How AI Will Transform Fintech In 2026
Summary
Fintech has moved from a startup category into the operating fabric of financial services, but its capital cycle remains brutally seasonal. About 25% of venture dollars flowed into fintech during the mid-2020-to-early-2022 “big EDM pumping summer,” followed by “basically 0%” from the second half of 2022. David Haber places the current cycle in “early to mid-spring”: stronger survivors, new startups, and lingering snow in lending and the broader economy.
The first fintech wave solved access; the next must improve the underlying financial product. Digitization can now produce 30 mortgage offers in an hour or a Rocket application in five minutes, but, as Perret put it, “We’ve made it digital. We haven’t necessarily made it excellent.” Cash-flow-informed underwriting, better fraud controls, embedded finance, and full-stack product bundles are the next value pools.
AI’s clearest near-term institutional role may be automating labor rather than launching autonomous consumer finance. Haber sees financial institutions moving from defensive, in-house development toward outside software that “can actually do the work” across compliance, risk, servicing, treasury, and trading. Voice agents operating in 50 languages illustrate the new economics: “The TAM is largely labor.”
Consumer financial agents remain a trust problem disguised as a technology opportunity. Perret wants an app that automatically routes his paycheck among expenses, high-yield savings, and investments, yet doubts mainstream users will accept unexplained money movement: “Where’s my money? What’s going on?” Plaid’s strategy is infrastructural—let users safely connect data and authorize actions, then observe emerging behavior while watching for new risks.
AI is already scaling the adversary faster than the defense. Financial fraud is growing 18% to 20% annually, and Perret’s bleak 2026 call is that “the mouse is winning right now,” even if the cat eventually prevails. AI has replaced the human factories described in some pig-butchering operations, while Plaid’s Protect combines bank, device, and cross-network behavior to score users, accounts, and actions.
Crypto’s mainstream path runs through familiar financial behavior, not necessarily a wholly separate system. Perret framed speculation, prediction markets, saving, investing, and spending as durable consumer desires whose form factors change. Haber expects some convergence between core financial services and stablecoins such as USDC, while Perret was not sure crypto would merge with banks; Haber left room for its more decentralized frontier.
Plaid’s next leg rests on products that became possible only after its network reached sufficient scale. Protect and the income-and-expense-based Lens Score are positioned as major 2026 drivers, following an 11-to-13-year journey that included paperwork to sell to Visa, the deal’s reversal, fintech winter, and several “refounding” moments. Perret argues the downturn—not the boom—created the discipline and data foundation for faster product development.
Deep dive
1. Fintech survived winter by becoming broader and sturdier
Perret’s cycle starts with 2018-19 as “late spring,” followed by COVID’s initial freeze and then an abrupt “big EDM pumping summer” from mid-2020 through early 2022. Haber’s marker for the mania: roughly 25% of all venture dollars went into fintech; by the second half of 2022, the share was “basically 0%.”
The host linked both sides of the swing to the rate cycle. He said zero-rate capital drove lending and origination growth, while higher rates shifted the revenue mix toward deposits and float. He cited SoFi, LendingClub, Square—which he thought had obtained an ILC charter—Robinhood, and Mercury as examples of fintech companies moving toward full-stack financial services or generating significant revenue from deposit flows.
Haber conceded that 2021 carried too much euphoria; Perret countered that it was “the exact right amount of euphoria” and only the pullback was wrong. His serious defense: apps growing 25% a month genuinely looked like excellent venture investments, even if stimulus and “helicopter money” made that growth unsustainable.
The washout saw many fintech companies die or shut down, with lenders especially closing up shop or merging. It also pushed surviving point-solution companies to add lending, investing, cards, and accounts around their original wedges. “The winners became even more so the winners.” Haber’s scale check included Robinhood at roughly $100 billion, SoFi at $35 billion, Affirm at $20 billion, Revolut at $75 billion for new investors, and Nubank at $100 billion in Brazil.
2. Digitization solved access without fixing financial logic
Perret’s verdict on fintech’s first era is deliberately qualified: “We’ve solved the access problem”—not everywhere, but broadly. Someone in his one-bank hometown can now solicit 30 mortgage offers online within an hour or finish with Rocket in five minutes. The industry transported bank products onto screens; it did not redesign every product.
Credit scoring is his sharpest example of the remaining defect. A new job that raises income without raising expenses makes someone a better risk, yet a traditional repayment-history file may take many years to reflect it. A more logical and intelligible score would respond to current income, expenses, and free cash flow.
Distribution has also escaped the bank-shaped box. Ford and John Deere can embed finance, while BNPL, cards, and wallets appear throughout consumers’ lives. Banks that once said they needed to become fintech companies now argue that they already are “the biggest fintech companies,” because technology has become core infrastructure.
Asked whether crypto is fintech, Perret started with behavior: consumers still speculate, predict, save, invest, and spend. Bitcoin and prediction markets such as Kalshi and Polymarket change the form factor, not necessarily the desire. Haber expects some convergence between dollar accounts and USDC wallets, while Perret was not sure crypto would merge with banks and Haber left room for crypto’s “crazy out-there stuff” and more decentralized frontier.
3. Incumbents are finally buying software that performs the work
Haber traced a cultural reversal inside financial institutions. Goldman Sachs once built even its own email client, Orbit—a revealing instance of “if the technology wasn’t built there, they weren’t interested.” The subsequent push to become fintech companies themselves, including Marcus, was followed by what Haber described as a humbling that increased openness toward the market’s best external technology.
AI makes this platform shift unusually legible at the top. Cloud adoption could sound esoteric to a bank CEO or board member; anyone can enter a prompt and intuit the potential productivity gain. Bottom-up adoption of Cursor, GitHub Copilot, and a broader ecosystem of tools is now meeting board-level pressure to improve productivity.
Haber’s investment focus has consequently moved toward software with possible network effects, sold into financial institutions. Moment has built fixed-income trading infrastructure for workflows that can still be manual: a JPMorgan wealth-management client building a bond ladder may have to select individual securities one by one, unlike in equities.
Salient’s loan-servicing and collections agents can speak 50 languages, make welcome calls and payment reminders, fully compliantly track UDAAP, and remain “infinitely patient.” This is more than a better software budget: automation opens categories previously unattractive to vendors because “the TAM is largely labor.”
4. Agentic finance must earn permission before it moves money
Haber sees AI as a possible catalyst for the old promise of “self-driving money”: products that do more than display advice and actively help users earn, save, and spend. Perret’s ideal agent would receive his paycheck, retain enough for daily expenses, sweep cash into high-yield savings, and invest a specified percentage automatically.
Perret immediately challenged his own product instinct. He is a fintech power user who understands and trusts each action; his mother might instead ask, “Where’s my money? What’s going on?” The unresolved constraint is whether ordinary consumers will understand and trust automatic money movements.
Plaid therefore wants to supply safe data links and tools that let agents take proper actions—analysis, transfers, and whatever comes next—without pretending to know the winning application. Perret’s platform doctrine: “If you build it, they will come. You just don’t know who will come and what they’ll look like.” Plaid must then observe emerging behavior, decide what to optimize, and watch for newly enabled risks.
5. Fraudsters are AI’s leading financial-services users
At a dinner, Perret jokingly answered that the biggest AI use case in financial services was “doing fraud,” then realized it was probably correct. Financial fraud is already a huge market and growing 18% to 20% annually; his 2026 prediction is further acceleration through mechanisms the industry cannot yet fully understand or predict.
His metaphor preserves the timing asymmetry: “The cat will win long term, but the mouse is winning right now.” Plaid’s Protect scores the trustworthiness of users, accounts, and actions using bank information, device signals, and behavior across the fintech companies on its network. Perret called it a first network-linked, cross-fintech, cross-bank anti-fraud tool, while stressing that it solves only part of the problem.
Pig butchering shows the difficulty of fighting fraud in which the victim is manipulated into sending money. Perret described human factories in Malaysia where people were locked in rooms sending messages to unsuspecting people; he said AI now performs that work, eliminating the need for those factories. Deepfake defenses are improving but remain early, and the hardest fraud may look like a legitimate action by a successfully tricked human.
6. Plaid’s reversed Visa deal became a refounding event
Plaid began as a project that was not yet Plaid at the end of 2012, pivoted into its current business in mid-to-late 2013, and launched publicly in 2014. Its first phase centered on account linking: connect a bank account to pay through Venmo, obtain a LendingClub loan, or access another digital financial product.
In January 2020, Plaid signed paperwork to sell the company to Visa. COVID then drove digital finance and Plaid’s business sharply upward. About a year later, Plaid and Visa decided to “part as friends,” after which Plaid raised a large up-round and continued independently.
Perret described the cultural whiplash: first persuading employees to remain energized after announcing a sale, then explaining that the expected cash would not arrive. Fintech winter created another crucible as customer growth slowed.
Product velocity rose once Plaid had enough network data to detect anomalous behavior and learned to launch products faster. Perret said he was happier in winter than during the boom, when “everything’s up and to the right” obscured differentiated execution. The downturn tested the “true believers” as fintech’s tourists chased newer trends.
7. The new spring favors disciplined builders and measurable AI
Haber places the market in “early to mid-spring”: green shoots are visible, but there is “still some snow in the background.” He said lending is better than last year but not as good as it was, and noted that a large part of consumer spending is being propped up by a small number of people. New startups look more responsible about durable markets, profitability, and growth, although AI funding excess is beginning to bleed into fintech.
Haber’s 2026 orientation remains enterprise software that performs manual institutional work. He cited Moment bringing some of the largest wealth-management platforms online, including LPL, and ModernFi building a bank-to-bank deposit marketplace that is beginning to see significant volume. Financial institutions’ growing appetite for AI is making enterprise sales cycles faster than in his earlier investing experience.
Plaid expects Protect and Lens Score to be major coming-year drivers. Lens Score rises with higher income and falls when personal expenses jump—the “logical credit score” Perret wants lenders to distribute broadly. Plaid is back to hiring, recruiting, and growing; Perret also described it as a customer-centric, “forward-deployed company” that puts engineers in front of customers and centers its mission on financial freedom.