It's a common presumption that all banks are cutting back on headcount and automating what they can. In actual fact, if you're an 'A-grade' banker in advisory, most firms will do what ever they can to get you on board. Great, but what if you're not of that standard? Prepare to work alongside artificial intelligence (AI), coders, and data analytics teams as banks assemble a makeshift A-team.
Don Raftery, managing director and the head of the commercial and corporate banking practice at Greenwich Associates, predicts that there's a classic war for talent in banking – not just rainmaking investment bankers, but also commercial and corporate bankers, including talented product specialists and relationship managers.
“We’re in this incredible period of uncertainty with so much change happening, from tax reform and deregulation to rising interest rates, that business owners are having to deal with, and in times of complexity they turn to their financial partners for advice,” Raftery said. “These bankers are needing to look at a large series of different metrics and information in order to deliver the right types of insights, industry information on the sector that the company is in, its peer group, its financials, the potential impact of rising interest rates, cross-border tax rates, looking at their cash flow cycle and what the company’s immediate, near-term and long-term goals are.
“If the client’s business has a global component, the banker needs to know what’s happening with FX rates,” he said. “The list goes on.”
The report states that highly skilled advisers able to help clients through uncertain times with complex solutions will become more difficult to find and retain. It's not just about making deals, most banks are now expecting their front office employees to become more consultative. They are looking for experienced bankers able to consistently execute on being a trusted adviser to clients’ senior management teams – while also selling the full suite of products and services, says Raftery.
“That’s not to say there aren’t plenty of bankers available, but there are not enough who are highly skilled advisors and solutions sellers,” Raftery said. “Clearly these sought-after candidates are high-level VPs and above, ones that are seasoned enough to play an advisory role."
One factor contributing to that skills gap is the fact that most banks stopped their banker training programs during the financial crisis. When the programs resumed, they were generally much smaller in scope and scale, said Greenwich.
“We talk to the heads of banks, and they say to get somebody who’s really good and who can interface with business owners and executives and create advisory relationships, to do it effectively and efficiently, it takes at least 10 years to get really good at it – it takes a long time,” Raftery said.
“Looking at that, plus the gap in training for several years, and the fact that more institutions taking a more advisory approach to consulting with clients and have their banker talent be more advisory in nature, there are more banks fighting for fewer and fewer people who have the right skills.”
For the banks that are not able to hire top people are bringing in client-facing front-office bankers from the next tier down. Many of these firms are looking to adopt new technologies such as AI and machine learning to support these relationship management teams and try to outmaneuver competitors in that way.
The Greenwich report found that next-generation advisory models being developed by leading banks will leverage AI interfaces that assess a large number of complex data sets, including econometrics, industry trends, peer analyses, foreign and domestic tax rates, bank fees, FX, interest rates, cash-flow cycles/seasonality, liquidity needs and costs of capital. These data sets are mapped against the client’s current, short-, medium- and long-term needs to create customized advice, per the report.
“The pressing question is, how can banks not only source the right talent but perhaps augment it with AI specialists and algorithms that crunch those numbers and make sense of some of that data more efficiently,” Raftery said. “The idea is to create leverage for bankers so they don’t have to do all the legwork themselves – that way you can try to take B-level talent and leverage AI algorithms to deliver A-level solutions and advice.”
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