UK banking is at its most profitable point in years. However, the foundations underpinning those profits are eroding particularly quickly in the United Kingdom.
Most UK incumbent banks earn returns on tangible equity (ROTE) in the mid-to-high teens, with the strongest performers reaching the twenties. In contrast, banks’ ROTE globally slipped from 12.4 percent in 2024 to 11.8 percent in 2025, despite record net income. But the UK banking sector trades at roughly a 52 percent discount to other industries on book value, showing investors remain sceptical about how durable those economics will prove.1
Three disruptions help explain the paradox. First, customer primacy—and the low-cost, sticky deposits that come with it—is shifting. Neobanks and fintechs now hold more than a quarter of UK banking relationships, up from low single digits a decade ago, and increasingly capture transactions and daily engagement, unbundling the traditional relationship between the primary account and the customer’s financial life.
Second, competition is intensifying in commercial banking as value shifts from the balance sheet to the transaction layer. More than 60 percent of UK commercial-banking revenue already sits outside lending. Incumbents increasingly risk retaining the credit relationship while another provider captures the transactions, data, and engagement from which value is created.
Third, AI changes both the speed and the economics of this competition. AI will make it easier to compare providers, switch products, and move money. For decades, banks could adopt new technology late because their most valuable customers adopted it late, too. Not so with AI, which customers are adopting far faster than previous technologies.
At the same time, digital-native competitors already operate with structurally different economics: Leading neobanks serve the same number of customers with far fewer employees than banks do. Agentic AI has the potential to widen that gap by allowing institutions to redesign entire customer journeys and operating models rather than simply automate individual tasks. Agentic AI could become the primary interface between customers and their money, automatically comparing products and sweeping idle cash into higher-yield accounts. For banks, the grace period is closing—and this time at AI speed, not banking speed.
The 2020s are likely to be a defining decade for UK banking, and the playbook is precision at speed, as outlined in McKinsey’s Global Banking Annual Review 2026. Three races will shape banks’ competitive position: securing customers and deposits, winning the commercial transaction layer, and rebuilding the cost base with AI. Each of these contests is a race against time as much as against competitors, because primacy compounds: The bank that wins the customer’s attention, transaction, or deposit first tends to keep it.
This report explores why today’s profitability masks increasing strategic vulnerability and why AI compresses the industry’s window to respond, before examining each of the three races in detail.
A profitable plateau
UK banks outperform their global peers for three reasons. Their retail funding is ring-fenced, a legacy of post-2008 reform that gives them a stable and inexpensive deposit base. Their market is concentrated in balance sheet terms, which protects spread income even as competition for the customer relationship intensifies. And, as in many Western markets, banks in the United Kingdom have recently earned higher lending margins due to rising interest rates. Between 2024 and 2025, net interest margin at UK banks rose six basis points, making the country one of only a handful of major markets, alongside the United States and Japan, where margins widened rather than narrowed.2 Beyond market factors, the strongest UK banks manage costs very effectively, boosting profitability.
UK retail banking generated around £62 billion revenue after risk costs in 2025, while commercial banking brought in about £32 billion. McKinsey Panorama forecasts both banking sectors to grow steadily at about 2 percent a year through 2030, adding around £10 billion in annual revenue after risk costs, from £94 billion in 2025 to £104 billion in 2030 (Exhibit 1) (see sidebar “More about McKinsey Panorama”). However, that stable growth masks intense competition: Valuable customers and deposits are being won and lost much more quickly than the industry’s aggregate growth numbers suggest. As a result, individual banks could perform very differently.
UK banking revenue pools are forecast to grow about 2 percent a year through 2030.
Note: Revenue after risk costs (net of loan-loss provisions). Retail and commercial segments each grow about 2% per annum from the 2025 baseline. Figures rounded to the nearest £1 billion.
The primacy paradox
A bank’s strength has always rested on primacy—the salary that lands in the account, the standing orders that follow, the inertia that holds a relationship for decades. On this traditional measure, incumbents still lead, holding primary status for 55 to 65 percent of their customers, against 15 to 25 percent for neobanks. That looks like safety. It is not. The account that receives a customer’s salary is increasingly not the one the customer uses every day. Many people leave their paycheque with an incumbent because changing payroll arrangements is inconvenient, then move spending money to a challenger soon after payday for a better product. The incumbent keeps the salary deposit; the challenger becomes the bank customers rely on day to day.
That means the definition of primacy is shifting beyond the salary deposit to include engagement primacy, built on daily mobile app usage. Traditional primacy, built on direct deposit of the customer’s salary and the bank’s share of the customer’s total balances, still favours incumbents. But the underlying relationship is changing: The share of customers receiving their salary into their primary current account was essentially unchanged between 2023 and 2025, while transaction primacy fell around two percentage points and digital primacy around six points (Exhibit 2). On the measures that predict the future, challengers are ahead. Revolut, for instance, reports 75 million total users, of which 19 percent self-report as primary, up from 11 percent in 2023.3
Customers still see incumbents as their primary bank, but not necessarily as their everyday bank.
1Self-reported primary-bank status among current-account holders.
The distinction matters because engagement primacy now determines who owns the data, the customer relationship, and ultimately the opportunity to cross-sell. Financial institutions are also experimenting with the role of physical presence and its potential relationship to primacy (see sidebar “The role of physical presence in building trust and engagement”).
The customer has already unbundled the bank. Using multiple financial institutions is the norm. Neobanks and fintechs hold around 27 percent of all UK banking relationships (defined as an active customer account with a provider; one customer can hold several), up from low single digits a decade ago.4 AI agents could accelerate that trend by making it easier to select the best provider product by product, with no allegiance to any single institution.
The same paradox is even more pronounced in commercial banking, where primacy is more valuable and changing hands more quickly. Corporations, institutional investors, and financial sponsors report that 12 to 25 percent of their annual banking wallet is being reallocated to different providers each year, according to a global McKinsey survey.5 In business banking, primacy is won early, at company formation, and then reinforced through the daily flows of payments, expenses, payroll, and liquidity, rather than through lending. It is precisely this transaction layer that challengers target first. Monzo Business—which is scaling quickly, reaching one million customers in just six years—ranks first in Great Britain on a survey of business banking service quality by the UK’s Competition and Markets Authority. Meanwhile, embedded-finance platforms and software providers are increasingly positioning themselves between banks and their business customers. As a result, incumbents might keep the credit relationship yet lose the daily customer interaction—and with it the transaction data and engagement that will shape the next decade of revenue growth.
Execution speed and certainty rank among the top three reasons corporate clients choose their primary bank, behind only price.6 Commercial banking clients most often cite a better digital platform, followed by pricing and more responsive relationship managers, as reasons to switch banks. One fast-growing regional trade bank illustrates how banks can turn execution into an advantage. It rebuilt its trade-finance journeys around four levers: speed, structure, simplicity, and smarter decision making. Letter-of-credit issuance times fell from more than six hours to under 30 minutes, while hedging costs were cut in half.
The economics of primacy compound. Serving as a customer’s primary bank makes an institution three to four times more likely to be considered for the next product and roughly twice as likely to cross-sell one.7 The bank that owns the everyday relationship captures a disproportionate and compounding share of lifetime value.
UK neobanks have evolved from loss-leading challengers into profitable competitors, demonstrating that digital-first models can acquire customers and deposits at scale (Exhibit 3). The question remains whether those economics can translate as challengers move deeper into capital-intensive lending.
UK neobanks have crossed the threshold from niche challengers to scaled, profitable competitors.
Note: Revenue share is a reported range. Deposits grew ~5×, from ~£15 billion in 2020. 2025 profits of >£1.2 billion are compared with ~£250 million of combined losses in 2020. Based on reported or estimated data for 8 leading UK neobanks.
Leading neobanks are now expanding into incumbents’ core businesses, just as incumbents are trying to replicate challengers’ engagement levels and cost economics. Revolut secured a full UK banking licence in March 2026, giving it deposit funding and a balance sheet, and is moving into incumbents’ most valuable profit pools, including the roughly £1.7 trillion UK mortgage market and private banking services targeting affluent and high-net-worth clients. Incumbents still hold a structural edge in mortgages, consumer lending, and insurance and protection products, but these business areas are becoming contested. Revolut spent years and considerable capital to acquire deposit funding, capital, and credit risk models built on decades of performance data, as well as the permissions to lend at scale. A balance sheet without engagement, though, is a utility. The edge only pays if the bank also owns the relationship that originates the business.
Incumbents are under pressure from both ends of the market. International banks are investing to gain share at the high end, while neobanks continue to erode share in the mass market. But incumbents are not standing still. Lloyds Banking Group, for example, ran about 50 gen AI use cases in 2025, delivering roughly £50 million in reported financial benefits. The bank, which cut income verification on mortgages from several days to seconds and reduced current-account onboarding from days to about seven minutes, is targeting around £100 million of financial benefits in 2026.8 NatWest this year became the first UK bank to launch an app in ChatGPT, allowing consumers to explore mortgage options directly on the platform.9
A window is closing, and speed is crucial
Previous waves of technological change in banking unfolded slowly enough to give incumbents substantial time to respond. In the past, banks’ most valuable customers, who were older and wealthier, generally adopted new technology slowly, meaning banks were able to preserve profitability while catching up. The internet and the smartphone changed how Britain shopped years before changing how it banked.
AI is different because adoption is both faster and broader than in previous technology waves (Exhibit 4). In the United Kingdom, 57 percent of consumers already use AI tools about three years after the launch of the first such tools. Mobile banking, in comparison, took roughly a decade to reach the same milestone, with 57 percent of UK adults using it in 2021.10
Customers have adopted AI much faster than previous technologies.
AI removes much of the friction that has historically protected incumbents in processes including onboarding, know-your-customer (KYC) regulations, affordability verification, credit and mortgage decisions, servicing, and disputes. Incumbents can build AI agents, too, but legacy technology, slower delivery cycles, and more complex operating models make it harder to move at the pace of digital-native competitors.
The most immediate consequence is disintermediation, and it strikes deposits directly. Today, many customers leave cash where it is because comparing rates, switching accounts, and moving money all require effort. Agentic AI drastically lowers those frictions. An AI assistant can continuously compare savings rates and recommend better products. Eventually, AI agents may be able to automatically move idle balances to higher-yield accounts. For banks, the economics are significant. If just 5 to 10 percent of balances moved this way, deposit profits could fall by 20 percent or more.11
Savings balances are likely to move first because they are already highly sensitive to interest rates, but there is a bigger prize for agentic sweeping: non-interest-bearing current-account balances, which provide banks with their cheapest and stickiest source of funding.12 The same dynamic is starting to emerge in corporate treasury. Tokenised treasury products let treasurers earn yield on idle cash rather than leave balances with the bank.
When consumers ask where to save or borrow, large language models are increasingly directing them to digital-native lenders over incumbents. Already, 25 percent of UK consumers are using gen AI at least monthly for financial tasks, a measure rising to 59 percent for high-income individuals (Exhibit 5).13 We estimate that disintermediation, if left unaddressed, could shrink global bank profit pools by around $170 billion, or 9 percent, over the next decade, enough to push average returns below the cost of capital.14
AI awareness and frequency of usage for financial tasks increases with income.
1Question: What is your awareness/use of gen AI tools? Respondent answers: "Heard of them but don't use them," "Use them occasionally," or "Use them frequently."
2Question: What is your awareness/use of gen AI tools? Respondent answers: "Use them occasionally" or "Use them frequently."
3Question: How often do you use gen AI tools for banking or financial-related activities? Respondent answers: "Very frequently (once a week or more)" or "Occasionally (once or twice a month)."
Technology that threatens banks also offers their best defence. AI can remove the frictions holding customers and deposits in place. It can also rebuild the economics of banking, enabling productivity gains. Over time, tokenised deposits and stablecoins could accelerate these shifts by making money itself more programmable, although their impact—like agentic deposit sweeping and AI-led financial advice—will depend partly on evolving regulation. The Bank of England’s Prudential Regulation Authority has identified innovation in deposits, e-money, and regulated stablecoins as a supervisory priority.15
Trust remains the incumbent’s strongest advantage, but it is perishable. Among AI users in the United Kingdom, 64 percent would trust their primary bank most to offer AI services, against 16 percent for a major technology company and 8 percent for an independent fintech. Yet 49 percent would consider a third-party financial AI service if their bank offered none.16
Trust creates an opening, not a guarantee, and AI won’t necessarily favour digital-native challengers. Banks that move quickly to build on that trust can turn AI from a threat into their sharpest tool. The proof points already exist, from Lloyds’ gen AI portfolio to the gains observed when banks rewire a single relationship management workflow end to end.17
Incumbents bring advantages including large tech budgets, extensive proprietary data, established customer relationships, and experience deploying technology within a highly regulated environment. AI could disintermediate banks, or it could strengthen incumbents able to combine trust, proprietary data, regulatory capability, and investment at scale. The outcome depends on which financial institutions can become a trusted AI interface for customers.
The three races ahead for UK banks
To compete in an AI-driven market that could accelerate unbundling, UK banks have three areas to focus on: securing customers and deposits, winning the commercial transaction layer, and rebuilding the cost base with AI.
Race one: Securing customers and deposits
Gaining customer primacy and deposits is the same challenge: The provider that wins customers’ everyday attention is better positioned to retain and attract their money. Banks need to compete on two fronts—winning the everyday relationship and defending the deposit base.
Win the everyday relationship. Banks need to become the customer’s default financial interface, building habits that generate the data, trust, and attention that underpin future product sales.
- Make the app a daily habit. Incumbents can turn the banking app into an active financial companion offering real-time cash flow insights, bill alerts, subscription and duplicate-charge detection, automated savings, and financial prompts triggered by life events such as starting a new job or moving. The objective is not simply a better digital channel but ownership of the customer’s spending data and payment flows.
- Build a loyalty and engagement mechanism that works. Banks have two ways to reward customer engagement. Loyalty programmes reward salary deposits, tenure, and product depth across credit, mortgages, wealth, and protection. Subscriptions, by contrast, package immediate, everyday benefits for a recurring fee, independent of balance sheet usage or product bundling. Revolut illustrates the potential: Subscriptions now generate 16 percent of group revenue, a rapidly growing revenue stream at 67 percent year on year.18 Banks should give each model a defined role by customer segment rather than fund both as undifferentiated propositions.
- Own the agent interface. Banks need to build a trusted, in-house conversational agent that proactively provides guidance on everyday financial decisions, including budgeting, saving, and refinancing. Today, 71 percent of UK banking AI users turn to general-purpose AI tools such as ChatGPT and Gemini for financial tasks, while only 45 percent use bank chatbots for the same purpose.19 Banks must compete for this interface while employing generative-engine optimisation (GEO) to ensure their products are represented when customers ask AI for advice.
Defend the deposit. The goal is no longer simply to retain deposits but to keep customers’ money within the bank as it shifts between savings, investments, and advice.
- Prepare for sweeping and yield seeking. Agentic AI is expected to increasingly move idle retail balances into higher-yield products, while corporate treasurers are already shifting excess cash into tokenised treasury and cash-equivalent products. As tokenised deposits and stablecoins mature, banks will need to compete for deposits that have historically remained in place through inertia.
- Turn deposit outflows into wealth inflows. Over the next decade, an estimated £500 billion to £700 billion of mass and affluent savings could migrate from deposits into investments, part of a UK cash pile exceeding £2 trillion. For instance, an estimated seven million UK adults hold £10,000 or more of investible assets entirely in cash.20 Britain has a chronic advice gap, with only around 9 percent of adults receiving regulated advice last year, against roughly a third in the United States, and banks capture less than a quarter of the wealth distribution pool. The best positioned banks will be those that keep assets leaving the balance sheet within the franchise by converting deposits into assets under management. Rather than viewing this migration as a threat, they can turn it into their largest organic growth opportunity: Wealth is the fastest-growing retail pool, at around 7 percent a year, while savings revenue is declining.
Winning this race requires one accountable executive, a customer-and-deposit P&L, and shared metrics for engagement primacy and assets retained. Banks can explicitly model segment-level retention and migration economics, including the margin trade-offs as deposits move into wealth, and be willing to accept near-term cannibalisation to retain the customer relationship. In the next 12 months, banks can focus on closing the engagement gap in the core app, stemming the most vulnerable deposit leakage, and establishing targeted subscription and loyalty propositions. Over the next three years, the opportunity is to make the bank’s AI agent the primary interface for guiding customers to products within the franchise and deepening engagement.
Winning the customer relationship secures the funding base. The next challenge is to capture the transactions that generate an increasing share of value—a contest that is playing out most visibly in commercial banking.
Race two: Owning the commercial transaction layer
Commercial banking is increasingly won through transactions, not lending. As profit shifts away from the balance sheet and towards transaction services (cash and liquidity management, corporate treasury, domestic and cross-border payments, foreign exchange, and payroll), the institution that owns a business’s daily financial flows owns the relationship. For example, 67 percent of large corporations cite transaction banking as a primary reason they engage their banks.
Incumbents still lead UK transaction banking, but challengers are competing from several directions. Adyen, Revolut Business, Stripe, Wise, and embedded-finance platforms are expanding beyond payments into broader financial services, while software providers increasingly sit between banks and their customers. Challengers such as Tide are particularly astute at solving pain points unique to small, new businesses, including digital tax filing and a commercial card offering suited to them (via a partnership with Capital on Tap). At the other end of the market, international banks continue to compete for the largest corporate relationships. The result is a market in which incumbents risk retaining the lending relationship while losing the transaction layer that generates value.
At the top of the market, transaction opportunities are also increasingly aligning with growth sectors and trade corridors. UK investment is concentrating in areas such as advanced manufacturing, clean energy, defence, and life sciences, while a small number of corridors account for most UK goods trade. UK companies also face a distinctive currency challenge. For many, the first move overseas brings their first material foreign-currency exposure—and an immediate need for hedging (unlike non-UK companies expanding within the euro area or across markets where the dollar predominates, which can often grow internationally before encountering the same need). Banks that organise coverage around these flows can combine financing, payments, trade finance, and hedging earlier in a client’s expansion.
Competition is also intensifying at the intersection of commercial, investment, and private banking. Several UK and global banks have launched investment-banking teams focused on the midmarket segment, prompting incumbents to defend their UK midmarket corporate relationships. For entrepreneurs, the connection to private banking is equally important. A corporate relationship can ultimately lead to a significant personal-wealth relationship following a business owner’s exit. Commercial banks that manage these businesses separately risk losing both the advisory mandate and the wealth that follows it.
The following priorities are particularly important for UK banks:
- Win businesses at formation and solve the problems that matter most. Banks can integrate accounts, payments, cards, and expense management into the company-formation journey, then excel at a few recurring needs, such as tax payments, supplier management, and working-capital forecasting. Each problem solved strengthens the relationship early, before a competitor becomes embedded.
- Own transaction data and defend operational liquidity. Banks should treat payments, foreign exchange, working capital, trade, hedging, and treasury flows as strategic assets, rather than functions to be ceded to other platforms. Continuous transaction data allows banks to anticipate liquidity and capital needs, offer timely advice, and protect corporate deposits from yield-seeking treasury products (Exhibit 6).
- Build specifically for the midsize business opportunity. Midsize companies need more than scaled-up small-business banking or simplified coverage for large corporations. To serve these clients, banks can combine cash forecasting, short-term liquidity investments, foreign exchange, trade finance, and working-capital support in a digitally enabled service model. Relationship managers can then concentrate on advice and execution rather than internal coordination.
- Organise coverage around growth sectors and trade corridors. Banks can align relationship-manager and product coverage with the sectors and corridors where UK investment and trade are concentrating, rather than relying principally on revenue bands and branch geography. Sector and corridor expertise allows banks to shape a client’s financing and transaction structure before a formal tender, bundling payments, letters of credit, guarantees, supply-chain finance, and hedging around the client’s expansion.
Combining internal and external data helps banks identify high-growth small businesses earlier, and tailor support sooner.
Note: Third-party data use requires customer consent and appropriate privacy, competition, and data-sharing controls.
Over the next 12 months, commercial leaders should assign clear ownership of the client wallet across lending, payments, foreign exchange, and liquidity, and tie incentives to transaction share. The roughly £250 billion of undrawn facilities UK banks already provide can serve as a way to win more transaction and execution flows, rather than provide liquidity while competitors win the next mandate. Over the next three years, banks can build deeper client relationships by winning companies as customers from the point of incorporation, partnering with software and treasury platforms to access transaction-level data, and focusing frontline capacity on higher-value, customer-facing advice and execution rather than internal coordination.
Race three: Rebuilding the cost base with AI
UK incumbents cannot win the first two races on their current cost base or their current delivery model. The squeeze is already visible in the global numbers: Revenue margins fell from 0.97 to 0.94 percent of balances in 2025, and returns held only because costs fell faster still, from 1.31 to 1.23 percent of assets. As interest rate tailwinds fade and competition intensifies, holding today’s returns depends on keeping costs falling faster than margins.21
The gap between incumbents and challengers is structural, not incremental (Exhibit 7). Leading neobanks operate with about 200 to 250 full-time employees per million customers, compared with around 700 to 1,100 for large incumbents and 1,200 to 1,350 for smaller incumbents. Revolut nearly tripled its customer count while reducing cost to serve per customer from about £25 in 2022 to roughly £21 in 2025.
Leading UK neobanks require far fewer retail employees to serve the same number of customers.
Note: Bars rise from zero; the coloured band shows the estimated range across selected banks. Customer and FTE reporting perimeters differ.
The difference reflects more than neobanks’ lack of traditional branch networks. It reflects fundamentally simpler operating models. Commercial relationship directors at UK and European incumbent banks spend an estimated 65 to 75 percent of their time on nonsales activity. And UK branches sell far less than European peers (around 43 core sales annually per full-time employee, against roughly 70). The global banking industry has spent more on technology than the next four sectors combined and still ranks among the worst on productivity growth.
AI offers the chance to reset those economics, but only if banks reimagine the operating model rather than simply automating existing processes (Exhibit 8). Used as a copilot beside a banker, gen AI can lift productivity by perhaps 1.2 times. Agentic AI, where humans supervise multiagent workflows, has the potential to boost productivity as much as 20 times in supervised digital-factory workflows, based on McKinsey forecasts. Across European banking, agentic operating models could reduce cost-to-income ratios by 15 to 20 percent.22 Although no bank today has achieved a 20-fold productivity boost thanks to agentic AI, the results so far are encouraging. In frontline relationship-management teams where banks have rewired a single workflow end to end by shifting certain tasks to AI agents,23 they have observed a 20 to 40 percent lower cost to serve and ten to 12 hours a week of capacity returned to each banker.24 Pioneers of both internal and customer-facing AI could lift ROTE by up to four points by 2030; slow movers risk seeing lower profits due to pricing pressure and disintermediation.25
Different types of innovation require different organisational setups and speeds.
In corporate and investment banking, exception-heavy workflows—including onboarding, KYC checks, trade controls, collateral, settlement, and corporate actions—have proved difficult to automate with rules-based systems. Planner, specialist, and verifier agents can coordinate these workflows end to end while maintaining appropriate points of human oversight. Speed cannot come at the expense of risk and resilience. The Bank of England’s Prudential Regulation Authority expects models used in regulated decisions such as credit risk and KYC checks, AI-based or not, to remain fully explainable, traceable, and subject to continuous validation. Banks that move fast to implement agentic workflows need to stay on top of related governance and monitoring issues. Specialisation matters: Agents designed for narrow, well defined domains, such as a specific trade product or onboarding document type, outperform general-purpose assistants. Orchestrated across an end-to-end workflow, these specialised agents can help compress corporate onboarding from weeks to days, turning speed from a point-in-time advantage into a repeatable operating capability.
Rewiring the operating model with agentic AI extends beyond customer-facing operations. Banks can also use supervised agents to build products, write software, and modernise technology faster. That is what makes it possible to compete on AI timescales rather than traditional banking transformation cycles.
Banks can focus on the following steps:
- Industrialise what works. Move beyond pilots by scaling proven use cases in servicing, operations, onboarding, and the relationship manager workflow.
- Redesign work around agents. Rebuild end-to-end customer journeys, such as onboarding, KYC, and credit around supervised agents, instead of automating yesterday’s processes (Exhibit 9). Apply the same model to product and technology delivery.
- Scale quickly and safely. Implement AI governance alongside AI deployment, ensuring models used in regulated activities remain explainable, traceable, and continuously monitored while managing AI costs. As agentic AI scales, establish AI financial operations capabilities to monitor usage, optimise model routing and inference costs, and ensure productivity gains translate into sustainable economic value rather than escalating consumption.
AI creates the greatest value when banks redesign journeys, not simply automate individual tasks.
Note: Named proof points use public company disclosures.
The priorities outlined in the three races also shaped our conversations with leaders in the banking industry (see sidebar “Four questions for UK bank executives to ask themselves”).
UK banks are on stronger footing than many global peers, and the advantages that matter most are still theirs to lose: the trust customers place in their bank, the strength of the balance sheet, and profits solid enough to fund the rebuilding. But strength is not permanence. The most successful banks will be the ones able to combine the advantages of incumbents—funding, risk capabilities, scale, and trust—with the engagement, speed, and operating economics pioneered by digital challengers.
