BANKING AND FINANCIAL SERVICES
AI, data and cloud engineering for banking
A card is swiped in one country while the genuine holder sleeps in another. You have the length of an authorisation round trip to approve, decline or challenge. Get it wrong one way and you wave through a fraudster. Get it wrong the other and you decline a loyal customer at the checkout.
- Decisions made faster, more accurate, and fully accountable
- Every model decision carries a reason code and an audit trail
- No rip and replace of the core you already depend on
Ambition is not the constraint. Governed delivery is.
Financial institutions carry decades of regulated systems, fragmented customer data, and a supervisory context where every model must be explainable.
Fraud on a stopwatch
The approve, decline or challenge decision has to land inline, at transaction speed and sustained volume, without punishing good customers.
A legacy core you cannot stop
High-cost, brittle workloads run the business today, so modernisation has to happen without a big-bang risk to what already works.
Data scattered across silos
Transaction signal sits in fragments across systems, so trusted, real-time features are hard to assemble and harder to govern.
Every model has to explain itself
Fraud, credit, and monitoring models answer to model risk management. A supervisor can ask why any outcome occurred, at any time.
Manual load in KYC and onboarding
Document review, sanctions checks, and reconciliation still eat analyst hours while the audit trail has to stay immaculate.
Banking is a model-risk business before it is an AI business.
The engineering behind your banking priorities.
Explore the capabilities we bring together, from data foundations to monitored production systems.
Real-time fraud detection
Catch fraud in real time without punishing good customers. Streaming detection models tuned for precision and recall, scored inline.
EXPLORE02Conversational banking AI
Serve customers through natural conversation. Governed assistants with guardrails, escalation, and audit trails.
EXPLORE03Data and analytics
Turn scattered transaction data into trusted signal. Real-time and batch pipelines, lineage, and a governed data platform.
EXPLORE04Cloud and platform engineering
Modernise a legacy core without a big-bang risk. Incremental, strangler-fig modernisation on cloud-native foundations.
EXPLORE05Intelligent automation
Take manual work out of KYC, onboarding, and reconciliation. Orchestrated automation across rules, documents, and human review.
EXPLOREWhat this changes in everyday banking.
A suspicious payment needs a decision
Score the transaction using account and behavioural signals, then route it for approval, challenge or investigation under the bank's decision policy.
A customer needs help with their account
Retrieve relevant account or product information for an assistant, with a handoff to a service colleague when the request needs judgement or additional checks.
A lending application needs review
Bring application data and model outputs together for the lending team, with decision reasons and a route for cases that need human review.
Onboarding stalls on documents and checks
Extract required fields, support screening and assemble the evidence for an analyst to resolve missing information or flagged matches.
A payments service needs modernisation
Isolate a bounded service, validate it alongside the existing system and plan the cutover with monitoring and rollback criteria.
The answer to "why" is designed into every decision.
Fraud, credit, and monitoring models ship with documented lineage, challenger comparisons, and monitoring aligned to model risk management expectations such as SR 11-7.
Cardholder data flows are designed to PCI-DSS controls. Financial reporting workflows respect SOX control and change-management requirements. AML and KYC use cases keep the immutable records examiners expect. Human oversight gates sit on every high-impact decision.
- PCI-DSS controlled cardholder data flows
- SOX aligned control and change management
- Model risk monitoring to SR 11-7 expectations
- A reason code and audit trail on every decision
Data platforms the financial sector already trusts.
CORAS RESEARCH · FINANCIAL SERVICESReal-time
Softobiz rebuilt Coras Research's database layer: advanced indexing, efficient querying, and robust security, so analysts reach critical oil service data in real time and subscribers get timelier insights.
Regulated change is hard to hand off ticket by ticket.
Through our Global Capability Center and dedicated-team model, you get a persistent pod, ML and data engineers, MLOps, and domain leads, that learns your controls, your core, and your risk appetite.
That knowledge keeps compounding instead of resetting at every handover. You can also start narrow with a packaged fraud detection accelerator and scale from proof to platform.
Questions about banking technology delivery.
Start with one priority decision or workflow, an accountable owner and clear measures. We assess the data, interfaces, controls and exception path before defining a bounded first release.
Yes. We can isolate a bounded service, connect it through governed interfaces and validate it in parallel. The cutover and rollback plan is part of the engineering scope.
We define data lineage, permissions, reason codes, approval and escalation paths, monitoring and audit requirements around the decision. The exact controls depend on the use case and your policies.
We bring AI, data, cloud and engineering capabilities to the systems and priorities you already have. A scoped assessment establishes what should be configured, integrated or built for the institution.
Which decision costs you the most? Fraud loss, friction, or manual effort.
Tell us, and we will show you the shortest credible path to putting it into production, without asking you to rip out the core you already depend on.