Service
Custom Rust Development
Rust development for the integration layer of banks and fintechs — ISO 8583 and ISO 20022 message processing, payment routing, and the components where memory safety and predictable performance map directly to operational concerns. A focused capability for the parts of the banking stack where Rust earns its place.
Rust earns its place in banking at a specific layer: the integration fabric. The components that parse ISO 8583 and ISO 20022 messages, route payment authorisations, broker events between systems, and handle the boundary between trusted core platforms and untrusted external input. These are exactly the workloads where Java's garbage-collection pauses, C++'s memory-safety risks, and Python's performance ceiling each become operational problems — and where Rust's compile-time guarantees and predictable runtime translate into commercial advantage. We've made Rust a deliberate capability investment to serve this specific layer, alongside our long-running expertise in the card payments and core banking platforms it integrates with.
What You Get
ISO 8583 and ISO 20022 message processing
Zero-copy parsers, validators, and transformers for the message formats card payments and instant payments run on. Comprehensive test coverage across the message specification. Suitable as embeddable libraries callable from Java via JNI or Python via PyO3, or as standalone services in your message fabric.
Payment routing and authorisation components
High-throughput authorisation routing, scheme integration, and stand-in processing where p99 latency is a regulatory or contractual obligation. Designed to integrate alongside existing platforms — not to replace them. Rust earns its place where incremental performance gain matters more than a rewrite.
Integration layer and event processing
The fabric between systems — event brokers, stream processors, message routers, and the components that sit between trusted core platforms and untrusted external input. Often the layer where Java's garbage-collection pauses and C++'s memory-safety risks both become operational problems, and where Rust's guarantees translate directly into resilience and predictable performance.
Memory-safe components for security-critical paths
Buffer overflows, heap corruption, use-after-free bugs, and data races — the categories responsible for the majority of CVEs in C and C++ banking software — are eliminated by Rust's compiler. The right tool for protocol parsers, boundary code handling untrusted input, and audit-sensitive transaction paths where a memory-safety bug is operationally unacceptable.
Incremental integration with existing platforms
Most engagements are not green-field. Rust components built to integrate with the Java, C++, or Python systems already in production — exposed via Foreign Function Interface, JNI, PyO3, REST, or gRPC. The path is incremental adoption: replace one critical component, prove the operational gain, then expand.
Production engineering practices
Property-based testing, fuzzing, undefined-behaviour detection, and CI-gated linting using the standard Rust ecosystem tooling. Dependency review against the supply-chain risk profile regulated institutions carry. The engineering controls that distinguish production Rust from hobbyist Rust.
Our Approach
Fit assessment
Honest assessment of whether Rust is the right choice. For latency-bound or memory-safety-critical workloads at the integration layer, often yes. For most CRUD systems, often no. The Java, Go, or C++ alternative stays on the table if it's the better choice for the problem.
Architecture and integration design
Component boundaries, integration points with existing platforms (FFI, JNI, PyO3, gRPC, REST), and the latency budget the Rust component must hit. Documented to a level a third-party engineering team could pick up.
Implementation
Banking-domain engineers building in Rust with the toolchain discipline regulated production requires. Property-based testing and fuzzing from day one, not retrofitted. Architectural decision records for every non-trivial choice.
Validation and benchmarking
Latency, throughput, and memory benchmarks against the workload specification. Side-by-side comparison against the system being replaced where one exists. Numbers published internally — you decide whether they meet the bar.
Production handover
Operational documentation, deployment artefacts, runbooks, and architectural decision records. Optional follow-on support during the first production incidents while your on-call team builds Rust familiarity.
Related Expertise
Frequently Asked Questions
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