Innovation | 03.31.21
For Legacy Banks, Digital Transformation Desires Overtake Inertia
Prior to the pandemic, when retail banks talked about developing a digital strategy, it was pretty much just that – talk.
But circumstances have a way of forcing action, even in the face of obstacles.
These can include having to unwind or synchronize with, and/or defer to legacy technology; and then there’s the whole minefield of sensitivities surrounding client data.
Nevertheless, proverbial “digital transformation” efforts are now well underway. And there seem to be no turning back – because banks are sitting on a goldmine of data.
Teams on missions, en masse, are seeking to more effectively tap into best-in-class technologies part of an upgrade cycle for the ages that is finally accelerating, industry members say.
"Large retail banks are being more proactive about leveraging the power of their data, in some cases to deliver better services to clients but also to completely change their business models," said Richard Allman, head of the Impact Strategy-Financial Services group at SparkBeyond, an AI-powered platform.
SparkBeyond specializes in mining massive amounts of data for hidden insights.
"The pandemic and rise of challenger banks and the whole marketplace generally – all of it has forced the banks hands to make these investments in systems and services that help them harness knowledge," Allman said.
Some executives do not even know where to even begin when it comes to AI, but the smartest ones always at least have a sense of some specifically desired outcome, as opposed to flailing about, using buzzwords and savvy-sounding terminology, but ultimately just a hammer in search of a nail, Allman said.
A Major Push To Leverage Data
Any digital transformation strategy must be tailored to an organization’s primary agenda, as in right now – the world having had changed yet on the cusp of re-opening – taking into consideration changing customer behavior and broader market conditions.
It is here that AI can be leveraged, Allman said.
"So much of AI is about leveraging the information hidden in the data both you and others hold to its full potential,” he said.
Data has the potential to answer many difficult questions, “such as ‘can we identify the vulnerable businesses across our balance sheet?’"
All Roads Lead to Cloud
For bank-based advisors and agents, digital transformation brings greater data needs.
Storage for large data sets drawn from client interactions and internal operations inevitably lead to cloud integrations.
Nearly three-fourths of the financial services IT leaders who participated in BDO’s 2020 Digital Transformation Survey said that they were already deploying cloud capabilities with cloud as the single-biggest segment in terms of anticipated near-term investment.
A Warm Wealth Manager Embrace
Meanwhile, in 2020, U.S. banks made more than 65 equity investments into fintech companies, according to a CB Insights study.
Wealth management focused technologies accounted for the second-largest client segment for these investments; deal count for wealth tech was the highest ever, this despite the near total shut down of activity during the early phase of the pandemic in the first quarter of last year.
This flurry of activity shows no sign of slowing, and suggests that digital transformation, for bank advisors, remains a key theme.
Brave New World
AI is not yet ready for mass adoption among Main Street advisors doing retirement planning, but it is one of the hottest topics for bank IT groups.
With venture capital flowing rapidly into the machine learning segment, several firms are rising to the forefront. For instance, Canadian AI developer Responsive has been one of the more talked-about firms in the space. Responsive’s product, reportedly operating in prototype form at a handful of firms, provides behavioral insight to optimize advisor relationships.
Allman said that the SparkBeyond platform has been increasingly a part of corporate development, including in the financial services sector, as the retail banking and advisory landscape is shifting fast.
Many companies are on the lookout for attractive merger targets beyond the "usual suspects."
The use of AI and machine learning and data science advances applies to banks and advisory practices looking for new capabilities, especially with respect to companies trying to completely re-invent themselves in the mold of successful digital-first challenger models; and, as such, are eying potential smaller bolt-on acquisitions in less well-known regional markets or adjacent/emerging fields of technology.
Some of these targets, Allman explained, could remain elusive or pretty much even invisible were it not for new advances in data science and screening, used by bank corporate development teams and their advisors/consultants, and which are able to search not just media articles and databases but rather an incredibly wide variety of websites.