DATA MODERNISATION · PLATFORM · FINANCIAL SERVICES
In financial services, latency is risk.
Real-time, compliant data pipelines for banks, fintechs and insurers on AWS. Fraud detection, payments processing, risk monitoring and regulatory reporting. All running on live data, not yesterday’s batch.
Real-time
Decisions replace batch latency
Compliant
Regulated data, in every region
Kafka
Apache Kafka, Confluent and Apache Flink
THE PROBLEM
Batch processing is the bottleneck between your data and your decisions
Batch-driven architectures introduce delays between transaction events and the systems that act on them. That gap is where fraud happens, where risk accumulates, and where customers experience friction. This engagement closes it, replacing batch latency with continuous, event-driven data movement across your entire financial services stack.
FINANCIAL SERVICES USE CASES
Four workloads where real-time data is not optional
FRAUD AND RISK
Real-time fraud detection
React in milliseconds, not minutes.
Stream transaction events and apply in-flight enrichment, scoring and anomaly detection. Fraud signals acted on before the transaction settles, not after the chargeback arrives.
PAYMENTS
Event-driven payments processing
Modern payment infrastructure requires continuous data flow.
Low-latency, event-driven architecture for digital payment systems. Real-time state management, idempotent processing and audit-ready event streams for every transaction.
RISK AND COMPLIANCE
Risk monitoring and regulatory reporting
Threshold breaches detected as they happen, not at end of day.
Continuously track exposures, detect threshold breaches and maintain audit-ready data pipelines. Compliance reporting built on immutable event streams, not reconstructed from batch exports.
PERSONALISATION
Customer 360 and real-time personalisation
Relevant at the moment that matters.
Real-time customer insights across channels. Live behavioural signals feeding recommendation engines and next-best-action systems without the 24-hour batch delay that makes them irrelevant.
TECHNICAL ARCHITECTURE
Built on Apache Kafka, Confluent and Apache Flink
Apache Kafka and Amazon MSK
High-throughput, durable event streaming. The backbone of every real-time financial data pipeline.
Confluent Platform
Enterprise Kafka with Schema Registry, RBAC and Confluent Control Centre for governance and observability.
Apache Flink and ksqlDB
Real-time stream processing for enrichment, aggregation, correlation and in-flight anomaly detection.
Amazon Redshift and OpenSearch
Delivery to analytical and operational stores. Historical analysis alongside real-time decisioning.
AWS Glue and Amazon S3
Schema-governed ingestion and durable event storage. The foundation for data lineage and audit trails.
Amazon DynamoDB
Low-latency operational data store for serving real-time features to decisioning systems and APIs.
Amazon Bedrock
AI and ML integration on top of the real-time data layer. Fraud models, risk scoring and personalisation.
AWS IAM and encryption
Fine-grained access control, encryption in transit and at rest, aligned to FSI security requirements across Africa and the Middle East.
BUILT FOR REGULATED ENVIRONMENTS
Compliance and audit-readiness from the architecture up
End-to-end data lineage
Every event traceable from source to destination. Schema versioning and change data capture provide complete auditability for regulators.
Schema governance
Schema enforcement and version control via Confluent Schema Registry. Data contracts enforced at the pipeline boundary, not after the fact.
Encryption everywhere
Encryption in transit and at rest across all pipeline components. Aligned to FSI security standards and regional data protection obligations (POPIA, GDPR, DIFC PDPL).
Fine-grained access control
RBAC at the topic, cluster and application level. Access policies enforced through AWS IAM and Confluent RBAC.
Immutable event streams
Audit-ready event logs that can’t be modified after the fact. Regulatory reporting built on the source of truth, not derived summaries.
Regional data governance compliance
Data stays in your AWS account. Processing pipelines designed to minimise PII exposure and enforce data minimisation at the architectural level.
DELIVERY MODEL
Outcome-driven. Agile. With knowledge transfer throughout.
01
Discovery
Source systems, data volumes, latency requirements, compliance obligations
02
Design
Architecture design, schema definitions, processing topology, governance framework
03
Integration and streaming
CDC setup, pipeline build, stream processing implementation, delivery to target systems
04
Enablement
Team training, operational runbooks, monitoring dashboards and alerting configured
05
Handover
Production sign-off, documentation and transition to Managed Event Streaming Platform
DELIVERED FOR REGULATED FINANCIAL SERVICES ORGANISATIONS ACROSS AFRICA AND THE MIDDLE EAST
NEXT STEP
Ready to move from batch to real-time?
Tell us about your current data architecture and the use case you’re trying to unlock. We’ll scope the engagement from there.