Priya Jaiswal has spent years parsing how fast-growing fintechs turn momentum into durable economics. In this conversation, she unpacks Revolut’s leap to a $75 billion valuation, the mechanics behind its unusually liquid staff share sales, and the operating disciplines that enabled $4 billion in revenue with profit before tax of $1.4 billion. We explore how investor theses shaped the roadmap, why licenses in the U.K. and Mexico matter, what “super-app” means in banking terms, and the operational scaffolding required to serve 65 million users across 39 countries while aiming for 100 million across 100 countries.
Revolut is now valued at $75B, up from $45B just 15 months after winning the U.K. banking license. What concrete drivers most moved the needle—specific markets, product lines, or margin gains—and can you share cohort metrics, unit economics, and an anecdote from investor diligence that proved pivotal?
The re-rating from $45 billion to $75 billion rests on three pillars: licensing credibility post–U.K. approval, breadth of product beyond the original travel card, and global scale now spanning 39 countries and 65 million users. Investors saw the 72% revenue growth to $4 billion and profit before tax more than doubling to $1.4 billion as proof that cohorts are monetizing across multiple products, not just FX. Unit economics improved as customers added business accounts, savings, and payments—each with better contribution after fixed platform costs. One diligence moment that stood out was the focus on license sequencing; once the U.K. license was in hand, investors treated Mexico’s finalized license as evidence the playbook travels, which materially shifted confidence in the global bank vision.
You ran a fifth staff share sale and called the program one of the most liquid among private companies. How do you structure pricing, eligibility, and timing to balance employee liquidity with long-term alignment, and what hard numbers show retention, hiring impact, and secondary market depth?
Liquidity windows tied to milestone events—like this fifth sale—signal fairness without turning equity into a trading instrument. Pricing is anchored to third-party led rounds, as with the raise led by Coatue, Greenoaks, Dragoneer, and Fidelity, to avoid internal marks. Eligibility that vests with tenure aligns teams to multi-year outcomes, while timing after major regulatory or product wins protects both sides from volatility. While detailed retention figures aren’t public, the very ability to host repeated staff sales in a private company, underwritten by institutional demand, is itself a measure of secondary depth and a recruiting edge.
Revenues hit $4B in 2024, up 72%, with profit before tax more than doubling to $1.4B. Walk us through the biggest line items that drove operating leverage, the cost controls that mattered most, and how contribution margin evolved across key products and regions.
The operating leverage came from shared infrastructure supporting more products per user. Payments, cards, savings, and business services layered on a single risk and compliance stack, so incremental revenue flowed with modest cost uplift. On cost, automation in onboarding and dispute handling cut manual review intensity, and vendor consolidation in processing kept gross margins sturdy. Contribution margins rose as multi-product adoption accelerated in core markets; the same compliance backbone serving 39 countries reduced marginal costs per new region.
Coatue, Greenoaks, Dragoneer, Fidelity, NVentures, a16z, Franklin Templeton, and T. Rowe Price joined this round. What distinct theses did these firms bring, how do you operationalize their involvement post-deal, and can you share examples of boardroom debates that changed roadmap priorities?
The shared thesis was the emergence of a global financial super-app, validated by consumer and business traction. NVentures’ participation underscored the role of technology acceleration, while long-only firms like T. Rowe Price and Franklin Templeton reflected confidence in durability. Post-deal, you operationalize by aligning working groups—growth, risk, and product—around quarterly targets. One debate that often reshapes roadmaps is license-first versus product-first entry; with Mexico’s license finalized, prioritizing regulatory readiness before aggressive marketing won the day.
You operate in 39 countries and serve over 65 million users. Which two markets surprised you with adoption or monetization, what local tweaks unlocked traction, and can you share activation-to-paid funnels, NPS swings, and a story where localization directly lifted conversion?
Markets with complex fee structures can surprise on monetization once pricing transparency lands. Local tweaks—such as adapting onboarding flows to local ID norms or surfacing travel features more prominently in tourist-heavy corridors—lift conversion without heavy spend. While specific funnel and NPS figures aren’t disclosed, we’ve seen localization of support hours and payments rails materially improve activation-to-paid transition. A telling moment: enabling local language customer support in a new region triggered a visible uptick in paid plan upgrades within days.
Revolut Business hit $1B in annualized revenue in 2025. What specific SKUs and price points led that push, how did sales cycles shorten, and which acquisition channels scaled best? Please include win rates by segment, average deal sizes, and a step-by-step enterprise onboarding example.
The $1 billion annualized run-rate reflects small-business banking bundles—payments, cards, and expense management—sold as a coherent suite rather than single SKUs. Sales cycles shortened when onboarding and KYC were streamlined to match business workflows, and channels that paired product-led trials with lightweight sales assistance scaled best. While win rates and deal sizes aren’t public, adoption was strongest where integrations reduced administrative friction. A typical enterprise onboarding starts with compliance data ingestion, followed by sandbox testing for payments, staged card issuance, and go-live with role-based controls and support SLAs.
After the U.K. banking license, you finalized a banking license in Mexico. What milestones, regulatory expectations, and risk controls were critical, and how did they differ from the U.K.? Share timelines, team structure, and one operational lesson that saved time or capital.
Core milestones included local entity setup, capital planning, risk governance approval, and systems testing with the central bank. Expectations overlap—capital adequacy, consumer protection, AML—but local nuances around data residency and payment rail integration required bespoke builds. A blended team of regulatory specialists, risk, and engineering executed in waves, with compliance running in lockstep with product. The lesson: parallelizing regulatory testing with vendor integration avoided rework and saved meaningful engineering time.
You’re exploring a U.S. charter as part of the growth mission. What end-state charter path are you pursuing, what capital and compliance thresholds are gating items, and how do you phase product rollout pre-charter? Please outline a realistic 12–24 month milestone map.
The end-state is a full charter that supports nationwide banking, but pre-charter phases rely on partnerships while building compliance muscle. Gating items include capital planning that satisfies prudential standards and demonstrable BSA/AML and consumer compliance capabilities. A practical 12–24 month map starts with supervisory engagement and audits, expands product breadth under partner models, and culminates in charter application milestones. Sequencing ensures customers see steady improvements without overstepping regulatory limits.
The CFO said the model delivers “rapid growth and strong profitability.” What are the top three unit economics you monitor weekly, how do you hedge FX and credit risk, and where are margins most fragile? Share concrete thresholds you won’t cross and how you enforce them.
The watchlist is contribution margin per active customer, cost to serve per transaction, and cross-sell adoption. FX exposure is managed by matching flows and setting limits that prevent outsized single-currency risk, while credit risk is contained with conservative underwriting and portfolio monitoring. Margins are most fragile when expansion outpaces compliance and fraud controls; discipline means not launching in a market until the control stack is production-ready. Enforcement is simple: no-go gates tied to risk signoff.
Coatue said you’re building a “global financial super-app.” What’s your current definition of “super-app” in banking terms, which products are must-have versus nice-to-have, and how do you avoid feature bloat? Give examples where bundling improved retention and reduced CAC.
A banking super-app is a primary financial operating system for consumers and businesses—payments, deposits, cards, savings, and business tools in one place. Must-haves are accounts, payments, and cards; nice-to-haves become must-haves only when they tie into daily cash flow. To avoid bloat, features ship only if they deepen engagement or reduce support load. Bundling business payments with expense management, and consumer accounts with travel tools, tends to lift retention and compress acquisition costs by making the first use case immediately valuable.
From a travel card to a multi-product platform: what product sequencing rules guided you, and how did you decide kill-or-scale on new features? Share one product that underperformed, what the data said, and the exact changes that turned it around or led to a sunset.
Sequencing favored primitives—move, hold, and spend money—before layering services that ride those rails. Kill-or-scale decisions hinge on frequency of use and support friction; if a feature adds tickets without driving engagement, it’s a candidate to sunset. One underperformer type we often see across fintechs is a niche rewards module; when usage clustered among a small cohort and support spikes rose, simplifying the offer improved satisfaction and freed resources for core products. The north star: features must either increase daily utility or reduce cost-to-serve.
On operations across 39 countries, what’s your playbook for risk, fraud, and compliance at scale? Detail tooling, human review layers, and escalation paths, and provide metrics on false positives, recovery rates, and how those shifted after key machine learning upgrades.
The stack blends machine learning for anomaly detection with rule-based controls tuned to local regulations. Human review is layered—frontline analysts, specialist investigators, and a central risk committee—to prevent both over-blocking and leakage. Escalations follow time-bound SLAs, with post-incident reviews feeding model updates. While specific rates aren’t shared, upgrades typically aim to reduce false positives and improve recovery, and the breadth across 39 countries provides the training data to keep models current.
With over 65 million users today and a vision for 100 million across 100 countries, what are the bottlenecks—licensing, capital, talent, or distribution—and how will you sequence them? Please include hiring plans, partner strategies, and country launch checklists that de-risk execution.
Licensing remains the pacing item; capital follows once licenses unlock deposit-taking and lending. Talent is the multiplier—local compliance and operations hires are non-negotiable ahead of launch. Partnerships with payment networks and local banks de-risk ramp-up while the license pipeline matures. The country checklist anchors on regulatory mapping, data localization, payments integration, staffing, and a measured go-live that scales support in step with adoption.
Profit before tax more than doubled. Where did credit losses, interchange, and funding costs land versus plan, and how sensitive is profitability to interest rate moves? Walk through your stress test scenarios, hedging tactics, and the thresholds that would trigger pricing changes.
The headline is operating discipline: PBT more than doubling to $1.4 billion indicates losses and funding costs stayed within the rails of a diversified model. Sensitivity to rates exists through deposit margins and customer behavior, so scenarios test both higher and lower rate paths. Hedging focuses on balancing duration and currency exposures to keep income stable. Pricing changes are a last resort, triggered only if external shifts threaten core unit economics for sustained periods.
Customers and businesses expect speed and reliability. What SLAs do you commit to for payments and support, how do you handle outages, and what did your worst incident teach you? Share time-to-resolution benchmarks, escalation playbooks, and the metrics you track after a fix.
SLAs center on near-instant payments processing where rails allow and rapid support response measured in minutes for priority issues. Outages are handled with immediate incident command, customer comms, and staged rollbacks. The toughest incident always teaches humility: if monitoring lags or dependencies aren’t mapped, time-to-resolution stretches. After fixes, teams track stability, ticket volume, and customer satisfaction to confirm the platform is truly back to form.
Do you have any advice for our readers?
For operators, earn your licenses and your margins; one without the other won’t scale. For investors, follow the control stack—great growth stories are built on unglamorous governance. And for customers, reward products that make your financial life simpler across borders; their success pushes the industry toward better transparency and value.
