Edge Computing for Financial Services: Low-Latency Processing at the Network Edge

Edge computing brings processing closer to the data source. For financial services, this means processing transactions, analysing risk, and detecting fraud at the network edge — closer to customers, exchanges, and data sources — rather than in a centralised cloud data centre.

Edge computing is not new. Trading firms have colocated with exchanges for decades to minimise latency. But the cloud providers’ edge offerings — AWS Wavelength, GCP Distributed Cloud, Azure Edge Zones — have made edge computing accessible to a broader range of financial services firms.

Who Is This Guide For?

This guide is for platform architects, infrastructure leads, and CTOs at financial services firms evaluating edge computing. If you need to process data closer to the source for latency, compliance, or data sovereignty reasons, this is for you.

By the End of This, You’ll Know…

• Why edge computing matters for financial services beyond just latency
• How to deploy and manage edge infrastructure in regulated environments
• The regulatory considerations for edge deployments
• How to build applications that work across cloud and edge environments

Why Edge Computing Matters

Latency

The most obvious benefit: processing data closer to the source reduces latency.

• Cloud latency: 20-100ms round-trip to cloud data centres
• Edge latency: 1-10ms round-trip to edge locations
• Impact: For trading systems, 10ms of latency can mean the difference between profit and loss

Data Sovereignty

Some data cannot leave specific geographic boundaries:

• GDPR: Personal data of EU residents must be processed in the EU
• Data localisation: Some countries require financial data to remain within their borders
• Regulatory reporting: Some regulators require real-time reporting from local infrastructure

Bandwidth

Edge processing reduces the amount of data sent to the cloud:

• Data filtering: Process data at the edge and send only relevant information to the cloud
• Aggregation: Aggregate data at the edge and send summaries to the cloud
• Compression: Compress data at the edge before sending to the cloud

Edge Computing Models

Cloud Edge

Cloud providers offer edge locations that extend their cloud infrastructure:

• AWS Wavelength: AWS infrastructure embedded in telecommunications providers’ networks
• GCP Distributed Cloud: Google-managed infrastructure at edge locations
• Azure Edge Zones: Azure infrastructure at edge locations

On-Premise Edge

On-premise edge locations are infrastructure deployed at the customer’s premises:

• AWS Outposts: AWS infrastructure deployed in customer data centres
• GCP Anthos on bare metal: Google infrastructure deployed in customer data centres
• Azure Stack Hub: Azure infrastructure deployed in customer data centres

Network Edge

Network edge locations are infrastructure deployed at network aggregation points:

• Cell towers: Edge infrastructure at cellular base stations
• Content delivery networks: Edge infrastructure at CDN nodes
• Internet exchange points: Edge infrastructure at IXPs

Financial Services Use Cases

Trading Systems

Edge computing for low-latency trading:

• Market data processing: Process market data at the edge to reduce latency
• Order execution: Execute orders at the edge to minimise round-trip time
• Risk checks: Perform pre-trade risk checks at the edge

Branch Banking

Edge computing for bank branches:

• ATM processing: Process ATM transactions at the branch edge
• Video analytics: Process surveillance video at the branch edge
• Customer analytics: Process customer behaviour analytics at the branch edge

Payment Processing

Edge computing for payment systems:

• Terminal processing: Process card transactions at the terminal edge
• Fraud detection: Perform real-time fraud detection at the edge
• Offline processing: Process transactions offline when connectivity is unavailable

Regulatory Considerations

Audit Trail

Edge locations must maintain audit trails:

• Local logging: Log all transactions at the edge
• Centralised aggregation: Aggregate edge logs in a central system
• Retention: Retain logs for regulatory periods (7+ years)

Security

Edge locations must meet security requirements:

• Physical security: Secure edge infrastructure physically
• Network security: Encrypt all data in transit between edge and cloud
• Access control: Restrict access to edge infrastructure

Compliance

Edge deployments must satisfy compliance requirements:

• PCI DSS: Edge locations processing card data must comply with PCI DSS
• GDPR: Edge locations processing personal data must comply with GDPR
• SOX: Edge locations processing financial data must comply with SOX

What You Can Actually Use Today

• AWS Wavelength: Cloud edge for telecommunications networks
• GCP Distributed Cloud: Managed edge infrastructure
• Azure Edge Zones: Azure edge infrastructure
• AWS Outposts: On-premise edge infrastructure

FAQ

When should we use edge computing?

Use edge when: (1) latency requirements cannot be met by cloud data centres, (2) data sovereignty requires local processing, (3) bandwidth constraints require local processing, or (4) offline operation is required.

How do we manage edge infrastructure?

Use cloud provider management tools (AWS Systems Manager, GCP Anthos, Azure Arc) to manage edge infrastructure centrally. Apply the same security and compliance policies as cloud infrastructure.

What is the cost of edge computing?

Edge computing costs 2-5x more per unit of compute than cloud computing, due to smaller scale and distributed management. However, the total cost may be lower when considering reduced data transfer costs and improved performance.

We help financial services firms design and deploy edge computing infrastructure that satisfies latency and regulatory requirements. If you are evaluating edge computing, get in touch.