Finance

Tesla cut prices for its electric cars in China by more than BYD did for its flagship Han sedan, according to analysis from U.S.-based firm JL Warren Capital.
The Han sells in a similar price range as Tesla’s cars — above 200,000 yuan ($28,000).
Most of BYD’s many other cars cost much less.

BYD’s Han electric car, pictured here at the 2021 Shanghai auto show, is one of the most popular new energy vehicles in China.
Evelyn Cheng | CNBC

BEIJING — Tesla cut prices for its electric cars in China by more than BYD did for its flagship Han sedan, according to analysis Wednesday from U.S.-based firm JL Warren Capital.
Tesla reduced the price of its Model 3 by 6% compared to December last year, and cut the price of Model Y by 11% during the same period of time, JL Warren Capital CEO and Head of Research Junheng Li said in the report.

BYD’s Han only saw a 5% price decrease during that time, she said.
The Han, the company’s premium electric sedan, sells in a similar price range as Tesla’s cars — above 200,000 yuan ($28,000). Most of BYD’s other cars cost much less.
The report showed that BYD increased its sales promotions throughout the year, shaving 10% or 17% off the price of some mass market models. “Double-digit discounts are a common promotion by [original equipment manufacturers] to stimulate sell-through and meet the sales target,” Li said.

High-end electric car startup Nio also cut prices this year, despite initially trying to avoid getting caught up in an industry price war.
“Unlike in the EU or the US, residual values do not appear to feature highly in Chinese consumers’ purchase decisions,” HSBC analysts said in a Dec. 4 report about the auto industry. “That is perhaps the reason why price competition is so severe in China relative to EU/US.”

Thanks partly to government support, penetration of new energy vehicles, which include battery and hybrid-powered cars, has surged to well over one-third of new passenger cars sold in China.
Li expects that penetration rate will be around 40% next year, while electric car sales grow by 20%, a slowdown from a 35% increase in 2023.

Read more about electric vehicles, batteries and chips from CNBC Pro

Already for this year, the industry’s largest automakers had an “overly ambitious goal” of 93% sales growth, Li said. She pointed out that among 13 major EV manufacturers in China, only Tesla and Li Auto are set to reach their respective sales targets for the year.
That signals competition is about to get fiercer in China, the world’s largest auto market, which could lead to the potential for industry waste.
“New models spur EV demand, but at the cost of intensifying [the] pricing war as the market is flooded with inventory of ‘obsolete’ models,” Li said, noting the new car development cycle in China has been reduced to one or two years versus about three years previously.  More

Alibaba Group CEO Eddie Wu is taking over the top role at the company’s Taobao and Tmall e-commerce business, replacing Trudy Dai in the Chinese internet tech giant’s latest management shakeup this year.
Wu replaced Daniel Zhang as the group’s CEO in September.
Wu also became acting chairman and CEO of Alibaba’s Cloud Intelligence Group in September after Zhang abruptly left the business unit.

Trader works at the post where Alibaba is traded on the floor of the New York Stock Exchange (NYSE) in New York City, U.S., March 28, 2023. REUTERS/Brendan McDermid
Brendan Mcdermid | Reuters

BEIJING — Alibaba Group CEO Eddie Wu is taking over the top role at the company’s Taobao and Tmall e-commerce business, replacing Trudy Dai in the Chinese internet tech giant’s latest management shakeup this year.
Dai, who is one of the 18 cofounders of Alibaba, will assist in establishing an asset management company, according to an internal letter from Alibaba Chairman Joe Tsai seen by CNBC.

Alibaba’s announcement Wednesday comes after Wu replaced Daniel Zhang as the group’s CEO in September.
Wu has been chairman of Taobao and Tmall Group since May 2023.

The e-commerce business that once propelled Alibaba to success has run into challenges with rising competitors such as PDD, while consumption growth in China remains sluggish.
PDD’s U.S.-listed shares have gained more than 80% so far this year, driving the company’s market capitalization higher than Alibaba’s. In contrast, the company founded by Jack Ma has seen its shares fall by about 14% year to date.
Contributing to a recent decline in Alibaba shares was news last month that the company had scrapped plans to list its cloud business due to U.S. restrictions on exports of advanced chips to China.

Alibaba in March had announced a massive restructuring into six units, paving the way for individual stock listings, especially for its cloud business.
Wu became acting chairman and CEO of Alibaba’s Cloud Intelligence Group in September after Zhang abruptly left the business unit.
“Eddie’s leadership of both Alibaba Cloud and [Taobao and Tmall Group] will ensure total focus on, and significant and sustained investment in, our two core businesses of cloud computing and e-commerce, as well as enabling TTG to transform through technology innovation,” Tsai’s letter said.
“Soon, we will empower a new cohort of management leaders who have developed fundamental skillsets and experience from the bottom up.”
Dai “accomplished” the company’s mission regarding Taobao and Tmall, and her new role in the asset management company would allow her to “play to her strengths,” the letter said.
During Alibaba’s latest earnings call in mid-November, the company said it planned to monetize its non-core assets and noted it had $67 billion on its balance sheet in equity securities and other investments.
Tsai’s letter did not provide details on those non-core assets. More

The number of “accredited” investors swelled to 24 million in 2022, the SEC said. That’s 8 million more than in 2019, and the number is poised to keep growing.
Accredited investors can buy private securities such as private equity, hedge funds and venture capital funds. They generally meet financial requirements tied to net worth or annual income.
Private investments used to be earmarked for roughly the top 2%. Now, about 1 in 5 households can buy them.

Morsa Images | Getty Images

Inflation has given millions of people new access to certain investments earmarked for the wealthy — and consumer advocates argue that’s not a good thing.
Americans must generally be “accredited” to invest in private companies and investments such as private equity and hedge funds.

That accredited status is a consumer protection issue: To qualify, households must meet certain requirements — like a minimum net worth or annual income — which helps ensure they’re financially sophisticated and can sustain the risk of loss from private investments.
Over 24 million U.S. households — about 18.5% of them — qualified as accredited investors in 2022, the Securities and Exchange Commission said in a report issued Friday.
That’s an increase of about 8 million households from 2019, the last year for which the SEC published an estimate. That year, 13% of households qualified.
The increase is “largely due to” inflation, the SEC said.

How inflation affects accredited investor ranks

Individuals can generally become accredited by having a $200,000 annual earned income, or $300,000 for married couples. Individuals or couples can also qualify with a total $1 million net worth, not including the value of their primary residence.

However, those financial thresholds aren’t pegged to inflation. They stay the same even as wealth and incomes naturally grow over time — meaning more people have gradually become accredited over the years.
Indeed, the thresholds haven’t changed since their creation in the early 1980s. In 1983, just 1.5 million households — 1.8% — qualified as accredited investors, according to SEC data.

Most Americans will join the ranks of accredited investors in coming decades if the financial thresholds remain unmoored from inflation: By 2052, nearly 119 million households would qualify — or about 66% of them, the SEC said.
“The pool keeps increasing,” said Micah Hauptman, director of investor protection at the Consumer Federation of America, a consumer advocacy group. “If we don’t do anything, the standard will be rendered meaningless.”
If the financial standards had been indexed to inflation since the 1980s, a married household would need a roughly $3 million net worth or a $911,352 joint income to be accredited in 2022, the SEC said. Just 5.7% of households — about 7.4 million — would qualify, according to its data.
More from Personal Finance:Even high earners consider themselves ‘not rich yet,’ despite their net worthThe S&P 500 is up about 23% year to date. Here’s what to knowOnly 60% of student loan borrowers made payments when bills restarted

The difference between public and private investments

Private investments differ from their publicly available counterparts.
Public investments include ones with which most households are familiar, such as the stocks and funds available for purchase on a stock exchange. Generally, anyone can buy them.
Private investments let people invest in companies that aren’t listed on a public exchange.
Some argue that private investments should be available to a broader pool of investors due to benefits such as higher average returns.
Private equity returns, for example, have outperformed the S&P 500 stock index by 1% to 5% on an annualized basis since 2009, according to a 2021 report by Michael Cembalest, chair of market and investment strategy for J.P. Morgan Asset & Wealth Management.

Others argue that private markets are less transparent, with information about companies and funds less readily available to many investors, and carry additional risks.
“Without information, you have no ability to value the company to make an informed investment decision,” Hauptman said. “You’re investing blind.”
Private investments are also generally illiquid, and investors should be prepared to lock up their money for maybe 10 years in some cases, said Paul Auslander, a certified financial planner and director of financial planning at ProVise Management Group in Clearwater, Florida. That longer holding period could make them riskier for some investors, he said.
“It’s like any other investment,” Auslander said. “You have to read the fine print and make sure you know what you’re investing in.”

Shift away from pensions helps investors qualify

Aside from inflation, trends like the move toward 401(k) plans and away from pensions have contributed to the swelling ranks of accredited investors over time, according to the SEC.
About 85 million people actively participated in 401(k)-type plans in 2020, about three times the number in 1982, the SEC said. Such private retirement savings is included in calculations of net worth.

The pool keeps increasing. If we don’t do anything, the standard will be rendered meaningless.

Micah Hauptman
director of investor protection at the Consumer Federation of America

The shift from pensions may have also “created investor protection considerations” that weren’t present in the early 1980s, according to the SEC. That’s because the responsibility for investment decision-making shifts from employers to individuals, who may lack the experience to appropriately manage investment risk, the SEC said.
There would be about 5 million fewer accredited investors in 2022 if retirement savings were omitted from the net-worth calculation, the SEC said. More

Large language models, similar to the one at the heart of ChatGPT, frequently fail to answer questions derived from Securities and Exchange Commission filings, new research finds.
The findings highlight some of the challenges facing AI models as big companies, especially in regulated industries like finance, seek to incorporate cutting-edge technology into their operations, whether for customer service or research.
“That type of performance rate is just absolutely unacceptable,” Patronus AI cofounder Anand Kannappan said. “It has to be much much higher for it to really work in an automated and production-ready way.”

Patronus AI cofounders Anand Kannappan and Rebecca Qian
Patronus AI

Large language models, similar to the one at the heart of ChatGPT, frequently fail to answer questions derived from Securities and Exchange Commission filings, researchers from a startup called Patronus AI found.
Even the best-performing AI model configuration they tested, OpenAI’s GPT-4-Turbo, when armed with the ability to read nearly an entire filing alongside the question, only got 79% of answers right on Patronus AI’s new test, the company’s founders told CNBC.

Oftentimes, the so-called large language models would refuse to answer, or would “hallucinate” figures and facts that weren’t in the SEC filings.
“That type of performance rate is just absolutely unacceptable,” Patronus AI cofounder Anand Kannappan said. “It has to be much much higher for it to really work in an automated and production-ready way.”
The findings highlight some of the challenges facing AI models as big companies, especially in regulated industries like finance, seek to incorporate cutting-edge technology into their operations, whether for customer service or research.
The ability to extract important numbers quickly and perform analysis on financial narratives has been seen as one of the most promising applications for chatbots since ChatGPT was released late last year. SEC filings are filled with important data, and if a bot could accurately summarize them or quickly answer questions about what’s in them, it could give the user a leg up in the competitive financial industry.
In the past year, Bloomberg LP developed its own AI model for financial data, business school professors researched whether ChatGPT can parse financial headlines, and JPMorgan is working on an AI-powered automated investing tool, CNBC previously reported. Generative AI could boost the banking industry by trillions of dollars per year, a recent McKinsey forecast said.

But GPT’s entry into the industry hasn’t been smooth. When Microsoft first launched its Bing Chat using OpenAI’s GPT, one of its primary examples was using the chatbot quickly summarize an earnings press release. Observers quickly realized that the numbers in Microsoft’s example were off, and some numbers were entirely made up.

‘Vibe checks’

Part of the challenge when incorporating LLMs into actual products, say the Patronus AI cofounders, is that LLMs are non-deterministic — they’re not guaranteed to produce the same output every time for the same input. That means that companies will need to do more rigorous testing to make sure they’re operating correctly, not going off-topic, and providing reliable results.
The founders met at Facebook parent-company Meta, where they worked on AI problems related to understanding how models come up with their answers and making them more “responsible.” They founded Patronus AI, which has received seed funding from Lightspeed Venture Partners, to automate LLM testing with software, so companies can feel comfortable that their AI bots won’t surprise customers or workers with off-topic or wrong answers.
“Right now evaluation is largely manual. It feels like just testing by inspection,” Patronus AI cofounder Rebecca Qian said. “One company told us it was ‘vibe checks.'”
Patronus AI worked to write a set of over 10,000 questions and answers drawn from SEC filings from major publicly traded companies, which it calls FinanceBench. The dataset includes the correct answers, and also where exactly in any given filing to find them. Not all of the answers can be pulled directly from the text, and some questions require light math or reasoning.
Qian and Kannappan say it’s a test that gives a “minimum performance standard” for language AI in the financial sector.
Here’s some examples of questions in the dataset, provided by Patronus AI:

Has CVS Health paid dividends to common shareholders in Q2 of FY2022?
Did AMD report customer concentration in FY22?
What is Coca Cola’s FY2021 COGS % margin? Calculate what was asked by utilizing the line items clearly shown in the income statement.

How the AI models did on the test

Patronus AI tested four language models: OpenAI’s GPT-4 and GPT-4-Turbo, Anthropic’s Claude2, and Meta’s Llama 2, using a subset of 150 of the questions it had produced.
It also tested different configurations and prompts, such as one setting where the OpenAI models were given the exact relevant source text in the question, which it called “Oracle” mode. In other tests, the models were told where the underlying SEC documents would be stored, or given “long context,” which meant including nearly an entire SEC filing alongside the question in the prompt.
GPT-4-Turbo failed at the startup’s “closed book” test, where it wasn’t given access to any SEC source document. It failed to answer 88% of the 150 questions it was asked, and only produced a correct answer 14 times.
It was able to improve significantly when given access to the underlying filings. In “Oracle” mode, where it was pointed to the exact text for the answer, GPT-4-Turbo answered the question correctly 85% of the time, but still produced an incorrect answer 15% of the time.
But that’s an unrealistic test because it requires human input to find the exact pertinent place in the filing — the exact task that many hope that language models can address.
Llama2, an open-source AI model developed by Meta, had some of the worst “hallucinations,” producing wrong answers as much as 70% of the time, and correct answers only 19% of the time, when given access to an array of underlying documents.
Anthropic’s Claude2 performed well when given “long context,” where nearly the entire relevant SEC filing was included along with the question. It could answer 75% of the questions it was posed, gave the wrong answer for 21%, and failed to answer only 3%. GPT-4-Turbo also did well with long context, answering 79% of the questions correctly, and giving the wrong answer for 17% of them.
After running the tests, the cofounders were surprised about how poorly the models did — even when they were pointed to where the answers were.
“One surprising thing was just how often models refused to answer,” said Qian. “The refusal rate is really high, even when the answer is within the context and a human would be able to answer it.”
Even when the models performed well, though, they just weren’t good enough, Patronus AI found.
“There just is no margin for error that’s acceptable, because, especially in regulated industries, even if the model gets the answer wrong one out of 20 times, that’s still not high enough accuracy,” Qian said.
But the Patronus AI cofounders believe there’s huge potential for language models like GPT to help people in the finance industry — whether that’s analysts, or investors — if AI continues to improve.
“We definitely think that the results can be pretty promising,” said Kannappan. “Models will continue to get better over time. We’re very hopeful that in the long term, a lot of this can be automated. But today, you will definitely need to have at least a human in the loop to help support and guide whatever workflow you have.”
An OpenAI representative pointed to the company’s usage guidelines, which prohibit offering tailored financial advice using an OpenAI model without a qualified person reviewing the information, and require anyone using an OpenAI model in the financial industry to provide a disclaimer informing them that AI is being used and its limitations. OpenAI’s usage policies also say that OpenAI’s models are not fine-tuned to provide financial advice.
Meta did not immediately return a request for comment, and Anthropic didn’t immediately have a comment. More

The 167-year-old Credit Suisse was rescued by rival UBS in March in a deal brokered by Swiss authorities, after a string of risk management failures and scandals triggered a client and investor exodus.
In the 2018-2022 period, Swiss regulator FINMA conducted 108 on-site supervisory reviews at Credit Suisse and recorded 382 points requiring action, 113 of which were classed as high or critical risks.
The regulator therefore called for “extended options that would enable it to have more influence on the governance of supervised institutions.”

Axel Lehmann, chairman of Credit Suisse Group AG, Colm Kelleher, chairman of UBS Group AG, Karin Keller-Sutter, Switzerland’s finance minister, Alain Berset, Switzerland’s president, Thomas Jordan, president of the Swiss National Bank (SNB), Marlene Amstad, chairperson of the Swiss Financial Market Supervisory Authority (FINMA), left to right, during a news conference in Bern, Switzerland, on Sunday, March 19, 2023.
Pascal Mora | Bloomberg | Getty Images

Switzerland’s financial regulator on Tuesday called for greater legal powers and vowed to adapts its approach in the wake of the Credit Suisse collapse.
The 167-year-old bank was rescued by domestic rival UBS in March in a deal brokered by Swiss authorities, after a string of risk management failures and scandals triggered a client and investor exodus that forced it to the brink of insolvency.

The Swiss Financial Market Supervisory Authority (FINMA) said in a Tuesday report that, alongside the government and the Swiss National Bank, it had achieved the aim of safeguarding Credit Suisse’s solvency and ensuring financial stability.
It also drew attention to the “far-reaching and invasive measures” taken over the preceding years to supervise the bank and to “rectify the deficiencies, particularly in the bank’s corporate governance and in its risk management and risk culture.”
From summer 2022 onwards, FINMA also told the bank to take “various measures to prepare for an emergency” — a warning it suggests went unheeded.

“FINMA draws a number of lessons in its report. On the one hand, it calls for a stronger legal basis, specifically instruments such as the Senior Managers Regime, the power to impose fines, and more stringent rules regarding corporate governance,” the regulator said.
“On the other hand, FINMA will also adapt its supervisory approach in certain areas, and will step up its review of whether stabilisation measures are ready to implement.”

FINMA said that strategic changes announced to de-risk Credit Suisse, such as downsizing its investment bank, focusing on its asset management business and reducing its earnings volatility, were “not implemented consistently,” while “recurrent scandals undermined the bank’s reputation.”
It also noted that, even in years when the bank posted heavy financial losses, the variable remuneration remained high, with shareholders making little use of opportunities to influence pay packets.
Between 2012 and the bank’s emergency rescue, the regulator says it conducted 43 preliminary investigations of Credit Suisse for potential enforcement proceedings. Nine reprimands were issued, 16 criminal charges filed, and 11 enforcement proceedings were taken against the bank and three against individuals.
FINMA said it repeatedly informed Credit Suisse of risks, recommended improvements and imposed “far reaching measures.” These included “extensive capital and liquidity measures, interventions in the bank’s governance and remuneration, and restrictions on business activities.”

“In the period from 2018 to 2022 it also conducted 108 on-site supervisory reviews at Credit Suisse and recorded 382 points requiring action,” FINMA said.
“In 113 of these points the risk was classed as high or critical. These figures and measures illustrate that FINMA exhausted its options and legal powers.”
At the time of its collapse, Credit Suisse bosses attributed the loss of confidence to the market panic triggered by the collapse of Silicon Valley Bank in the U.S.
Credit Suisse was asked over the summer to put in place crisis preparation measures, such as partial business sales and the possible sale of the entire bank in an existential emergency.
The regulator therefore called for “extended options that would enable it to have more influence on the governance of supervised institutions.”
These include the implementation of a Senior Managers Regime, powers to impose fines and option of regularly publishing enforcement proceedings.
“To enable FINMA to effectively intervene in remuneration systems, a more solid legal mandate is required,” it concluded. More

Chopping off their heads does not work: cockroaches can live without one for as long as a week. Whacking them is no guarantee either: their flexible exoskeletons can bend to accommodate as much as 900 times their body weight. Nor is flushing them down the toilet a solution: some breeds can hold their breath for more than half an hour. To most, roaches are an unwelcome pest. Their presence is made all the worse because they are indestructible.An unwelcome pest is how many financiers and regulators would describe the crypto industry. Criminals use cryptocurrencies to launder money. Terrorists use them to make payments. Hackers demand ransoms in bitcoin. Many crypto coins are created simply so their makers can make off with the money.The industry also appears to be indestructible. Crypto prices were crushed by higher interest rates in 2022. The industry’s head has been chopped off: Changpeng Zhao and Sam Bankman-Fried, the founders of the world’s biggest and second-biggest crypto exchanges, now both await sentencing for financial crimes (breaking anti-money-laundering laws and fraud, respectively). Regulators are cracking down. Yet not only has crypto survived, it is once again soaring: bitcoin climbed to a two-year high of almost $45,000 on December 11th, up from just $16,600 at the start of the year.What is going on? For one thing, indestructibility is built into the technology. Bitcoin, ether and other coins are not companies—they cannot go bankrupt and be shut down. They employ blockchains, which maintain a database of transactions. Their lists are verified by a decentralised network of computers that are incentivised to keep maintaining them by the promise of new tokens. Only if the tokens fall to zero does the whole architecture collapse. And there continue to be lots of reasons to believe some crypto tokens are worth more than nothing.The first is that holding crypto is a bet on a future in which use of the technology is widespread. People in despotic countries already use bitcoin and stablecoins (tokens pegged to a hard currency, like the dollar) to store savings and sometimes to make payments. These could be used more widely. Artists and museums are still creating or collecting non-fungible tokens (nfts). As are those looking to flog an image. Donald Trump is selling his mugshot for $99 a piece. He plans to have the suit he was booked in cut into pieces, made into cards and given to punters who buy at least 47 nfts in a single transaction.During the boom times, the crypto industry raised a lot of money and hired plenty of smart developers. Those that remain are working on new uses, like social-media applications or play-to-earn games. Perhaps these will never be widely adopted. But even the small chance that they work out is worth something.The second reason is that, with each boom-and-bust cycle, it becomes clearer crypto is not a bubble like tulip mania in the 1630s or the craze for Beanie Babies in the 1990s. Although bitcoin is a volatile asset, its price history looks more like a mountain range than a single peak, and appears closely correlated with tech stocks. Yet it is only moderately correlated with the broader market. An asset that swings up and down, and not in parallel with other things people might have in a portfolio, can be a useful diversifier.That bitcoin has established itself as a serious asset seems to be the source of the latest surge. In August an American court ruled that the Securities and Exchange Commission, America’s main markets regulator, had been “arbitrary and capricious” when rejecting an effort by Grayscale, an investment firm, to convert a $17bn trust invested entirely in bitcoin into an exchange-traded fund (etf). Doing so would make investing in bitcoin easier for the average punter.In October the court upheld its ruling—in effect ordering the sec to give way. The biggest fund managers, including BlackRock and Fidelity, have also applied to launch etfs. Given the returns bitcoin has offered in the past, and its correlations with other assets, the result could be a rush of cash into bitcoin, as even sensible investors consider putting small slices of their pension pots or portfolios into crypto for diversification.Many feel instinctive revulsion when they spy a roach. But in spite of their flaws, the bugs have uses—they turn decaying matter into nutrients and eat other pests, such as mosquitoes. Crypto has its uses, too, such as portfolio diversification and keeping money safe under despotic regimes. And, as has been shown, it is just about impossible to kill. ■ More

Experts expect generative AI to transform the way wealth management firms do business.
Gen AI can have a powerful impact when combined with other AI technologies, according to PwC.
BlackRock and Morgan Stanley are among the big firms that have embraced AI.

Yuichiro Chino | Moment | Getty Images

Like it or not, generative artificial intelligence has arrived on Wall Street — and experts expect it to transform the way firms do business.
To be clear, artificial intelligence, like natural language processing and machine learning, has been used by wealth management and asset management firms for years. Yet with generative AI now on the scene, it can have a powerful impact when combined with other AI technologies, said Roland Kastoun, U.S. asset and wealth management consulting leader for PwC.

“We see this as a massive accelerator of productivity and revenue growth for the industry,” he said.
In fact, the banking sector is expected to have one of the largest opportunities in generative AI, according to McKinsey & Company. Gen AI could add the equivalent of $2.6 trillion to $4.4 trillion annually in value across the 63 use cases the McKinsey Global Institute analyzed. While not the largest beneficiaries within banking, asset management could see $59 billion in value and wealth management could see $45 billion.

Some of the biggest names in the business are already on board.
Earlier this month, BlackRock sent a memo to employees that in January it will roll out to its clients generative AI tools for Aladdin and eFront to help users “solve simple how-to questions,” the memo said.
“GenAI will change how people interact with technology. It will improve our productivity and enhance the great work we are already doing. GenAI will also likely change our clients’ expectations around the frequency, timeliness, and simplicity of our interactions,” the memo said.

Meanwhile, Morgan Stanley unveiled its generative AI assistant for financial advisors, called AI @ Morgan Stanley Assistant, in September. The firm’s co-President Andy Saperstein said in a memo to staffers that generative AI will “revolutionize client interactions, bring new efficiencies to advisor practices, and ultimately help free up time to do what you do best: serve your clients.”
Earlier this year, both JPMorgan and Goldman Sachs said they were developing ChatGPT-style AI in house. JPMorgan’s IndexGPT will tap “cloud computing software using artificial intelligence” for “analyzing and selecting securities tailored to customer needs,” according to a filing in May. Goldman said its technology will help generate and test code.
Read more from CNBC Pro:How to invest in Wall Street’s artificial intelligence boom
Those who don’t embrace AI will be left behind, said Wells Fargo bank analyst Mike Mayo.
“If the bank across the street has financial advisors that are using AI, how can you not be using it too?” he said. “It certainly increases the stakes for competition, and you can keep up or fall behind.”
In fact, as the younger generation ages, those digitally native investors will seek greater digitization, more personalized solutions and lower fees, William Blair analyst Jeff Schmitt said in an Oct. 20 note.
“Given that these investors will control an increasing share of invested assets over time, wealth management firms and advisors are leveraging AI to enhance offerings and adjust service delivery models to win them over,” he wrote.
Cerulli Associates estimated some $72.6 trillion in wealth will be transferred to heirs through 2045.

Not just generative AI

The big appeal of generative AI — and a differentiator from other AI tech — is its ability to generate content, said PwC’s Kastoun.
It’s one thing for technology to analyze a large set of content, he pointed out. “It’s another thing for it to be able to generate new content based on the data that it has, and that’s what’s creating a lot of hype.”
Yet what he’s seeing in both the wealth management and asset management business is the use of multiple elements of AI, not just generative AI, he said.
“It’s the power of combining these different technologies and methodologies that is really creating an impact across the industry,” Kastoun said.
Firms are now figuring out how to incorporate generative AI into their businesses and existing AI technologies. At T. Rowe Price, its New York City Technology Development Center has been building AI capabilities for several years.
“We ultimately are looking to help our decision makers get the benefit of data and insights to do their job better,” said Jordan Vinarub, head of the center.
His team made a big pivot with the arrival of generative AI.
“We kind of saw this as an existential moment for the firm to say, we need to understand this and figure out how we can use it to support the business,” Vinarub said. “Over the past, I guess, six months … we’ve gone from just pure research and proofs of concept to then building our own internal application on top of the large language model to help assist our investors and research process.”

New entrants

It’s not only the big firms adapting to generative AI; smaller upstarts are looking for ways to disrupt the industry.
Wealth-tech firm Farther is one of those. Its co-founder, Brad Genser, said the company is a “new type of financial institution” that was built to combine expert advisors and AI.
“If you don’t build the technology, along with the human processes, and you don’t control both, you end up with something that’s incomplete,” he said. “If you do it together, you’re building people processes and technology together, then you get something that’s greater than the sum of its parts.”
Then there is Magnifi, an investing platform that uses ChatGPT and computer programs to give personal investing advice. Investors link the technology to their various accounts, and Magnifi can monitor their portfolios. About 45,000 subscribers have connected over $500 million in aggregate assets to the platform, Magnifi said in November.
“It’s a copilot alongside individual consumers that they’re interacting with over time,” said Tom Van Horn, Magnifi’s chief operating and product officer. “It’s not taking over control, it’s empowering those individuals to get to better wealth outcomes.”

An AI coworker

The technology is so fast moving, it’s difficult to know what use cases could exist in the future. Yet certainly as productivity continues to increase, advisors can increase their time and level of engagement with their clients.
“It could change the way we think about a lot of the way we set up our business models,” PwC’s Kastoun said.
It’s also about people working with the technology and not the technology necessarily replacing humans, experts said.
“The dream state is that every employee will have an AI copilot or AI coworker and that each customer will have the equivalent of an AI agent,” Wells Fargo’s Mayo said. “I’m not talking about computers alone. I’m not talking about humans alone, but humans plus AI can compete better than either computers or humans alone.”
— CNBC’s Michael Bloom contributed reporting.
Correction: This article has been updated to reflect that Magnifi said in November that about 45,000 subscribers have connected over $500 million in aggregate assets to the platform. A previous version misstated the amount of assets. More

The Fed voted last week to hold rates steady once again, and its updated projections showed an expectation of three rate cuts in 2024.
That caused a rally in stocks and bonds, with the Dow Jones Industrial Average jumping to a record.
However, Chicago Fed President Austan Goolsbee suggested on CNBC’s “Squawk Box” on Monday that the reaction wasn’t totally rational given what the central bank actually said.

A Federal Reserve official said Monday that the market may have misunderstood the central bank’s intended message last week after stocks and bonds rallied sharply.
The Fed voted last week to hold rates steady once again, and its updated projections showed an expectation of three rate cuts in 2024. That caused a rally in stocks and bonds, with the Dow Jones Industrial Average jumping to a record high.

“It’s not what you say, or what the chair says. It’s what did they hear, and what did they want to hear,” said Chicago Fed President Austan Goolsbee said on CNBC’s “Squawk Box.” “I was confused a bit — was the market just imputing, here’s what we want them to be saying?”

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The Dow hit a record high last week.

The Fed president also pushed back against the idea that the Fed is actively planning on a series of rate cuts.
“We don’t debate specific policies, speculatively, about the future. We vote on that meeting,” he said.
Trading in the options market implies that traders see 3.75% to 4.00% as the most likely range for the Fed’s benchmark rate at the end of 2024, according to the CME FedWatch Tool. That would be six quarter-point cuts below the current Fed funds rate, or double what was forecast in the central bank’s summary of economic projections.
Goolsbee did not explicitly say that the market pricing was wrong, but did highlight this difference.

“The market expectation of the number of rate cuts is greater than what the SEP projection is,” Goolsbee said.
Goolsbee is not the only Fed official who has downplayed the meeting in the wake of the market rally. New York Fed President John Williams said on CNBC’s “Squawk Box” on Friday that “we aren’t really talking about rate cuts right now.” More