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The top Democrats on congressional banking committees called on the Federal Reserve to reconsider its decision to approve Capital One Financial Corp.’s purchase of Discover Financial Services, saying it would inflict “serious harm” on consumers and the banking system. The decision sounds like the Fed “had predetermined it was going to approve the transaction and either ignored relevant facts or explained them away with baseless assertions copied and pasted from Capital One’s application,” Senator Elizabeth Warren and Representative Maxine Waters said in a letter sent to the Fed. “Treating the transaction as a traditional bank merger was deeply misguided,” the lawmakers wrote. “These are not two traditional banks — they are card giants.” Warren and Waters emphasized the Fed’s review failed to appropriately assess the competitive effects on the credit-card market and didn’t take into account the views of the Consumer Financial Protection Bureau and the Federal Deposit Insurance Corp. The Fed said in an order last month that it consulted with other regulatory agencies including the FDIC and CFPB. Capital One said the deal’s approval follows “an exhaustive, fact-based 14-month examination where legal and regulatory experts examined the deal’s competitive impact, financial stability considerations, community needs, and all other relevant factors.”

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Citigroup Inc. is ramping up lending to private equity and private credit groups, working to catch up with peers like JPMorgan Chase & Co. and Goldman Sachs Group Inc. after the bank spent years on the sidelines. The bank told investors it wants to get back into a lending business it retreated from several years ago. Citigroup in the past year returned to offering loans backed by the cash that investors pledge to funds, according to people familiar with the situation, granted anonymity to discuss private matters. As the bank pulled back on this kind of funding, known as subscription line financing, rivals moved to pick up more business. Goldman Sachs, JPMorgan and PNC Financial Services Group scooped up large amounts of the debt from First Republic Bank and Signature Bank, which were big providers of the revolving loans before they failed or were rescued in 2023. Citigroup’s return comes as CEO Jane Fraser pushes to overhaul the bank and boost profits by generating more fee-based revenue and forging ties with alternative asset managers. Last year, the lender hired Vis Raghavan, a rainmaker from rival JPMorgan, to run its global banking business. Subscription lines don’t generate high margins but they do help banks build relationships with asset managers, who may hire their lenders in the future to advise on acquisitions and underwrite junk bond sales. The lines have become extremely popular among fund managers, used by nearly 85% of buyout funds last year, up from just a quarter a decade ago, according to data from MSCI. Altogether, the sublines business is estimated to be roughly $900 billion globally, law firm Dechert LLP wrote last year. The financing is helpful when dealmaking picks up, but it also provides liquidity during a slowdown, which asset managers have faced for years as transactions dried up and some of their bets haven’t paid off. The threat of tighter standards under the previous White House led some large banks to exit capital-intensive lines of business. Regulators last year said they were going to ease rules known as Basel III Endgame, potentially freeing up space for banks to offer more financing. Fraser wants to lift Citigroup’s return on tangible common equity — a key measure of profitability — to 10% to 11% by the end of next year, bringing it more in line with its peers. Last quarter, that metric came in at 9.1%.  When private equity firms raise funds, their investors agree to provide cash to fund leveraged buyouts over time. But to access that money, managers have to make a “capital call.” Subscription lines are backed by the promises to meet those calls. Because investors have rarely defaulted on capital calls, subscription lines are seen as safe. Many banks have packaged them into securities, freeing up their balance sheets to make new loans.

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Banks have long used traditional AI and machine learning techniques for various functions, such as customer service bots and decision algorithms that provide a faster-than-human response to market swings. But modern generative AI is different from prior AI/ML methods, and it has its own strengths and weaknesses. Hari Gopalkrishnan, Bank of America’s chief information officer and head of retail, preferred, small business, and wealth technology, said generative AI is a new tool that offers new capabilities, rather than a replacement for prior AI efforts. “We have a four-layer framework that we think about with regards to AI,” Gopalkrishnan told.  The first layer is rules-based automation that takes actions based on specific conditions, like collecting and preserving data about a declined credit card transaction when one occurs. The second is analytical models, such as those used for fraud detection. The third layer is language classification, which Bank of America used to build Erica, a virtual financial assistant, in 2016. “Our journey of Erica started off with understanding language for the purposes of classification,” Gopalkrishnan said. But the company isn’t generating anything with Erica, he added: “We’re classifying customer questions into buckets of intents and using those intents to take customers to the right part of the app or website to help them serve themselves.” The fourth layer, of course, is generative AI. Given the history, it’d be reasonable to think banks would turn generative-AI tools into new chatbots that more or less serve as better versions of Bank of America’s Erica, or as autonomous financial advisors. But the most immediate changes instead came to internal processes and tools. Bank of America is pursuing similar applications, including a call center tool that saves customer associates’ time by transcribing customer conversations in real time, classifying the customer’s needs, and generating a summary for the agent. The decision to deploy generative AI internally first, rather than externally, was in part due to generative AI’s most notable weakness: hallucinations. Banks are wary of consumer-facing AI chatbots that could make similar errors about bank products and policies. Deploying generative AI internally lessens the concern. It’s not used to autonomously serve a bank’s customers and clients but to assist bank employees, who have the option to accept or reject its advice or assistance. Bank of America provides AI tools that can help relationship bankers prep.

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Koren Picariello, a Morgan Stanley managing director and its head of wealth management generative AI, said Morgan Stanley took a similar path. Throughout the 2010s, the company used machine learning for several purposes, like seeking investment opportunities that meet the needs and preferences of specific clients. Many of these techniques are still used. Morgan Stanley’s first major generative-AI tool, Morgan Stanley Assistant, was launched in September 2023 for employees such as financial advisors and support staff who help clients manage their money. Powered by OpenAI’s GPT-4, it was designed to give responses grounded in the company’s library of over 100,000 research reports and documents. The second tool, Morgan Stanley Debrief, was launched in June. It helps financial advisors create, review, and summarize notes from meetings with clients. “It’s kind of like having the most informed person at Morgan Stanley sitting next to you,” Picariello said. “Because any question you have, whether it was operational in nature or research in nature, what we’ve asked the model to do is source an answer to the user based on our internal content.” Picariello said Morgan  Stanley takes a similar approach to using generative AI while maintaining accuracy. The company’s AI-generated meeting summaries could be automatically shared with clients, but they’re not. Instead, financial advisors review them before they’re sent. Meanwhile, Morgan Stanley is concentrating on making the company’s AI tools easy to understand. “We’ve spent a lot of time thinking through the UX associated with these tools, to make them intuitive to use, and taking users through the process and cycle of working with generative AI,” Picariello said. “Much of the training is built into the workflow and the user experience.” For example, Morgan Stanley’s tools can advise employees on how to reframe or change a prompt to yield a better response.

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Cash App saw a marked slowdown in the first quarter, monthly transacting members using the digital wallet showed 0% year-over-year growth, remaining stagnant at 57 million users. Drill down a bit and the use of Cash App Card slowed, to 7% growth in monthly transacting active users slowed to 7% (at 25 million), where in previous quarters that growth rate had been in the mid-teens percentage points. Inflows have slowed to 8% growth to $76.8 billion in the first quarter, down from the 17% year on year growth that had been logged in the year ago first quarter. On an individual basis, the inflows come out to $1,355 per transacting active in the latest quarter, at 8% growth, also down from double-digit growth rates. The read across here is that at least for now, users are arguably being conservative about how much money they want to — or can — put to work with the digital wallet as entry point into the Block financial ecosystem. This performance is attributed to changing consumer behavior, including a shift in spending away from discretionary items like travel and media toward non-discretionary areas like groceries and gas. CEO Jack Dorsey said. “Tax refunds are an important seasonal driver of Cash App inflows. This year, we saw a pronounced shift in consumer behavior during the time period that we typically see the largest disbursements, late February and into March,” said Dorsey. “This coincided with inflows coming in below our expectations. During the quarter, non-discretionary Cash App Card spend in areas like grocery and gas was more resilient, while we saw a more pronounced impact to discretionary spending in areas like travel and media. We believe this consumer softness was a key driver of our forecast miss.”

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