Why Finance Is Moving to the Cloud
For years, major banks and trading firms ran everything on their own hardware — private data centres, physical servers, dedicated networking. The reasons were understandable: regulatory requirements around data residency, latency concerns for trading, and security worries about multi-tenant infrastructure.
That picture has changed significantly. AWS, Azure, and Google Cloud now offer dedicated regions for financial services, compliance certifications (SOC 2, PCI DSS, ISO 27001), and performance that matches or exceeds most on-premises setups. The economics are compelling: instead of buying servers that sit idle most of the time, you pay for what you use.
Today, most new fintech companies are cloud-native, and even traditional banks are migrating workloads. Understanding cloud computing is becoming essential for anyone building financial technology.
The Three Major Providers
| Provider | Market Share | Strength | Finance Focus |
|---|---|---|---|
| AWS | ~32% | Broadest service range | Most mature financial services tooling |
| Azure | ~23% | Enterprise integration | Strong with banks already using Microsoft |
| Google Cloud | ~11% | Data and ML | BigQuery for analytics, TensorFlow integration |
AWS is the most common choice in finance, which is why we cover AWS-specific services in a separate guide. But the core concepts — compute, storage, networking, databases — are essentially the same across all three.
Core Services You Need to Know
Compute
The ability to run code. Three main models:
Virtual Machines (EC2 on AWS, VMs on Azure) — full control over the operating system. Run whatever you want. You manage patching, scaling, and availability.
Containers (ECS, EKS, Azure Container Apps) — run Docker containers without managing servers. You define how many instances to run and the platform handles the rest.
Serverless (Lambda, Azure Functions) — upload a function, it runs when triggered. No servers to manage at all. You pay per invocation, down to the millisecond. Excellent for event-driven workloads (process a file when it is uploaded, send an alert when a risk limit is breached).
Storage
Object Storage (S3, Azure Blob, GCS) — store any file, any size, at very low cost. Market data archives, backups, data lake storage. Virtually unlimited capacity.
Block Storage (EBS, Azure Disks) — high-performance storage for databases and applications that need filesystem access.
File Storage (EFS, Azure Files) — shared filesystems accessible from multiple instances.
Databases
Cloud providers offer managed versions of virtually every database type:
- Relational — RDS (PostgreSQL, MySQL), Aurora, Azure SQL Database
- NoSQL — DynamoDB, CosmosDB, Firestore
- Time Series — Timestream, or self-managed options on compute instances
- Data Warehouse — Redshift, BigQuery, Synapse — for analytical queries over massive datasets
Managed databases handle backups, patching, replication, and failover automatically. For financial systems where database availability is critical, this is significant.
The Cost Model
Cloud pricing can be surprising if you are used to fixed on-premises costs. The key models:
On-Demand — pay by the hour or second. Most flexible, most expensive per unit. Good for development and variable workloads.
Reserved/Savings Plans — commit to 1-3 years of usage for 30-60% discounts. Good for predictable production workloads.
Spot/Preemptible — use spare capacity at 60-90% discount, but can be terminated with short notice. Excellent for batch processing, data pipelines, and workloads that can handle interruptions.
The Surprise Bills
Cloud costs can escalate quickly if not monitored:
- Data transfer — moving data out of the cloud is charged per GB. Egress costs add up.
- Storage growth — logging and data accumulation is gradual but relentless
- Zombie resources — development instances left running over weekends and holidays
- Over-provisioned databases — paying for large instances that are 10% utilised
Set up billing alerts and review costs monthly. Most organisations discover significant savings just by right-sizing their resources.
Security in the Cloud
Cloud security operates on a shared responsibility model: the provider secures the infrastructure, you secure your configuration, data, and applications.
Common mistakes:
- Public S3 buckets (have caused major data breaches)
- Over-permissive IAM roles (giving services more access than they need)
- Unencrypted data at rest or in transit
- Missing audit logging
For financial applications, encryption at rest and in transit is typically mandatory, access logging must be comprehensive, and identity management needs to be robust. See our security guide for more detail.
Getting Started
If you are new to cloud computing:
- Create a free-tier account on AWS, Azure, or GCP
- Deploy a simple web application
- Set up a managed database
- Learn the IAM (identity and access management) basics
- Understand the billing console
The learning curve is real but manageable. Most of the complexity comes from the breadth of services available — the individual services themselves are well-documented and relatively straightforward once you understand the fundamentals.
Want to go deeper on Cloud Computing for Finance: Getting Started?
This article covers the essentials, but there's a lot more to learn. Inside Quantt, you'll find hands-on coding exercises, interactive quizzes, and structured lessons that take you from fundamentals to production-ready skills — across 50+ courses in technology, finance, and mathematics.
Free to get started · No credit card required