The second quarter 2024 investment banking earnings season is nearing an end with strong numbers, an upbeat pitch, and less hesitation. What was described as “green shoots” in the first quarter is firmly an acceleration of revenue and deal visibility in the second. As Ted Pick (CEO) said on Morgan Stanley’s earnings call, “I think we’re in the early stages of a multiyear investment banking-led cycle…We are quite convicted on this call.”
The great debt issuance impasse during the Fed’s hiking cycle has begun to thaw, as banks have helped corporates push nearly a trillion dollars of refinancing in the first half of the year. Many of these issuances have been floating rate (perhaps in anticipation of an easing cycle). This was evinced by bumper earnings across ratings agencies such as Moody’s (MCO US). According to an analysis by the Financial Times (FT), “Revenues from debt underwriting at the [top] five banks were up more than 50 per cent from a year earlier to $3.7bn.”
Additionally, there were a few landmark merger deals that have slowly worked their way through the system, largely across mega cap buyers. While the private equity and credit space has begun to see a narrowing bid/ask (and “green shoots” of dealmaking activity), it still isn’t holding up to the pace witnessed mere quarters ago. The result of all this was Q2 YOY revenue growing at a very healthy clip (“Fiscal second-quarter investment-banking revenue jumped 59 percent in the three months through May” from Jefferies; “Investment banking surged 50 percent off of relatively meager levels a year ago” from JP Morgan; and “The five largest investment banks — Goldman Sachs, JPMorgan Chase, Morgan Stanley, Bank of America and Citigroup — together reported investment banking fees of $8.2bn in the second quarter, a 40 per cent increase from a year earlier and the highest since the start of 2022” as compiled by the FT).
This is an optimistic view. Are there any potential dark clouds? For one, the chart below furnished by LSEG and TRI demonstrates a reduction in M&A deal volume closing in H1 2024 compared to H1 2023, even as Q2 revenues increased. The decline was more pronounced in the US:
The source of this discrepancy is not only a H1 vs Q2 difference in comp but also banks demanding an increase in ancillary fees, irrespective of deals being completed. The goal for the banks is to protect themselves during a heightened period of antitrust uncertainty in the US. We’ve seen the FTC successfully halt several high-profile mergers, or at the very least inject risk and cost associated with getting a deal over the line.
ModuleQ’s Unprompted AI specifically caters to investment banks and private wealth managers, making investment banking trends a key area of our focus. This quarter’s earnings calls provided ample fodder for why AI is increasingly top of mind for banks. While the uptick in revenue has been a cause for celebration, efficiency ratios are still in some cases upside down. Increases in spend during the ballyhooed period of 2021 have still yet to be fully digested. This showed up in Jefferies earnings announcement, with Brian Friedman (President) noting that “revenue rose from a year earlier, so too did expenses, climbing to $1.43 billion from $1.02 billion.” This sent shares down post announcement, only for them to rally meaningfully in the month since.
David Solomon (CEO) emphasized the need to enhance productivity at Goldman Sachs (GS) through the use of AI. On the analyst call, he framed productivity as the spearpoint for AI adoption across the bank (emphasis added):
…we as most companies around the world are focused on how you can create [AI] use cases that increase your productivity. And if you think about our business as a professional service firm, a people business, where we have lots of very, very highly productive people creating tools that allow them to focus their productivity on things that advance their ability to serve clients or interact in markets is a very, very powerful tool.
We’re in wholehearted agreement!
Morgan Stanley pointed to Private Wealth Management as a central case for AI deployment. This is unsurprising given the bank’s focus and dominance in the private wealth space. As Sharon Yeshaya (CFO) noted on the call, “AI tools are helping advisers grow, and Wealth Management's partnership with institutional securities is increasing connectivity around our workplace offering.”
The use cases around AI for private wealth are a little bit more flexible than investment banking. Providing a market digest of the day’s moves to a client doesn’t need to be exactly correct, it needs to be engaging, concise, and well written. This seems like a ripe use case for the wordsmith capabilities of LLMs. This is a different story from investment banking, where precision tools need to be applied to ensure the accuracy of output.
Larger, more diversified banks like JP Morgan (JPM) are tackling AI from a variety of different angles, such as chat bots, customer service, back and middle-office, as well as compliance. With JPM’s investment banking revenue a mere tenth of the vast net interest margin it generates on deposits, it’s not surprising. JPM’s spend on technology dwarfs most banks. Mike Mayo (Wells Fargo banking analyst) questioned Jeremy Barnum (JPM’s CFO), effectively asking him where’s the AI beef (emphasis added):
at some point, if you're spending $17 billion a year to improve the company, if you're gaining share with digital banking, if you're automating the back office, if you're moving ahead with AI, if you're doing all these things that I think you say others aren't doing, why wouldn't those returns go higher over time? Or do you just assume you'll be competing those benefits away?
Perhaps as a middle ground to GS and JPM’s approach, we have Bank of America (BAC US), which is taking a path which ModuleQ preaches (information processing, insights delivery, focus on being proactive). Given their scale, they did cite an eye-popping price tag! Quoting Brian Moynihan (Chairman and CEO):
We also have increased our technology initiatives and expect to spend nearly $4 billion on technology initiatives this year. We have focused projects around our artificial intelligence enhancements with both clients and our teammates. A recent example of our use of AI is our Advisor and Client Insights tools. We've delivered more than 6 million insights year-to-date to our financial advisers, providing them proactive reason to engage with clients.
This perhaps is the crux of where we are with AI in banking. The initial “wide-eyed optimism” of GPTs (General Purpose Transformers) as a unicorn technology is giving way to an understanding that subject matter specific products will win the day. They will do so by leveraging these technologies to deliver the right productivity gains to the right business needs. This will vary across private wealth, investment banking, retail banking, and back-office functions. Finding those products will be crucial for driving return on investment.
At ModuleQ, we staked our reputation on this direction years ago. We are beginning to see the early signs of the investment banking industry coming around. As firms increasingly tinker with Generative AI solutions, they are starting to realize that they need products, not infrastructure to accompany their specific workflows. ModuleQ’s Unprompted AI is that product, designed specifically to drive productivity and revenue generation across investment bankers and private wealth managers.
We look forward to tracking these trends on the blog each quarter!