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The Banker : Delivering next-generation banking

During the Covid-19 pandemic, banks have had to react quickly to changing conditions and digitally deliver products and services not only to customers but also provide the digital tools needed for staff do their jobs remotely. Is hyperautomation the answer?

The digital transformation trend started a few years ago in the banking industry, as banks saw an opportunity to improve customer experience and their competitiveness. And the Covid-19 pandemic certainly accelerated the digital trend. The pandemic has also highlighted where banks have been successful, as well as exposed their weaknesses.

Many banks have implemented robotic process automation (RPA) and seen some increase in efficiency, which has whetted their appetite for more emerging technologies, such as artificial intelligence (AI) and machine learning to increase the level of automation. Many that have embarked are on their journey to the cloud and have moved some of their workflows into the cloud, with much more still to shift.

Yet the digital transformation journey has not been a smooth one for many incumbents. These organisations face cultural challenges, in addition to those connected with legacy technologies. “Transformation doesn’t come for free, either in money terms or in terms of the elements of your culture that you have to discard,” says Jason Maude, chief technology advocate at UK challenger Starling Bank.

In addition to senior management saying what they want to achieve in a digital transformation programme, says Mr Maude, they should also be identifying what they are willing to give up. By changing the culture of a bank, “the technology will follow,” he adds. But trying to implement digital technologies without changing the culture will result in a “white elephant”.

While Starling Bank is a digital-first organisation and unencumbered with legacy technology, or indeed legacy culture, transformation for a bank of greater age and size requires a different approach to achieve the same ends, says Claire Dancy, head of ServiceNow product and technology data at Lloyds Banking Group. “You need to be mindful of the landscape in which you are operating,” she says. “You have to focus on risk in technology, because you are not fully in the cloud.”

In terms of driving that culture change, she explains that Lloyds Bank’s centre of excellence and innovation “pivots around colleagues and how we can unlock them to work on more exciting opportunities”.

Niall Bellabarba, fintech innovation specialist, Deutsche Bank, notes the dichotomy between scale and culture, arguing that cultural change does not happen overnight or without friction at a large bank. “A bank’s leadership has a big role to play, as do the partnerships that banks forge.” Deutsche Bank’s recent cloud and innovation partnership with Google Cloud represents a significant cultural change for the bank, he says. This cultural change overshadows the technological aspects of the partnership and goes to the heart of how the bank’s technology teams are structured and what they aim to achieve. “This is fundamental to digital transformation at a large entity like Deutsche Bank,” he adds.

One of the cultural challenges for larger institutions is the tendency to be “very inward-looking”, Mr Bellabarba says, yet most technological changes are “happening outside” a bank. Therefore, the concept of bringing in fresh ideas and technology from the outside is one of Deutsche Bank’s most important key performance indicators, he adds.

Beyond automation

The route for banks from where they are now technologically to a world of hyperautomation, which is the bringing together of technologies such as AI, advanced analytics and RPA to augment workers and automate processes, will not necessarily involve replacing the “human element” in all cases, says Mr Bellabarba. “In wealth management, for example, trust is fundamental and human contact in this area is geared towards engendering that. Hyperautomation has a business case in the sense that it reduces costs, but a bank has to be careful not to cut into the bone of a client relationship.”

This is not to say that certain elements of wealth management, such as advisory, exchange traded funds and portfolio construction, cannot be hyperautomated, but the relationship between the wealth manager and the client is “about emotions”, he adds. “If your portfolio falls by 15%, there are few computers that could cope with that human anguish and anxiety.”

A focus on hyperautomation makes sense given most banks have return on equity issues and a cost base that is too high, but “human contact is one of the aspects that I think should always be preserved”, concludes Mr Bellabarba.

Mr Maude agrees, saying the “big gains” in automation are where data is moved from one place to another, something machines can do far more easily, reliably and efficiently than a human being can. “I have heard a lot about organisations wanting to automate away their call centres and customer contact, but I don’t think it will work,” he says. “We shouldn’t ignore the emotional level on which money operates.”

To enhance customer experience, the “first touch” must be human contact, says Ms Dancy. She agrees with Mr Maude that back-office activities, such as the movement of data, are ideal to hyperautomate, and will result in enhanced customer experience. It is critical that the customer experience is considered and if they want a “first touch” to be human that should be enabled but the customer should be informed that their outcome has been dealt with in seconds.

Success metrics

Measuring the success of a hyperautomated environment involves a number of factors, says Keith Pearson, global head of financial services, go-to-market at ServiceNow. “The way I think about business cases in a bank involves the ‘six Cs’: cost, compliance, control, colleague experience, customer experience, and continuous improvement. A bank should be able to measure advances in any one of these to demonstrate success,” he says, adding that the definition of success will vary, depending on the priorities of the bank.

Determining the success, or value, of a hyperautomation project is also about transparency, says Ms Dancy. “There has to be a connection between the value you want to deliver and how long that will take to achieve. Transparency between the business line and the engineering/IT department, enabling them to have a mature conversation about what value is needed and what is prioritised, is critical to the delivery of that value,” she says.

Drawing on his background as a software engineer, Mr Maude points up the folly of measuring success based on project delivery timelines. Whenever a project plan is created in which software engineers are invited to comment, he says that one of two things will happen. Either a software engineer, when asked how long a project will take, will come up with a number that gives them enough time to cover themselves, or they won’t be experienced enough to lie. “Either case will result in bad outcomes, he says.

Generally, a “tug of war” between software engineers and managers over project timelines ensues. “As a software engineer of 12 years, I cannot tell you how long any particular software project will take to complete and nor do I care to,” says Mr Maude. “One of the reasonings behind a minimum viable product (MVP) approach is to get rid of the necessity of a project plan that has dates attached to it.”

The “illusion of control” where a number is pulled out of the air regarding how long a project will take to complete has to be abandoned, he adds.

The risk aversion of a heavily regulated industry forces a culture by which certainty of outcomes is a “good thing”, notes Mr Bellabarba. “However, certainty is a fallacy, which is why we have this bizarre situation of wanting estimates that inevitably are hit and miss.”

There are many different ways to measure success of a transformation project, he adds. These include some “banal” ones such as comparing the total cost of ownership of an infrastructure inhouse or in the cloud, and others, such as MVP approaches, where results are achieved on a smaller basis then scaled up into the cloud.

Deutsche Bank measures success through a variety of means, including the outcomes of hackathons, which Mr Bellabarba describes as powerful ways to propel the idea that change can come via small projects. “Smaller teams can move faster than larger project teams, where you are more likely to have hit and miss time estimates,” he says.

The end of a digital transformation journey is “when you realise there is no end”, says Mr Maude. “For Starling Bank, digital transformation is something that is happening all the time, every day. We are constantly changing the underlying code base that runs the bank, be that the core platform server code in the back end, or our public application programming interfaces, or our connections to other parts of the financial services landscape, our mobile apps, our web app, etc. Digitalisation is a constant fact of life.”

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