Case study · Banking · GCP

Real-time transaction monitoring for a modern bank.

How Tenplus moved a South African banking initiative from batch processing to real-time transaction intelligence on Google Cloud and Apache Flink.

Google CloudApache FlinkStreaming pipelinesReal-time monitoringObservability
Banking · real-time streaming
From delayed batches to instant transaction intelligence.
Real timeTransaction monitoring
InstantAnomaly detection
ScalableCloud architecture
Client background

Ademola: building a modern, scalable bank.

Ademola is part of a banking initiative in South Africa focused on a modern, scalable financial system. The goal was to move away from batch-based processes and introduce real-time capabilities that support faster, safer, more reliable transactions with instant visibility into risk.

At a glance
  • Retail and digital-first banking users
  • Payment and transaction services
  • Internal risk and compliance teams
The problem

No real-time visibility into transactions.

The system relied on batch processing, so important decisions were made after the fact rather than when they mattered.

Transactions were processed with delays instead of in real time.
No immediate visibility into suspicious or high-risk activity.
Fraud detection was slow and reactive.
Risk and compliance teams could not act quickly on live data.
Pipelines were not designed for continuous streaming.
The system could not scale efficiently with growing volumes.
What they needed
  • A real-time data streaming architecture
  • Continuous processing of transaction data
  • Instant detection of anomalies and risks
  • A scalable cloud-based system
  • A foundation for future analytics and AI
Solution overview

Real-time monitoring on Google Cloud and Apache Flink.

Tenplus designed a system that processes financial transactions as they occur, enabling instant analysis and decisions.

1

Google Cloud

for scalable, secure infrastructure.

2

Apache Flink

as the core real-time stream processing engine.

3

Cloud-based data pipelines

for continuous ingestion and processing.

4

Monitoring and logging systems

for visibility and reliability.

Built with Google CloudApache FlinkStreaming pipelinesReal-time monitoringObservability
How we built it

From ingestion to real-time risk detection.

1

Step 1Real-time data ingestion

2

Step 2Stream processing with Apache Flink

3

Step 3Real-time risk detection

4

Step 4Scalable cloud infrastructure on Google Cloud

5

Step 5Monitoring and observability

Results

A fully real-time banking data platform.

  • A fully real-time transaction monitoring system.
  • Instant visibility into transaction activity.
  • Faster detection of fraud and anomalies.
  • A scalable architecture that grows with demand.
  • Improved decision-making for risk and compliance teams.
  • A strong data foundation for future analytics and AI.
★★★★★
Working with Tenplus helped us transition from a traditional banking system to a real-time architecture that supports our future vision. The team designed a scalable and reliable solution using Google Cloud and Apache Flink, which allows us to monitor transactions instantly and respond to risks faster. The platform is strong, efficient and ready to support our growth.
Head of Engineering · Ademola
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