Editor's note: Consumer-grade AI Agents are moving from "helping users answer questions" to "completing tasks for users." Bernstein noted in its latest report that after launch, Muse quickly rose to the top of the U.S. App Store, with downloads reaching about 2.8 million, and users have already begun using it to book services, cancel subscriptions, compare insurance, fill out forms, and contact customer service. At the same time, a group of financial stocks that rely on consumer stickiness and operational friction saw significant declines.

The market's most intuitive concern is whether AI Agents will directly bypass banks, insurance companies, brokerages, and credit cards. But what Bernstein is really discussing is not simply "technological replacement," but a more fundamental question: if AI can continuously compare prices, switch products, and move funds for consumers, will the profits the financial industry has built on consumer inertia, information friction, and switching costs begin to be compressed?

The report argues that insurance renewals, bank deposits, brokerage idle cash, and primary credit card status could all be affected. But this does not mean Agents will soon be able to fully take over financial decisions. Financial institutions still control accounts, data, and trading permissions, consumers may not be willing to hand their money entirely to AI, and liability and regulatory frameworks have not kept up with technological development.

Therefore, the impact of this wave of Agents on the financial industry may not be a comprehensive disruption, but a redistribution of value: the more a segment relies on consumers "not acting" to make money, the greater the potential pressure; the more it can provide infrastructure for identity verification, payment security, risk control, and data interfaces, the more important it may instead become.

The following is a compilation of the original text:

After Muse launched, financial markets quickly began trading a new question: if consumers have an AI Agent that can continuously compare prices, switch products, cancel subscriptions, and even move funds on their behalf, what will traditional financial institutions rely on to retain customers?

Bernstein statistics show that since Muse was launched, insurance, large banks and credit card issuers, regional banks, brokerages, and mortgage lenders have all experienced declines to varying degrees, with mortgage-related companies falling the most; the payments sector has been relatively limited in the impact it has suffered.

The logic behind this market reaction is not complicated.

A considerable portion of the financial industry's profits does not come because consumers make the wrong decision every time, but because consumers simply will not continuously optimize their choices.

And what AI Agents are most likely to change is precisely this.

What AI Agents touch first is the "consumer inertia" of the financial industry

Insurance is the most typical example.

Many users will directly renew their policies after they expire, rather than re-comparing prices, coverage, and products from different companies every year. As long as this renewal inertia exists, insurance companies have a certain degree of pricing room.

Banks and brokerages also have similar logic.

Consumers do not compare deposit rates at different banks every day, nor do they continuously deal with idle cash in brokerage accounts. As a result, low-yield deposits can remain in banks for a long time, and brokerages can also earn revenue from businesses such as cash sweep.

The credit card industry relies on another habit.

Consumers often use the same credit card for a long time, and this position of "using a certain card by default first" is usually called top-of-wallet. Through points, cashback, and long-term usage habits, banks turn a card into the default choice when consumers pay.

AI Agents may weaken these advantages at the same time.

If an Agent can automatically compare insurance quotes, find higher deposit yields in real time, move idle cash in brokerage accounts into higher-yield products, or compare the cashback, points, and rates of different credit cards before every purchase, then the "search-compare-switch" process that consumers previously had to complete on their own will be greatly compressed.

Bernstein therefore believes that automated cash management may make deposit migration easier, thereby pushing up bank funding costs and compressing net interest margins; brokerages' cash sweep revenue may come under pressure; and credit card issuers may lose part of the advantages brought by top-of-wallet and long-term usage habits.

What is really changing here may not necessarily be the financial products themselves, but rather the declining cost for consumers to optimize financial products.

In the past, consumers had to invest time and effort to switch insurance every year, compare interest rates across five banks, and research which credit card offers the highest cashback; if these tasks can be continuously handled by an Agent in the background, then the economic value of "users being too lazy to switch" itself may decline.

But just because an Agent can do it doesn't mean it has the right to do it

If we continue to extrapolate along this logic, it is easy to reach an extreme conclusion: AI Agents will ultimately bypass banks, insurance companies, and brokerages to directly complete all financial decisions for consumers.

Bernstein believes things are not that simple.

Third-party Agents face a fundamental contradiction: without cooperation from merchants and financial institutions, it is difficult for them to truly complete complex transactions; but if open access means losing customer relationships, transaction entry points, or part of their revenue, financial institutions have no reason to cooperate unconditionally.

Banks, brokerages, and insurance companies still control several key points: account login, identity verification, data permissions, formal quotes, and whether users are eligible for a certain product.

This is also why some platforms have already begun restricting Agent access.

Bernstein mentioned that Amazon chose to block Muse, with disputes between the two sides over Agent identity recognition and the use of user login credentials; the insurance comparison platform Insurify also restricted Muse from scraping quotes, on the grounds that insurance is not simply a price comparison—beyond premiums, there is also a large amount of information such as coverage limits, deductibles, discount conditions, eligibility, and regulatory disclosures. If an Agent ultimately presents only a "lowest price," what consumers get may not be a truly comparable product.

This means that the core bottleneck for financial Agents is shifting from "whether the model can do it" to "who allows it to do it."

Data is one of the most important thresholds. Financial institutions control account authentication, account data, and data-sharing permissions, so Bernstein raised a possibility opposite to "AI platforms charging banks": will banks in the future instead charge Agents data access fees?

The report mentioned that the earlier U.S. open banking rules around Section 1033 originally sought to require banks to provide account data for free to consumers and their authorized third parties through secure APIs; the relevant rules were subsequently blocked, and JPMorgan has since begun charging data aggregators for customer data access. Bernstein believes that in the future, around Agent data access, there are likely to be more blockings, paid agreements, and situations in which financial institutions actively control what information is shown to Agents.

Even if the technology and data interfaces are already in place, consumers themselves are another constraint.

A 2026 TD Bank survey of more than 2,500 U.S. consumers showed that 55% already use AI to help manage their personal finances, but only 18% are willing to let AI make important financial decisions independently. Consumers clearly prefer a model in which "AI provides advice and humans retain the final say."

Other surveys show similar results. A survey by ACI Worldwide and YouGov showed that only 7% of U.S. and U.K. consumers are willing to let an AI assistant make purchases directly without approval; an Accenture survey showed that 32% are willing to let an Agent make purchasing decisions within set parameters, but when it comes to the actual payment step, only 12% are willing to let the Agent decide completely autonomously.