RELY Q4: New leadership, AI-driven efficiency, and product expansion
Remitly closed Q4 CY2025 with momentum: revenue grew 25.7% year over year to $442.2M, beating expectations, and non-GAAP EPS landed at $0.39. Guidance stayed firm with Q1 CY2026 revenue at a $437M midpoint, ahead of consensus. Profitability stepped up as operating margin improved to 8.8% from -1.1% a year ago. Shares recently traded at $17.58, up from $13.61 pre-earnings.
Headline numbers product teams should care about
- Revenue: $442.2M vs. $427.3M est. (+25.7% YoY; 3.5% beat)
- Adjusted EPS: $0.39 vs. $0.16 est.
- Adjusted EBITDA: $88.58M vs. $51.49M est. (20% margin)
- Q1 CY2026 revenue guide: $437M midpoint vs. $429.2M est.
- FY2026 EBITDA guide: $350M midpoint vs. $310.9M est.
- Active customers: 9.3M, up 1.5M YoY
- Market cap: $2.85B
What's driving the outperformance
High-amount and very high-amount senders now account for nearly half of total send volume, with very high-amount volume more than doubling year over year. Larger average transaction sizes improved unit economics and customer lifetime value.
AI upgrades are pulling real weight. A platform-wide fraud model delivered record low transaction losses, and early signals show AI-led support interactions can match or beat human agents-reducing cost to serve without tanking CSAT. Marketing stayed disciplined with lower spend per active customer and better payback.
New products are contributing more. Flex (Send Now, Pay Later) hit 120,000 users and nearly doubled revenue sequentially. Remitly Business onboarded 15,000+ SMBs with roughly 2x consumer transaction sizes. Adoption is broad-based geographically, with standout growth in the UAE and non-traditional receive corridors.
Leadership and focus areas
Incoming CEO Sebastian Gunningham called AI a "big tailwind," reinforcing leadership's intent to scale automation across fraud, support, and operations. CFO Vikas Mehta highlighted favorable regulatory shifts and resilient customers as supports for 2026. The theme: expand product lines while holding the line on costs and operational leverage.
Product implications (what to copy, what to adapt)
- Prioritize high-value segments: Explicitly build for high-amount senders and business customers. Increase limits thoughtfully, pair with tighter risk controls, and push tailored pricing and UX.
- Make AI native to risk and support: Real-time fraud scoring at the transaction level and AI-first support can cut losses and handle volume spikes without headcount bloat.
- Design for cross-sell momentum: Flex, Business, Wallet, Card, and membership (Remitly One) form a stack. Use targeted prompts, perks, and embedded eligibility to lift attach rates.
- Constrain CAC by improving retention: Better onboarding, limit management, and proactive support outcompete brute-force marketing. Optimize LTV/CAC through lifecycle nudges, not just discounts.
- Diversify corridors and channels: Don't wait for saturation in legacy routes. Treat new geographies like products-stage-gate launches, instrument deeply, and scale where signal is strongest.
Roadmap signals for 2026
New products are moving from pilots to scale: credit, expanded Wallet and Card features, and a growing membership layer. Management expects new-product revenue to more than double in 2026, supported by cross-sell and higher engagement.
AI remains a structural lever: lower fraud losses, faster ops, and quicker iteration cycles. The mix shift toward high-amount senders and SMBs should keep average transaction values and margins trending up-if risk is managed as limits rise.
What to watch next
- Adoption and revenue from credit, Wallet, and Card features-especially cross-sell into existing high-amount senders.
- Fraud-loss rates and support costs as AI models mature. Watch CSAT/quality alongside deflection rates.
- Growth in business customers and very high-amount tiers across priority corridors (UAE and newer receive markets included).
Tactical checklist for product development teams
- Risk + RevOps handshake: Ship higher limits with dynamic risk bands, step-up verification, and per-corridor policy tuning.
- "AI by default" workflows: Route support to AI first, escalate with context to human agents, and measure resolution quality-not just handle time.
- Credit and pay-later guardrails: Use repayment models tied to historic send behavior; keep small-batch launches and daily risk reviews until cohorts stabilize.
- Cross-sell surfaces: Eligibility messaging on confirmation screens, receipts, and post-send journeys. Keep offers persistent but context-aware.
- Geographic playbooks: Treat each corridor as a mini-P&L with clear win conditions, local partnerships, and compliance checkpoints.
- Instrumentation: Track send size distribution shifts, attach rate by product, fraud-loss rate per segment, and true LTV/CAC by cohort.
If you're building similar AI-first product lines, this resource can help operationalize the strategy: AI Learning Path for Product Managers.
For the official materials and updates, see Remitly's investor relations site: ir.remitly.com. For guidance on responsible AI risk practices, the NIST AI Risk Management Framework is a solid reference point: NIST AI RMF.
Your membership also unlocks:
