Investment Banking Trends: CXOs on the Roles of AI, CRM, and Data Science

“Junior banker retention” is all you have to say to get a crowd of banking executives talking.

That’s how our panel dinner started off a few weeks ago, when we invited a small group of senior operations leaders at top banks to discuss key investment banking trends and challenges.

However, retention itself is an old problem, and we weren’t there to talk about conventional fixes like salary increases. Our goal was to explore some of the new and innovative changes organizations are making to enable their bankers.

As a first order of business, many shared insights into the hard work of re-balancing their workforce and location strategies post pandemic. Everyone was pretty much in agreement here. Hybrid is table stakes, expand beyond New York, partner with strategic vendors. It’s not about if you adopt new benefits but how to do it right.

What drew a more heated discussion was data and technology. While the potential upside is huge, the resistance is arguably more substantial. Large banking institutions are not exactly known for agile processes and rapid system-wide change. In pockets, AI is powering quants to scale their simulations, and virtual data rooms are augmenting M&A due diligence, but what about the day-to-day grind of banking?

Below are highlights from the exchange on investment banking trends and challenges. As expected, there was a healthy dose of push and pull between those who introduce innovation and those responsible for banker adoption.

Technology and the limits of its impact

“Last year, we closed 25% more deals, and we didn’t have more people,” according to a strategic innovation leader. While you can’t guarantee 25% growth YoY, he’s a firm believer that technology needs to play a central role in driving productivity. The bank had implemented new workflow automations and leveraged AI to auto tag documents in the last year, and he’s seen an increase in efficiency. “Even if it’s just 5 minutes out of 20, marginal savings add up” and make a huge difference at scale.

The counter is, “technology will take you part of the way.” Without business adoption, technology has no impact. There’s really no arguing against this. However, there are a million ways to address adoption. Should you start with company culture or product design? The most influential senior banker or UI?

“You can’t spend enough on change management.” Innovation agents need massive amounts of effort to fight inertia. They need teams who have credibility in the industry to run domain-specific processes and technologies, all dedicated to the cause. There’s a lot of internal marketing to do, and it’s worth your time to find a banker who will champion the product. At the end of the day, there are more opportunities to pursue and deals to close. Bankers are already overworked, so you better have a good reason for them to listen to you.

Beyond CRM

“If you don’t have good data, that’s just bad. You’ve got to get over that.”

CRM implementation is one of the most common investment banking trends we've seen in the last few years, but many continue to face challenges with filling in the data. Luckily, remote work has helped some banks jumpstart good data habits. Suddenly, more calls were being recorded, and bankers needed to collaborate digitally. However, just because the data is there doesn’t mean it’s getting used.

“CRM can’t be an island. It can be a golden starting source, but it needs to have tentacles into your other processes and systems.” Reaching the end user where they are is key to any technology’s success. Whether manual or automated, bankers work in an ecosystem of processes and workflows. Process reengineering should try to minimize change on the user end and streamline data transfers behind the scenes.

An integrated ecosystem requires a certain level of “standardizing without standardizing.” Banking is still a personality-driven business, and people are particular about their reports. The question is, how do you deliver information that appeals to idiosyncrasies – in templates?

Templates can also help support teams be proactive about pulling out the most relevant insights. “More often than not, junior bankers don’t know what they need,” and one of the ways to address this is by streaming intel on a defined set of external triggers versus on direct request. There are platforms that do this, but you have to walk a fine line. Too many golden nuggets of information can quickly feel like loads of unwanted information shoved into your face.

Even with a central database for customer insights, and proactive intel, you may not be able to eliminate duplicate effort without picking up the phone. When you get 40 separate requests in two days from the same junior banker, its time for a conversation.

The role of data scientists

All bankers want is to know where the next big deal is. But if that’s all you ask of your data scientists, they will always come up short.

“You cannot use AI to predict the next deal, that’s not possible.”

Yet, there’s so much value data scientists can add in moving you closer to that win. They can provide 360 insights and gap analyses to improve client engagements. They can run models on customer insights and uncover patterns across interactions.

There are endless ways to transform data, and “it’s virtually impossible for data scientists to crack the code on their own.” Without business context, technologists and data scientists often solve problems that bankers don’t have.

One panelist is addressing this issue with a rotational program. Bankers in the program spend time in the data science org to work through systematic challenges together. The face-to-face teamwork is paying off. Data scientists get a better understanding of the questions bankers have, and bankers become more familiar with what data scientists are capable of.

The reality is that innovation is still limited to pockets of the organization for most investment banks. Data science support teams are small, maybe a dozen or two. This lags far behind other industries and even other financial institutions like hedge funds. “If we had 150 data scientists, we would integrate a data scientist into every deal team.”

For now, banks are still in the business of proving the role of technology and data science. The challenge doesn’t stop at showing RoI for pilots. New challenges arise as you deploy new tools, manage dependencies, and promote adoption.

We’re all still figuring out how to integrate and institutionalize data-driven ecosystems.

That’s why we are continuing our CXO panel series around Investment Banking trends this fall. Stay tuned for discussion highlights from London and Toronto, and let us know if you have questions for the panel to address.

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Susan Xie
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