Bank Execs: Covid’s Tech Challenges Handed ‘Big Wins’ to Automation, AI

The technical challenges of operating major financial institutions during the Covid-19 outbreak have driven uptake of automation and other new technologies such as artificial intelligence at hitherto unprecedented rates, according to speakers on a virtual panel at WatersTechnology’s Innovation Exchange event this week.

The sheer undertaking of moving between 90% and 95% of financial sector employees across all business functions and locations worldwide—from front-office sales and trading roles to overseas staff in offshore delivery centers—to remote working almost overnight was itself a validation and a driver of the need for greater automation, said Stuart Gurr, group chief information officer for the Asia-Pacific region at Deutsche Bank.

“This in itself qualifies as a wholesale digital transformation that had to be delivered in a matter of days, not weeks or years. At the outset, I’m sure there were a lot of concerns about what this would mean for productivity, delivery timeframes, and technology adoption, but many of those concerns turned out to be unfounded. On the contrary, we’ve seen an acceleration of technology for automation in certain areas,” Gurr said—unsurprisingly, much of it around remote working, collaboration, and client communication.

Covid has also highlighted the value of digital and electronic channels that allow clients to transact and communicate with financial firms, which has translated into stronger partnerships between companies’ technology arms and other parts of their business, Gurr said. “That’s been a ‘big win’ that I’ve seen over the last six months.”

Vincent Kilcoyne, EVP of product management at SmartStream Technologies, said that without increased automation, Covid would have placed greater strain on the vendor’s ability to serve customers.

“We use automation all across out business… [and] Covid has absolutely driven the desire within the community to increase levels of automation. We saw a spike in client activity, and the only way to insulate yourself against that is to automate, to retain customer service levels and reduce error rates at a time when the practical challenges of everyone working remotely means that the time taken to resolve problems has increased,” Kilcoyne said.

Gurr noted a similar challenge to resolving issues quickly under Covid. “We may have lost some agility in terms of problem solving,” he says. “I think those desk-to-desk chats and water-cooler moments when you have a quick question and you can get a quick answer are much harder to recreate remotely. That’s one concern—that it can take longer to solve challenges.”

AI Sees Sentiment Shift For the Better

Another area of technology development that has benefited from Covid’s impact is artificial intelligence, which has gained greater acceptance as the pandemic has exposed the limitations of “human” intelligence when faced with an infection that poses serious risks to people but leaves computers unscathed.

“Covid-19 is the flame that will light the blue touch paper of artificial intelligence,” said Janet Adams, head of strategic projects and performance, SME at TSB Bank.

“Public opinion towards robotics and AI has gone through a reversal. Before Covid-19, there was a lot of fear that AI and robotics would steal our jobs. But now… people see AI and robotics as solutions that keep us safe and enable us to live our lives,” Adams said. “Covid-19 has also shown us that the human system isn’t 100% resilient, and automation and AI solutions have a really important part to play in our financial systems.”

She also noted that when necessity dictated, firms adopted new technologies quickly, which will contribute to further acceptance even sooner. “Necessity is the mother of invention. Across the world, we’ve seen technology changes that could have taken months or years previously getting turned around in a couple of days… Put all of this together… and it’s a major uplift for robotics and AI systems. So I think this is going to rapidly speed up the evolution of these technologies.”

However, a key factor to successfully adopting “extremely data-hungry” technologies such as AI and machine learning is having access to relevant data and the expertise to incorporate it, as well as setting realistic ambitions for what you want the technologies to achieve, and having the patience to realize those ambitions, Kilcoyne said. “Am I looking for 2% or 20%? A big win on day one is not realistic. It’s about access to data, access to expertise, and having a realistic outcome,” he said.