Three years ago, in Tashkent, I witnessed a payment processor collapse during peak shopping hours after a generator failed at a local data center during a rainstorm. In Central Asia’s fintech boom, where payment adoption in Uzbekistan has reached 50 percent according to the World Bank, Western cloud-first strategies often hit regulatory walls, with public clouds frequently banned for core data. In contrast, in Western markets, cloud adoption is widespread and usually the cheapest and fastest path for fintechs.
That moment crystallized something I’d been seeing across emerging fintech markets: infrastructure decisions made under pressure rarely survive first contact with exponential growth. The business celebrates user adoption, engineers watch the systems strain, and someone has to bridge that gap.
When growth outpaces planning
Digital payments and mobile banking adoption often follow a J-curve where user numbers double, then triple. Infrastructure planning, meanwhile, moves linearly. This mismatch creates technical debt that compounds faster than most teams anticipate.
In January, your platform served 100,000 daily active users. By March, you’re at 250,000. By year-end, you’re approaching 600,000. Your infrastructure was provisioned for 20% quarterly growth. Now you’re firefighting.
User adoption can triple within 2-3 years while infrastructure planning struggles to keep pace. Engineers see this coming. Finance teams often don’t, until downtime starts costing real money.
Downtime now costs large enterprises an average of $23,000 per minute. For financial institutions, annual losses from outages alone hover around $152 million. Even in the early stages, compliance and audit requirements can amplify the consequences of downtime, turning infrastructure from a cost center into an existential concern.
Why infrastructure fails (and it’s not the technology)
Most infrastructure failures share a common thread: operational realities were underestimated, the technology works, but the ecosystem around it doesn’t.
In mature markets, Tier III data center certification means something specific and auditable. In fast-scaling regions, you’ll find facilities claiming equivalent standards without the operational muscle to back them up. Power redundancy exists on paper. In practice, generators fail during the rainy season.
A ‘three nines’ uptime commitment (99.9%) sounds reasonable until you calculate the math. That’s still almost nine hours of acceptable downtime per year. For a payment processor, that window might swallow an entire payroll cycle or settlement period. ‘Four nines’ brings you down to under an hour annually, but few local providers can deliver that consistently.
You need physical access to the equipment at 2 AM when something breaks. Some facilities have excellent uptime but complicated entry procedures. Others have 24/7 access but questionable physical security. Whether your team can fix problems or just watch them unfold depends on getting through the door.
Three paths CTOs take
Infrastructure decisions in fintech tend to cluster around three models. Each makes sense for specific time horizons and risk profiles.
Cloud infrastructure works well in the West, where providers are abundant and regulatory constraints are minimal. It gets you moving fast, with low upfront capital expenditure, elastic scaling, and managed services reducing your operational burden. But in Central Asia, heavy regulatory pressure can prohibit public clouds for core data, forcing fintechs to rely on local facilities or hybrid approaches even at early stages. Costs and compliance risks rise as a result.
Building your own data center inverts the equation. Full control, predictable long-term costs, and the ability to optimize hardware for specific workloads come at the price of significant capital, long deployment timelines, and the need for a team to manage infrastructure operations. Most early-stage fintechs can’t afford the upfront cost or the delay. In Central Asia, building local infrastructure is often necessary when compliance rules prevent cloud use for sensitive data.
Hybrid approaches split the difference. Critical systems and customer data live in controlled environments, whether on your own hardware or in carefully vetted colocation. Everything else runs in the cloud. This adds complexity but lets you balance control, cost, and compliance requirements. In regions with strict cloud restrictions, hybrid models often become the default even for mid-sized fintechs, whereas Western firms might only use hybrid for optimization or redundancy.
These choices naturally lead to a question of timing: when do you commit to each model? That brings us to the role of time horizons in infrastructure strategy.
Time horizons determine architecture
Your infrastructure strategy should map to your time horizon, not just your aspirations.
- Year 1: Cloud-first makes sense for most teams. You’re proving product-market fit, iterating rapidly, and potentially pivoting. Heavy infrastructure investment would be premature, so rent what you need and move fast.
- Year 3: If you’ve found traction and can project growth, hybrid architecture becomes worth the added complexity. Move core banking systems or transaction processing to a controlled infrastructure while keeping variable workloads in the cloud.
- Beyond Year 5: With sustained growth, owning infrastructure becomes financially viable. Capital expenditures are amortized across a large, stable user base, supported by operational expertise that allows you to optimize for your specific needs rather than conforming to someone else’s service model.
I’ve seen these patterns across dozens of implementations. Your mileage will vary based on the regulatory environment, available local infrastructure, and team capabilities.
Regulation shapes infrastructure
Regulatory requirements often dictate infrastructure choices even before cost or scale considerations. Data localization mandates mean you can’t simply default to the nearest major cloud region. Customer data stays in-country, often in specific facilities that meet regulatory standards. This fragments your infrastructure geographically and limits your provider options.
In Western countries, compliance typically focuses on certifications such as PCI DSS or SOC 2, which cloud providers already handle. In Central Asia, local regulations may outright ban cloud storage for sensitive data, making local infrastructure mandatory for compliance.
Uptime requirements get codified into license conditions. PCI DSS certification becomes table stakes for payment processing. Business continuity planning is mandatory and must be demonstrable in your infrastructure architecture to satisfy regulatory audits before you can operate.
This changes how you think about infrastructure. You’re designing systems that can prove compliance and survive audits first. Scalability comes second because, without regulatory approval, scale doesn’t matter.
A cloud provider’s global compliance certifications don’t always cover local requirements, so backup strategies must meet specific recovery time objectives. Infrastructure documentation, meanwhile, takes on a new role: it becomes a regulatory deliverable rather than just an internal reference.
Infrastructure as process
There’s no universal solution for fintech infrastructure. Teams that succeed treat infrastructure as something that evolves rather than a one-time decision.
You’ll probably start in the cloud, move to hybrid, and eventually might build your own facilities. Or you might not, if cloud economics work at your scale. What matters is matching infrastructure to current reality while creating flexibility to evolve.
The payment processor that collapsed during peak hours? They rebuilt on a hybrid infrastructure with owned core systems and cloud overflow capacity. It took two years and significant capital. But their architecture now aligns with their business model rather than fighting it.
Infrastructure decisions are compound: choose based on where you are, not only where you want to be. Plan for future growth but avoid overbuilding prematurely. Operational details matter more than the technology stack.
Your infrastructure should enable growth, not constrain it. But it also shouldn’t bankrupt you or expose you to unnecessary risk. Finding that balance requires an honest assessment of your current needs, a realistic projection of future scale, and a deep understanding of your operational environment.
The infrastructure that works serves your users reliably, meets compliance requirements, and leaves resources to build the product that brought you here.
