Of Special Interest


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7th May 2019

SAS asks whether banks really need to choose between operations and innovation

Caroline Hermon, Head of Adoption of Artificial Intelligence and Machine Learning at SAS UK & Ireland, considers whether banks really need to choose between operations and innovation.

She says: “It’s no secret that challenger banks and Fintech companies are changing the banking industry as we know it. The main issue for today’s banking leaders is not that customers are switching to new high-street providers, such as Metro Bank, or to internet and telephone banking specialists like First Direct. The real threat is much more insidious – and much harder to combat.

“A wave of next-generation digital disruptors, such as Monzo Bank and Revolut, are launching completely new types of services that eat into the most profitable parts of traditional banks’ value chains. Agility, flexibility and an insatiable appetite for innovation are powering the rise of these disruptors. Many traditional banks claim to value these same qualities, yet only a handful of today’s market leaders practice what they preach in their digital strategy documents.

"Banks that can’t read the writing on the wall risk becoming obsolete and seeing their market share whittled away. With data-driven innovation speeding the industry towards a future of seamless, integrated, customer-focused services, it really is time to get real or get out of the race. Many traditional banks are so focused on keeping the lights on that they fail to execute their innovation goals. Keeping a bank running profitably while satisfying the regulators is no easy task, and transformation initiatives often get pushed down the priority list.

"Moreover, in the race to deliver transformation, many banks fall at the first hurdle. Their main competitive advantage – the rich data they possess about every aspect of their customers’ financial needs – is typically siloed in multiple legacy systems and managed by different departments. The task of consolidating data and establishing a central hub for business analytics is expensive, time-consuming and diverts valuable resources from run-the-bank activities.

"Resistance to change is another common barrier to innovation. Automation can be an unwelcome concept for decision-makers, especially those who manage large teams and have spent years building up expertise around the bank’s legacy systems and manual processes. But it doesn’t have to be this way.

"Banks that adopt a disruptor mindset recognise that machine learning and artificial intelligence are powerful tools. With the right approach, these banks can use the same technologies to both drive transformation initiatives and streamline day-to-day operations, creating a virtuous circle. Traditional banks may find transformation painful. But when they do embrace change, the benefits can be huge

"Analytics is key to transformation because it’s one of the unique competitive advantages that large, well-established banks have over their new rivals. With millions of customers who trust and value their services, these banks can accumulate a vast amount of incredibly rich data about customer behaviour.

"Since modern analytics techniques such as deep learning are extremely data-hungry, the banks with the most data will be able to build predictive models that are far more sophisticated and accurate than their competitors. This could prove to be a decisive advantage as AI initiatives begin to take centre stage in transforming customer service."