5 ways the World Economic Forum says Artificial intelligence is changing banking
Artificial intelligence has been a focus of discussions at the World Economic Forum’s annual meeting in Davos, Switzerland, over the past few years, so the organization decided to partner with Deloitte Consulting on a study that sought to “cut through the sensationalism surrounding AI” and offer helpful insights for business leaders and policymakers.
“Financial institutions around the world are making large-scale investments in AI, while governments and regulators seek to grapple with the significant uncertainties and growing public trepidation as AI becomes central to the fabric of institutions and markets,” according to a new report the forum published with Deloitte, “The New Physics of Financial Services.”
The two organizations surveyed financial services executives about AI and held half-day workshops around the world, including one at Davos, on the topic over the past year. They came to several conclusions about how AI is reshaping the financial industry, including the five noted here.
Banks will need to use AI to create competitive products
“As products and services become more easily comparable and therefore commoditized, it’s not sufficient any more to compete on delivering credit quickly and at a good price, which have been the historic competitive levers” for banks, said Rob Galaski, Deloitte Global Banking and Capital Marketing Consulting leader and one of the authors of the report.
For example, to keep its auto loan business relevant, Royal Bank of Canada is piloting a forecasting tool for car dealers to predict demand for vehicle purchases based on customer data.
Such information could be more valuable to the dealers than any banking product, Galaski said.
“We think that is an exemplar of how we see the industry changing overall,” he said. “Much of the AI debate coming into our work was around replacing humans and doing existing things better or faster. But that take on AI dramatically underestimates the impact. The very way we go about conducting business can be redesigned using AI.”
Companies that don’t have scale or AI-based customization will get squeezed out
The report hypothesizes that midtier financial services providers will struggle in this AI-based competition.
“If you’re the scale player in the offering of a financial product or service and you’re able to offer it at lowest cost, that will continue to be a sustainable position,” said R. Jesse McWaters, financial innovation lead at the World Economic Forum and another author of the report. “Otherwise, you’re going to need to offer some level of customization. Simply having a fairly low-cost but relatively undifferentiated product will no longer be a sustainable competitive strategy.”
Banks that try to play a jack-of-all-trades role are likely to suffer, he said. Those that become more specialized in products or customers served will succeed.
Adaptability will be all-important in this AI-fueled competitive landscape
“The proper delineation between who wins and who loses comes down to the degree of adaptability rather than the size of the company,” Galaski said. “The natural advantage does go to scale players. But if you’re scaled but have low adaptability, you will lose. If you have don’t have scale but have a high degree of adaptability, there are a number of modular service providers you can plug into your infrastructure to gain the perception or appearance of scale.”
Several technologies are reaching maturity and needful for banks to adjust, he said: blockchain, AI, quantum computing and cloud computing.
“They are expensive to implement, they require massive scales of data, they require expertise to operate them, so naturally speaking, larger companies should be able to have an advantage” in implementing them, Galaski said. “But the larger companies have shown themselves to be less adaptable in many cases than smaller companies.”
Large-scale players that develop an adaptable mindset will be the winners in the future, he said.
AI will add usefulness to open banking
The report cites Lloyds Banking Group as a poster child for open banking.
“Lloyds Banking Group’s transformation investment of $4.1 billion a year is positioning the company to combine banking and insurance services, along with new API-enabled propositions, to compete in the digital world,” the report said, referring to application programming interfaces. “This is supplemented with a major focus on AI capabilities to transform the customer proposition and business operations. The aim is to be an ecosystem provider and a ‘trusted guardian of data’ in the age of many providers.”
Galaski pointed out that in a post-open-banking environment, aggregators or platforms will sit on top of financial account data feeds and provide a place where customers can suck in all their data from the different financial institutions they deal with.
“The competitive basis in the platform aggregator world will be, who can analyze the most data on behalf of that customer and provide personalized, tailored recommendations, either on price, suitability, or availability or any number of different factors?” he said. “Because that model is built primarily on fast and efficient, comparable outcomes, AI will be the core driver of that.”
AI will fuel ‘self-driving finance’
The combination of open banking and AI will put customers in a “self-directed mindset” going forward, Galaski said. Those that can provide the most AI-based self-help will have a strong competitive advantage.
The ability to tap into both financial and nonfinancial data will be important here, McWaters said.
“In exactly the same way that you wouldn’t expect an adviser to be able to make good financial decisions for you knowing only the contents of your personal balance sheet, an AI requires an understanding of preferences, locations and behaviors that exist well outside the realm of purely payments and deposits,” McWaters said. “So if you want to have recommendations that are truly individualized, that’s going to require the input of data from outside of the historical data of traditional financial institutions.”
The result could be automation of many people’s financial lives, which the report described as “self-driving finance.”
An example of this, according to Galaski, is Clarity Money, a former fintech app that is being integrated into Goldman Sachs’ Marcus consumer banking offering.
Products like Clarity Money provide advice to consumers on day-to-day financial activities like paying bills or deciding how much to save.
“The thesis of Clarity is it aims to automate day-to-day cash decisions for consumers, including everything from canceling unused subscriptions to financing credit cards,” Galaski said. “To do that specifically for one person requires a degree of intelligence that is more suited to AI than a simple rules engine.”
Another example is Citi, which recently launched a mobile app that allows customers to link their accounts across providers to deliver a 360-degree view of their financial lives across all banks and providers.