who are sitting on this mound of data make better use of it to retain relationships? Right now, banks still have the edge, and they also have the trust factor that comes with being a bank due to regulation.

But banks need to master data in order to hold this lead, build a collaborative ecosystem to take up and deploy innovation faster, and drive experience as a critical principle in product innovation — all these are done by Big Techs and fintechs very well in the current business models.

We hear so much about legacy technology holding back bank innovation. Are we at a point where tech stacks are no longer capable of being upgraded?

Definitely. Banks today are struggling to replace their tech stacks as they are now incredibly complex, due to years of piecemeal software development on antiquated platforms. This is further complicated by the fact that software programming talent developing and managing these platforms are out of the workforce and difficult to find. Also, the emergence of social, mobile-centric thinking in product design and mainstreaming of big data, machine learning and artificial intelligence as core principles in banking platforms make it more difficult for banks to survive on these platforms.

While a rip-and-replace model with a long-drawn-out transformation program is becoming less of an option, we see a progressive approach could work. As with today’s componentized, open and microservices-based architecture and movement toward the cloud, banks can undertake a fast outcome-driven transformation of their tech stacks and core banking platforms. With this approach, banks can choose the business area they want to transform, either based on revenue and profitability priorities, or new business models they want to bring, such as digital banking.

Prime examples from our customer base are Westpac in Australia, which is undertaking a homeownership-lending-focused transformation, and KeyBank in the U.S., which has undertaken a transformation of its digital experience followed by a personal lending transformation.

Alternative core providers are breaking into the U.S. market from Europe. There are banking industry firms investing in core provider startups. We’ve heard a lot of unhappiness among smaller financial institutions about their service. Can you discuss how the core banking industry can address this issue?

Core banking is a mission-critical application, and it requires robust product development, testing and implementation methodology to be successful. While like any other industry where new and disruptive thinking is welcome, banks need to choose their core banking technology partner based on R&D investment that the partner brings to the table currently and for future product innovation.

Customers in financial services are demanding high-touch service on demand, especially for certain important transactions like investments. Can financial institutions do both in a digital-first environment?

It is possible to do both, but a bank has to prioritize where it wants to deliver high-touch, on-demand services on its own versus segments where it can leverage technology innovation to deliver more high-volume but less personalized services.

A broad rule could be to keep high-revenue-generating, high-profitability areas within the bank and its owned channels, such as relationship management for high-net-worth wealth management. For more volume-driven opportunities such as the mass-affluent segment, it could deploy a robo-advisory capability or even externalize its system through open application programming interfaces and use third-party fintech innovation.

However, automation and a data-driven approach is needed for both, but segmentation will help retain and acquire customers at the same time while driving profitability.

Many executives talk about horizontal roles and breaking down silos when it comes to data sharing and use. What is the reality for institutions to achieve this? What’s worked best to ensure this collaboration takes form?

Banks need to take a foundational approach to how they turn data into an asset to use across functions. A core investment toward this is a common data model and analytical applications that source, curate and transform data for risk and finance data from multiple sources into a common standard for use across functions for insight and action.

With this approach, data can be used not only for specific immediate purposes like regulatory reporting and risk, but also reused to analyze profitability and decide next-best action by different offices within the bank's chief financial, marketing, compliance and revenue, cutting across silos.

A recent Accenture report suggested over 50% of bank staff roles can be automated. What are some of the emerging tools that Oracle sees playing a role in that transformation?

There are a number of emerging tools, we see. First among them is the broad set of machine learning and robotic process automation tools. For example, within financial compliance, automation is a way to make your staff more productive. Banks can use machine learning and robotic process automation to fetch reports from disparate sources, reducing false positives in transaction monitoring, giving anti-money-laundering investigators more time to focus on analysis instead of gathering data information. Interestingly, we are seeing that banks are using this to increase the overall effectiveness of their compliance departments at lower costs.

One digital-advice firm at our recent event said it will roll out the ability for its users to get a one-click mortgage. They are building these capabilities from scratch. Can banks match this? The CEO said that the best engineers don’t want to work at banks.

There is a popular view that banks are technology companies with a banking license, and it could be true for large banks like JPMorgan, BBVA and Citi. They could attract engineers, but that won’t be the case for medium to smaller banks. As the best engineers tend to move quickly and want to have a diverse portfolio across industries, it will be difficult for these banks to win the talent war. Digital-first application development needs to come from agile development, which is best done by financial technology providers with strong expertise in cloud and modern architecture. Banks should not focus on developing a core competency here but concentrate on product innovation and customer profitability and financial wellness.

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