Fintech & Transfers

For two years, the pitch for AI agents in personal finance has been simple: give the software access to your accounts and let it pay bills, shop for better rates, rebalance a portfolio or book a trip. In late October 2026 the banks that hold those accounts are pushing back. Reports from across North America describe a growing list of lenders that are restricting, or considering restricting, outside agents from reaching customer accounts.

This article explains what is happening, why liability is at the centre of the dispute, what it means for customers and fintechs, and how finance teams should think about agent access in their own banking relationships.

What the banks are actually saying

The most direct public warning has come from Jamie Dimon at JPMorgan Chase. Coverage of his remarks describes a "liability transfer": when a customer hands an agent the keys to an account, the customer, not the bank, is expected to carry the risk of what the agent does. JPMorgan has been reported as blocking external AI agents from customer accounts altogether.

Citi and Bank of America have also restricted third-party agents. Bank of America's Brian Moynihan was quoted as saying the bank is limiting access while it develops protocols to establish which party is liable for payments authorised by artificial intelligence. That phrasing matters. It does not describe a permanent ban; it describes a pause until the rules of responsibility exist.

In Canada, the debate reached the front page of the industry press this week. Finextra reported that the chiefs of RBC and BMO were the latest bank leaders to warn customers about the dangers of linking accounts to AI agents. The detail in other reporting is more precise: RBC's chief executive, Dave McKay, said on Bloomberg Television that the bank is weighing whether to block Meta's agent from reaching customer information, with no final decision made. He raised unauthorised data access, fraudulent consent and liability as autonomous agents increasingly carry out transactions. BMO's contribution, from its chief AI and quantum officer Kristin Milchanowski, was less a warning than a forecast: people will be using AI agents for shopping and investing within six months, and consumer-facing companies must think about how they interact with and market to agents as well as to humans.

Why liability is the real fight

Consumer banking law in most markets was written around a human who initiates, or authorises, each payment. Protections such as chargebacks, unauthorised-transaction refunds and fraud liability limits assume that either the customer did something or a criminal did. An agent introduces a third category: a transaction the customer technically authorised in general terms but never approved in detail.

Consider three scenarios banks are worried about:

• The misread instruction. A customer tells an agent to "pay off the card". The agent pays the full balance from a savings account that was earmarked for tax. Was that authorised?
• The manipulated agent. A malicious web page or email contains hidden instructions that steer an agent into moving funds. The customer did not act; the agent did, but it was deceived.
• The over-broad consent. A user clicks through a permission screen granting an agent wide access, then disputes a transaction they did not expect. "Fraudulent consent" is the phrase McKay used for this family of problems.

In each case the bank is the party with the deepest pockets and the regulatory duty, yet it has no visibility into the software making the decisions. From a risk officer's perspective, blocking agents until responsibility is allocated is the conservative move. From a product perspective, it is a way to keep control of the customer relationship while the bank builds its own agents.

The competitive subtext

It would be naive to read the restrictions as purely defensive risk management. Banks have fought for years over who owns the customer interface. Open banking regimes and data-aggregation APIs forced them to share data with fintechs under defined terms. General-purpose AI agents threaten to go further by sitting on top of the bank app and turning it into a back-end utility. If an agent chooses the savings account, the card and the loan, the bank's brand stops mattering to the customer.

That is why the language from executives mixes safety and strategy. Banks want agent traffic to arrive through sanctioned channels, with authentication, spending limits and audit trails they define. They also want the economics: who pays for the API calls, and whether the agent's operator shares revenue. BMO's remark that companies must learn to market to agents is a tell. Agents will be a distribution channel, and the question is on whose terms.

What a workable framework might look like

Nobody has published a settled standard, so this section describes the components most proposals share rather than a finished rule.

1. Delegated, scoped credentials. Instead of handing over a password, a customer issues a token limited by action (view, pay existing payees), amount, merchant category and time. The token can be revoked instantly.
2. Agent identity. The bank can see which agent, run by which operator, is making a request, rather than an anonymous session that looks like a customer.
3. Step-up confirmation. Payments above a threshold, or to new payees, require the human to approve in the bank's own app.
4. A liability matrix. Contracts or regulation specify who bears losses when an agent errs, is manipulated, or is compromised. This is the missing piece Moynihan referred to.
5. Logs. A tamper-evident record of what the agent was told and what it did, so disputes can be resolved on evidence.

None of these is technically exotic. Payments already uses tokenisation, strong customer authentication and mandate-based direct debits. The hard part is commercial and legal agreement across thousands of institutions and a handful of dominant AI platforms.

What this means for customers

If you are an individual using, or considering, an AI agent with financial access, the practical implications are straightforward.

• Assume you carry the risk. Dimon's liability-transfer framing is a signal that banks may not reimburse losses caused by an agent you authorised.
• Prefer read-only access first. Letting an agent analyse spending is much safer than letting it move money.
• Use separate accounts. If you experiment, keep a small balance in an account the agent can touch, and the rest out of reach.
• Check whether your bank will block it. An agent that works today may stop working if your bank tightens rules, which can leave bills unpaid if you relied on it.

What this means for fintechs and AI platforms

Fintechs that built businesses on data aggregation have seen this film before, when banks restricted screen scraping in favour of APIs. The agent era will probably follow a similar arc: a period of blocking and negotiation, followed by formal access agreements for operators that accept liability, security requirements and fees. Startups that can offer compliant agent infrastructure, such as identity, consent management, monitoring and insurance, may find a market selling to both sides.

For AI platforms, the lesson is that general-purpose capability does not equal permission. Having an agent that can use a browser does not give it the right to operate inside a bank's authenticated session. The platforms that win financial use cases will likely be those that sign agreements with banks early.

What finance teams should do now

Corporate treasury and finance functions are experimenting with agents too, for reconciliations, payment preparation and cash reporting. The same questions apply at larger scale, and the stakes are higher.

• Inventory agent access. List every tool, employee-built automation or vendor feature that touches bank portals, and what credentials it uses.
• Separate preparation from release. Agents can draft payment files; humans or controlled systems should approve and release them. Dual control still applies.
• Ask your bank. Find out the bank's position on agent access, API options and liability allocation before rolling anything out.
• Update policy. Add agent-specific rules to your delegation-of-authority and information-security policies.
• Test for manipulation. Treat content an agent reads, such as invoices and emails, as untrusted input that could carry instructions.

The resilience link

The agent debate also intersects with operational resilience. This week UK and EU regulators sought answers from Google over a major cloud outage, a reminder that banks and fintechs depend on shared infrastructure. As agents add another dependency layer, a single failure in an agent platform could affect many customers' payments at once. Regulators who already scrutinise concentration risk in cloud services are likely to ask similar questions about agent providers.

What to watch next

• Whether RBC finalises a decision on blocking Meta's agent, and how Meta responds.
• Whether other large banks publish formal agent-access policies, or standard terms for sanctioned agents.
• Any regulatory guidance clarifying liability for agent-initiated payments. In the absence of new rules, existing unauthorised-transaction frameworks will be stretched.
• Pilot programmes where banks launch their own agents or approve selected partners.

Bottom line

The banks are not rejecting AI agents; they are refusing to underwrite them on someone else's terms. Until the industry agrees who bears the loss when software makes a mistake with real money, expect a patchwork of blocks, pilots and carefully scoped permissions. Individuals should treat agent access to money as a risk they personally carry, and finance teams should apply the same controls to agents that they apply to people: limited authority, separation of duties and clear audit trails.

Sources and further reading: Finextra reporting on bank limits for agent access (22 October 2026); coverage of JPMorgan, Citi and Bank of America restrictions on third-party agents; reporting on remarks by RBC's Dave McKay and BMO's Kristin Milchanowski. Details reflect public reports as of 25 October 2026 and may change. This article is general information, not financial or legal advice.

The Week Fintech Met Its Dependencies

Financial technology has spent a decade promising speed, convenience and lower costs. This week’s headlines show the other side of that bargain. According to The Guardian and Finextra, a major outage in Google’s London cloud region on October 20, 2026 caused problems at banks, at the digital bank Revolut and even at court video systems. Days later, Finextra reported that the chief executives of two of Canada’s largest banks, RBC and BMO, have warned customers about the dangers of linking their accounts to AI agents.

One story is about infrastructure that sits beneath the financial system; the other is about a new type of software that wants to act on customers’ behalf. Both raise the same question: when the technology does something unexpected, who is responsible, and how quickly can the damage be contained? This guide examines both, adds context from the week’s other fintech news, and ends with a practical checklist for fintech founders, bank technology teams and business customers.

The Google Cloud Outage in Detail

The Guardian’s live coverage reported that Google apologised after a power issue caused a major Cloud outage in its London region, leading to problems at banks, Revolut and court video cameras. Later in the day, the paper reported that problems had been fixed for most customers while regulators pushed for details. Finextra followed up that the European Banking Authority and the UK’s Financial Conduct Authority have been in contact with Google over the outage that knocked services offline earlier in the week.

It is worth being precise about what is known. Public reporting identifies a power issue in one cloud region, affecting multiple customers, with regulators asking questions. It does not tell us how long individual firms were affected or what, if any, customer losses resulted. Any commentary beyond that is inference, and we flag it as such.

Why a single region matters

Cloud providers divide infrastructure into regions and availability zones so that a failure in one place does not take everything down. Customers are supposed to design for that, spreading workloads across zones or regions. But doing so costs money and adds complexity, and many firms concentrate in one region for latency, data-residency or cost reasons. When a regional problem bites, the firms that chose the cheaper design find out at the worst possible time.

For regulated financial firms, this is not only a technical choice but a compliance one. Supervisors in the UK and EU have been building frameworks around operational resilience and third-party risk, and the fact that two regulators reached out to the provider this week shows the topic is live. Banks must be able to demonstrate that important business services can stay within tolerated disruption levels, including when a supplier fails.

AI Agents and the Bank Account Question

The second story is newer and, in some ways, more unsettling. AI agents are software programs that can take actions for a user, such as comparing offers, paying bills or moving money, rather than just answering questions. To do that, an agent needs access to accounts. Finextra reports that the CEOs of RBC and BMO are the latest bank chiefs to warn customers about the dangers of linking their accounts to such agents.

The reasons are easy to imagine, though the reporting we reviewed gives only the headline warning. Agents can be manipulated by malicious instructions hidden in the content they read. They can make mistakes with real money. They may operate with broad credentials that customers granted without understanding the scope. And when something goes wrong, liability is unclear: is it the customer, the agent developer, the bank or the platform hosting the model?

The security backdrop is not reassuring. CoinDesk reports that Bitcoin Core developers changed their security policy because AI now makes finding code bugs dangerously easy, ending a months-long embargo for flaws that a chatbot could rediscover, after a summer in which AI found hundreds of bugs. The same capabilities that help defenders find flaws also help attackers. A financial system increasingly connected to AI agents is a larger surface to defend.

What banks are likely to do

Without speculating about any particular bank’s plans, the options are fairly predictable. They can restrict agent access by default, require customers to opt in with explicit scopes, offer read-only connections, set transaction limits for agent-initiated payments, or build their own sanctioned agent interfaces. Each choice trades convenience for control. The warnings from large bank CEOs suggest the early posture will lean toward control.

Money Keeps Flowing In Anyway

Caution at the large institutions has not slowed investment in the sector. Finextra’s headlines this week include several funding and deal items:

• Coast, a New York-based fintech building a payments platform for companies in the physical economy, raised $35 million.
• Cognitive Credit closed a $40 million strategic growth investment led by Summit Partners to scale specialist data and AI for corporate credit markets.
• Fireblocks pushed back on reports of $2.5 billion acquisition talks with Visa, saying the reports were news to the company. That is a denial worth noting: the story was circulating, but the company says it is not true as reported.
• Finextra also reports that pay for quantitative finance professionals continues to rise despite the AI revolution, according to recent research.

In the wider technology world, TechCrunch reports that Daytona, a cloud for AI agents that gives each agent its own computer, hit a $1 billion valuation. That suggests investors expect agents to be a large category, which only increases the importance of the safety questions banks are raising.

Stablecoins and Cross-Border Rails: The Context

Alongside the resilience debate, fintech is busy building new payment rails. HSBC launched its first stablecoin for public use, and Thailand and Malaysia backed Singapore’s BLOOM cross-border digital money initiative, according to Finextra. Yet research from the Bank for International Settlements, also covered by Finextra, finds that fintechs such as Wise and Remitly have cut retail cross-border costs substantially relative to bank wires, while stablecoins still suffer from friction. The takeaway for fintech builders is humbling: customers reward measurable cost and speed improvements, not technology labels.

It also ties back to resilience. New rails create new dependencies, whether on a blockchain, a cloud region or a model provider. Every new dependency needs an answer to the question, what happens when it fails?

What Google Trends Shows

We checked Google’s daily trending searches for the US, UK, Hong Kong, Canada and India on October 24. Fintech terms did not appear among the top trending searches, which were dominated by sports and entertainment. That is typical: infrastructure outages and agent-security debates rarely trend with the general public, even when they matter greatly to professionals. The implication for content and communications teams is that the audience for these topics is specialist. Reach them through trade media, regulators’ publications and professional networks rather than waiting for a search surge.

A Resilience Checklist for Fintech Teams

1. Map critical dependencies. List every cloud region, payment processor, identity provider and data vendor your top customer journeys rely on.
2. Define tolerances. Decide how long each journey can be disrupted before customers are harmed, then compare against tested recovery times.
3. Design for regional failure. For services that matter, run active-active or at least warm-standby across regions, and test failover on a schedule.
4. Prepare customer communications. Pre-write status page and in-app messages. During the outage, silence erodes trust faster than the outage itself.
5. Know your regulator’s expectations. Incident reporting timelines and third-party risk rules differ by jurisdiction. Confirm them before you need them.

A Control Checklist for the Agent Era

1. Scope access narrowly. Prefer read-only or limited-permission credentials for any agent connection.
2. Set limits. Apply per-transaction and daily caps to agent-initiated payments, with step-up authentication above them.
3. Log everything. Keep an auditable record of what an agent did, on whose instruction, and with what permissions.
4. Plan for prompt injection. Assume content an agent reads may contain hostile instructions. Separate what an agent may read from what it may execute.
5. Clarify liability in the terms. Make clear who bears losses from agent errors, and document the customer consent flow.

What Business Customers Should Do

If you are a company that depends on a bank or fintech for payments and payroll, have a fallback. Keep a secondary bank account with a different provider, know the manual payment procedures, and hold enough buffer to bridge a day or two of disruption. If your staff are experimenting with AI agents, set a policy: no connecting corporate bank or card accounts to experimental tools without security review. The Canadian bank chiefs’ warnings are a useful prompt to write that policy now.

Frequently Asked Questions

Was customer money lost in the Google Cloud outage?

The reporting we reviewed describes service disruption at banks and Revolut but does not describe customer losses. Check your provider’s communications for specifics.

Are AI agents banned from bank accounts?

No. The reporting describes warnings from bank CEOs, not bans. Policies vary by institution and are likely to evolve.

Did Visa agree to buy Fireblocks?

No acquisition has been announced. Fireblocks said reports of $2.5 billion talks were news to the company.

Does multi-cloud solve resilience?

It can help, but it adds cost and complexity, and poorly executed multi-cloud can create new failure modes. Testing matters more than the architecture diagram.

The Bottom Line

Fintech’s glossy promise rests on layers of infrastructure and, increasingly, on autonomous software. This week showed both layers under scrutiny: a cloud region failure that touched banks and neobanks, and bank leaders urging caution over AI agents. Neither story means the sector is in crisis; investment and product launches continue. But the firms that earn lasting trust will be the ones that treat resilience and control as core product features rather than compliance chores.

Sources

• The Guardian: Google Cloud outage, problems fixed for most customers as regulators push for details
• Finextra: Banks move to limit agents’ access to customer accounts
• Finextra: Fintechs top banks and stablecoins for cheap cross-border payment, BIS research
• Finextra: HSBC launches first stablecoin
• CoinDesk: Bitcoin Core changes security rules as AI makes finding code bugs dangerously easy
• TechCrunch: Agent cloud startup Daytona hits $1B valuation

Every quarter, venture data tells a slightly different story about the same industry. The third quarter of 2026 tells one of selectivity. According to Crunchbase News, fintech startups worldwide raised $10.6 billion in July through September, a drop of 21.4% from the $13.5 billion raised in Q3 2025 and a steeper 28.4% decline from the $14.9 billion raised in the second quarter. The number of funding rounds fell even faster. Just 687 deals were recorded globally, down nearly 31% year over year and 12.9% from the previous quarter.

That deal count is the figure worth dwelling on. Crunchbase tracks quarterly fintech data back to the first quarter of 2018, and Q3 2026 is the lowest deal count in that entire window. Dollars are down, but the number of companies getting funded is down by much more. This is what a narrowing market looks like, and it matters for anyone building, buying or investing in financial technology.

The headline numbers, in context

It helps to put the quarter’s figures side by side:

• Funding: $10.6 billion in Q3 2026, versus $14.9 billion in Q2 2026 and $13.5 billion in Q3 2025.
• Deal count: 687 rounds, versus 789 in Q2 and 995 a year earlier.
• Large rounds ($100 million or more): $5.15 billion in Q3, down 43.3% from $9.07 billion in Q2.
• Smaller rounds (under $100 million): down just 5.1% from the prior quarter.

The quarter-over-quarter decline is almost entirely a story about big checks. The pullback in rounds of $100 million or more accounts for roughly 93% of the overall dollar decline from Q2. In other words, Q2 was unusually rich in mega-rounds, and Q3 did not repeat the performance. That is a different thing from a collapse in early-stage activity.

The year-over-year picture flips the emphasis. Compared with Q3 2025, funding from rounds of $100 million or more fell only 7%, while funding from smaller rounds dropped 31.4%. So large transactions have proven comparatively resilient over twelve months, and the smaller-round segment is where the longer-term squeeze has been felt. Both observations can be true at once: the biggest rounds are lumpy from quarter to quarter, yet the broad middle and early stage of the market has thinned out over the year.

A bifurcated market

The most useful framing in the Crunchbase report comes from investors themselves. Laura Bock, a partner at QED Investors, described the market as “bifurcated — AI vs. not and market leaders vs. not.” Kirsten Green of Forerunner made a similar point, describing capital concentrating in fewer, larger rounds, with infrastructure, payments and stablecoin rails attracting interest, supported by greater regulatory clarity.

Two dividing lines run through this description. The first separates companies with a credible AI story from those without one. The second separates category leaders from everyone else. A fintech that is both, or even one of them, can still raise capital on attractive terms. A fintech that is neither faces a market that has become considerably more disciplined.

Bock illustrated the point by comparing two similarly sized businesses, Ramp and Monzo, which command very different valuations. She attributed Ramp’s premium to investor enthusiasm for its AI momentum and growth trajectory. Green said much the same from another angle: a small group of companies with clear momentum command aggressive valuations, while others face greater pricing discipline. For founders, the practical takeaway is that comparable revenue no longer implies comparable valuation. The narrative around where a company’s growth is heading now carries real weight in pricing.

What investors now want to see

Green’s comments set out the new bar fairly directly. Investors want stronger evidence of performance before writing checks. In emerging categories, actual usage and momentum can matter more than revenue multiples. Ahead of a large Series B, investors want efficient growth, a credible path to profitability and stronger evidence of lasting customer demand.

That is a meaningful shift from the earlier part of the decade, when growth at almost any cost could carry a story to the next round. Today the sequence is reversed: prove the demand, show the efficiency, and the capital follows. The companies that do not make it through this filter are not necessarily failing; many are simply being asked to wait, raise smaller amounts, or find other forms of financing.

Which brings up another trend noted in the report. More startups are combining debt and equity to limit dilution. For a business with predictable receivables or lending books, blending a debt facility with an equity round can stretch the capital further and preserve ownership. It also signals to equity investors that lenders have underwritten the business’s cash flows. Expect to see more of this structure in fintech, where the underlying assets often suit it.

Where the money went: geography

The United States remained the largest fintech funding market, with startups attracting $5.38 billion, or 50.5% of the $10.64 billion global total. After that came a more varied group:

• Singapore: $1.28 billion (12.1%), heavily concentrated in Ant International’s $1.2 billion round.
• Saudi Arabia: $626.6 million (5.9%).
• India: $452 million (4.2%).
• Brazil: $352 million (3.3%).
• United Kingdom: $337.8 million (3.2%).

One detail stands out: although the U.S. led in total dollars, the quarter’s five largest funding rounds all went to companies based outside the United States. Singapore’s number is the clearest example of how a single transaction can reshape a country’s ranking. Without Ant International’s round, Singapore would not have placed second. This is a reminder that country-level fintech statistics are sensitive to individual deals, and a single quarter should not be read as a durable shift in where fintech is being built.

Saudi Arabia’s presence in third place is consistent with the broader story of Gulf capital and regulatory development drawing fintech activity, while India and Brazil continue to appear as large, populous markets with active payments and lending sectors. For readers following regional markets, it is worth pairing this global picture with local data: Crunchbase’s Q3 analysis of Latin America, for instance, shows a region where total venture investment rose 26% year over year to $1.3 billion, with Mexico’s startups raising more than Brazil’s across the first three quarters of 2026, even as Brazil retained more breadth in the number of deals.

Why infrastructure, payments and stablecoins

The categories singled out by investors are not random. Infrastructure, payments and stablecoin rails share a few features that make them attractive in a selective market. They tend to be tied to transaction volume, which gives investors observable usage data rather than projections. They can serve many end customers at once, which supports the “market leader” thesis that investors are prioritizing. And, as Green noted, greater regulatory clarity reduces one of the largest sources of uncertainty for these businesses.

For companies that sit at the application layer, such as consumer budgeting apps or niche lending products, the picture is harder. These businesses are more exposed to customer acquisition costs and competition, and they may not have the same transaction-linked metrics to point to. That does not make them uninvestable, but it does mean the burden of proof is higher.

What this means for different readers

For founders

Plan for a longer, more demanding process. With fewer deals closing, investors have room to be choosy, and they are using it. Lead with usage, retention and unit economics. If your product has a credible AI-driven efficiency or growth angle, make it concrete and measurable rather than rhetorical. Consider whether a mix of debt and equity could extend your runway without heavy dilution, and talk to lenders alongside investors.

For finance teams and buyers of fintech

A thinner funding market has procurement implications. Vendors that cannot raise their next round may cut costs, change pricing, narrow their product lines or look for acquirers. When you select a payments, expense or banking-infrastructure provider, ask about runway and funding history alongside features. Dependence on a vendor that is struggling to raise can become an operational risk. Our guides to free and low-cost financial tools are a useful place to compare options, but it is wise to keep a fallback provider in mind for critical flows.

For investors and limited partners

A quarter of falling deal count and concentrated capital supports the case for careful selection and, for some, for reserving capital for follow-on rounds in proven winners. It also suggests that valuation dispersion will stay wide. If Ramp and Monzo, similarly sized, can attract such different pricing, then benchmarking against averages is less informative than looking at each company’s specific momentum.

How to read the next quarter’s data

When Q4 figures arrive, a few questions will help separate noise from signal. Does deal count stabilize, or does it keep falling? Do smaller rounds, which have fallen 31.4% year over year, begin to recover, or does the squeeze on early-stage companies continue? Do large rounds rebound to Q2 levels, which would suggest the Q3 dip was timing, or stay near $5 billion, which would suggest a lower baseline? And does the AI-versus-non-AI split in valuations persist or narrow?

Another factor to watch is exit activity. Crunchbase has separately reported that acquirers have been buying startups from the 2021 boom era that have not raised funding in years, often at valuations well below their peaks. A funding market with few new rounds and an active acquisition market tend to go together: companies that cannot raise on acceptable terms look for buyers instead. If that pattern continues, fintech consolidation may become a bigger part of the story in the coming quarters.

Key takeaways

• Q3 2026 fintech funding was $10.6 billion, down 21.4% year over year and 28.4% quarter over quarter.
• The 687 deals recorded are the fewest of any quarter since Q1 2018 in Crunchbase’s data.
• Large rounds drove the sequential decline; smaller rounds drove the year-over-year decline.
• Investors describe a bifurcated market split by AI exposure and by market leadership.
• Infrastructure, payments and stablecoin rails are drawing interest, helped by greater regulatory clarity.
• The U.S. took 50.5% of global funding, but the five largest rounds all went to non-U.S. companies.
• Founders are being asked for evidence of usage and efficiency, and many are blending debt with equity.

Conclusion

The third quarter of 2026 does not describe a fintech funding drought so much as a funding filter. Capital is available for companies that can show momentum, efficient growth and a place at the front of their category, and it is much harder to find for those that cannot. The record-low deal count, paired with resilient large rounds, is the clearest sign of that concentration. Whether you are raising money, buying software or allocating capital, the sensible response is the same: look past the narrative and examine the evidence.

Sources and methodology: funding figures, deal counts and investor quotes are drawn from Crunchbase News coverage of Q3 2026 fintech and Latin America venture funding and its analysis of acquisitions of older venture-backed startups. Figures are as reported by Crunchbase and may be revised as additional rounds are recorded. This article is for information only and is not investment advice. Google Trends topic-level data was not available to this edition’s research.