Engineering for the systems that move money — reliable, secure, audit-ready.
Banking is unforgiving — about reliability, about security, about regulatory evidence. We work inside that frame: AI-native engineers, audit-ready delivery, and modernisation that doesn’t bet the bank on a rewrite.
- Confidential first call
- Discovery inside your perimeter
- Build against evidence
- Parallel run, then a reversible switch
- Operate or hand over
Banking software fails in expensive, visible ways.
A batch that finishes late becomes a regulatory letter. A duplicated payment becomes a headline. An outage on salary day becomes a queue in every branch. So the engineering has to be conservative where it matters and modern where it pays — and the evidence has to satisfy an auditor, not just a standup. The system that holds the record is often older than the team maintaining it, and the interesting work is rarely replacing it. It is building around it at a pace the business can absorb, with the ledger left exactly where it is.
We work inside your regulatory perimeter, under your controls, with documented change management and traceability from requirement to test evidence. Environments are segregated, production access is scoped and logged, and every deploy can be traced back to the requirement that caused it and the test that proved it. Regulated data stays where your regulator expects it: on your cloud account or in your data centre, not copied into infrastructure we manage for our own convenience.
We are not a regulated entity and we do not sell a core banking system. We are the engineering partner that extends, integrates and modernises the estate around the core — channels, payments, open banking, fraud tooling, regulatory data — with engineers who write the evidence as they go. Security & compliance sets out the controls we operate under.
What we work on.
Six areas we focus on. Everything else we say no to, or partner for.
Core banking modernisation
Strangling legacy cores into composable services with measured cutover. We characterise the existing behaviour first — tests that pin what the system does today, quirks included — then move one capability at a time behind a routing layer, with a rehearsed way back at every step. No big-bang rewrites, and the cutover is designed to avoid a freeze on the change calendar. See legacy re-engineering and software modernisation.
Digital channels
Web and mobile banking, onboarding, KYC and account opening — built to the reliability a bank needs rather than campaign-site standards. That means performance budgets on the journeys that convert, offline and degraded-network behaviour designed rather than discovered, and accessibility treated as a requirement. Built with React and Next.js over service layers your product teams can move on.
Card & payments
Issuer platforms, scheme integration, real-time payments, 3DS and dispute workflows. Payments engineering is mostly about what happens when something goes wrong: idempotency keys on every instruction, reconciliation that runs continuously rather than at month end, and a settlement view that says exactly which side of the transaction is unmatched and why.
Fraud & risk
Real-time scoring, rule engines and ML-driven detection, with audit trails the regulator can read. Rules stay readable and versioned so a risk analyst can change a threshold without a release, while models are evaluated on held-out data with drift monitoring in production. Built with our AI & machine learning and event-streaming practices.
Open banking
PSD2 and Open Banking APIs, consent management, TPP onboarding and FAPI-grade security. Consent is treated as a first-class record with its own lifecycle — granted, scoped, expiring, revoked — because that record is what you will be asked to produce. Rate limiting, mutual TLS, token binding and per-TPP observability come as part of the build, not as a hardening phase afterwards.
Regulatory reporting
BCBS, FINREP / COREP, MiFID, KVKK and GDPR — pipelines that auditors actually understand. Lineage is captured from source system to submitted figure, transformations are versioned code rather than spreadsheet steps, and reruns of a prior period reproduce the number that was filed. Built by our data engineering practice on governed models.
What we build, in detail.
The core stays. The dependency on it does not.
Nobody gets promoted for replacing a working core, and nobody survives breaking one. So we do not propose it. We characterise the capability we want to move — payments initiation, customer data, product catalogue — with tests written against the live system’s real behaviour. Then a routing layer sends a slice of traffic to the new service, both paths run in parallel until their outputs match record for record, and only then does the old path retire. Each capability is a small, reversible programme rather than one enormous one, and the business keeps shipping while it happens.
- Characterisation tests first — the legacy behaviour is documented in code before anything moves
- Parallel run with record-by-record comparison; cutover only after the exceptions are explained
- Every step reversible, with the rollback rehearsed in a lower environment before the change window
- 01Characterise
- 02Wrap in API
- 03Route a slice
- 04Parallel run
- 05Retire path
One capability at a time
Payments that still reconcile at the end of the day.
A payment is not a request, it is a promise with a lifecycle. Instructions arrive with an idempotency key, are validated and screened, sit in a state machine that survives a restart, and land on a ledger entry that carries the scheme reference back to the original message. Reconciliation runs against the clearing file continuously instead of waiting for month end, so an unmatched item is a queue with an owner and an age, not a discovery. Every transition is an event on the log, which is what makes a dispute answerable months later.
- ISO 20022 and scheme messages mapped to an internal model, with the raw message kept for evidence
- Idempotency and exactly-once outcomes over at-least-once transport — see Kafka & event-driven
- Continuous reconciliation with an exception queue: owner, age and reason on every unmatched item
Consent is a system, not a checkbox.
Open banking looks like an API programme and behaves like a consent programme. The endpoints are the easy part. The hard part is a consent record with a life of its own — what was granted, to which third party, over which accounts, for how long, and how the customer withdrew it at two in the morning from the mobile app. We build the gateway and the consent store as one design: strong client authentication, per-TPP rate limits and quotas, mutual TLS, and an audit log that reconstructs any access after the fact. The core sees governed, throttled traffic and nothing else.
- Consent lifecycle as a first-class record — granted, scoped, expiring, revoked, with the evidence
- Per-TPP onboarding, certificates, quotas and observability, so one integrator is isolated from another
- The gateway isolates the core: no third party holds a direct dependency on a system of record
Risk rules an analyst can change and an auditor can read.
Fraud and AML logic dies when it lives in code that only two engineers understand. We separate the two halves: the decision engine is a versioned, testable artefact a risk analyst can edit, simulate against last month’s traffic and publish with four-eyes approval; the model layer supplies scores as inputs, evaluated on held-out data and monitored for drift. Every decision keeps the rule version, the score, the features that mattered and the actor who released the change. When the regulator asks why a payment was held in March, the answer is a query rather than a project.
- Rules as configuration with simulation on historical traffic before publication
- Model scores as one input among several, not as an unexplained decision on their own
- Decision records retained with rule version, features and outcome — exportable to your GRC tooling
One programme, three sets of expectations.
A map of what moved, and what deliberately did not.
The architecture question in a bank is rarely which framework. It is which boundary you are prepared to defend for the next ten years. We draw that boundary explicitly: what we build and hand over, what stays with the vendor core, and where the contract between them lives. Documentation, tests and infrastructure as code come with the estate, so the work is transferable to your team or another supplier.
- An explicit build / buy / leave-alone line, agreed before the first sprint
- Everything as code — infrastructure, pipelines, environments — kept in the repository
- Exit is designed in: no knowledge that lives only in our heads
The run matters more than the launch.
Systems that move money are judged on ordinary days. We size for the peak you actually have — salary day, tax deadline, the campaign that lands on a Friday — rehearse the failure of every dependency, and design what degrades first when something upstream is unavailable. On run contracts we operate to defined SLOs with incident cover to the hours the run contract sets, and the dashboards are shared with your operations centre rather than kept on our side of the wall. See DevOps & cloud.
- Load modelled from your real curves, not from a round number in a slide
- Dependency failure rehearsed: what degrades, in what order, and what stays alive
- Runbooks, alert policies and dashboards handed over as code and rehearsed with your team
Evidence produced as work happens, not reconstructed later.
The costly part of an audit is never the control itself. It is assembling the proof months after the fact. We generate the evidence as a by-product of delivery: requirements traced to tests, tests traced to releases, releases traced to approvals, access requests logged with their justification. Vendor-risk artefacts are ready for procurement before procurement asks, and the controls we work under are documented rather than described. We treat GDPR / KVKK as design inputs.
- Requirement → test → release → approval, traceable in one direction and back again
- Segregated environments and scoped, logged production access
- Pen-tested releases at a rhythm agreed with you, with findings tracked to closure
The estate a bank actually runs.
Core banking
Temenos, Oracle FLEXCUBE, Finacle and bespoke cores — extended and wrapped through governed contracts, not replaced by us
Card issuing & switch
Authorisation streams and clearing files matched on processor reference, with reversals and chargebacks linked to the original entry
Payment schemes & rails
ISO 20022 messaging, instant-payment rails and local schemes, with the raw message retained as evidence
Open banking & TPPs
PSD2-style APIs with consent store, strong customer authentication, mutual TLS and per-TPP quotas
Fraud & AML case systems
Scores and holds exchanged both ways; alerts land in your case tooling with the decision record attached
Regulatory reporting
Governed data models feeding FINREP / COREP-class submissions, with lineage from source system to filed figure
Identity & access
Customer identity federated across channels
Data warehouse & BI
Event and ledger feeds into Snowflake, BigQuery or your lakehouse, with Power BI models on top
What engineering discipline in banking means in practice.
- Change management with documented controls — every deploy traceable to the requirement that caused it, the review that approved it and the tests that passed before it shipped.
- Segregated environments, with production access scoped and logged. Access is requested with a justification, granted for a window, and expires by itself. No standing credentials, no shared accounts.
- Encryption at rest and in transit; HSM integration where required. Key custody stays with you, and the systems we build are designed so that we do not need a copy of production data to support them.
- Disaster-recovery drills, not just plans. Failover is exercised on a schedule against the real topology, with the recovery time measured and the gaps written down where the team can see them.
- Pen-tested releases at a rhythm agreed with you, with findings tracked to closure and retested — and threat modelling in design rather than a scan at the end. See cybersecurity.
- Audit-trail design as a first-class engineering concern. Append-only records with actor, timestamp, before and after state, retained to your policy and exportable to your GRC tooling.
- Regulatory traceability — every requirement maps to test evidence, and the matrix is produced by the pipeline rather than typed up by a delivery manager the week before the review.
- Vendor risk artefacts ready for procurement — security posture, sub-processors, data-handling model and the controls we operate under, prepared before your third-party risk team asks for them.
From a first confidential call to a system in production.
Confidential first call
One call with the engineers who would do the work. We want the constraint that makes this hard: the core you cannot touch, the audit finding from last year, the deadline set by a regulator. You leave with a written follow-up and a frame, not a proposal deck.
Discovery inside your perimeter
We read the estate: interfaces, batch windows, data ownership, controls, the change calendar. Where the system of record is involved we write characterisation tests before proposing anything. The output is a ranged scope, a team profile and the risks named in plain language.
Build against evidence
Short iterations behind your controls, with traceability from requirement to test built in from the start rather than added later. Security review and performance budgets are part of the definition of done, and the environment pipeline is built before the first feature lands in it.
Parallel run, then a reversible switch
Anything touching the book of record runs in parallel until outputs reconcile record for record. Cutover moves segment by segment inside an agreed window, with the rollback rehearsed and the exception list agreed before anyone signs.
Operate or hand over
Either your team takes it with the documentation, tests and infrastructure code, or we run it to defined SLOs with incident cover to the hours the run contract sets. Both paths are priced and planned from the start, so the decision is not made under pressure.
Frequently asked questions
Where else we go deep.
Working in banking & financial services?
Let’s talk specifics — not a generic capabilities deck. A confidential first call, then a frame, a team profile and a ranged scope.