Fraud Does Not Pause Between Business Hours. Your Fraud Detection Should Not Either.
Financial fraud is growing in sophistication and volume across the region. Account takeovers, card fraud, internal employee fraud and digital channel fraud are all increasing — and the institutions best positioned to contain losses are those with real-time, cross-channel fraud detection that acts before a transaction completes, not after a customer complaint arrives.
$485
B
Estimated global losses to payment fraud in 2023 — a figure growing at approximately 14% annually as digital transaction volumes increase and fraud techniques become more sophisticated
Nilson Report Global Payment Fraud 2024
70
%
of fraud losses in African financial institutions occur through digital channels — mobile banking, internet banking and card-not-present transactions — where real-time detection is most critical
Africa Financial Crime Report 2024
60
%
of internal fraud cases in financial institutions involve employees with privileged system access — reinforcing the need for both fraud detection and access management controls
ACFE Report to the Nations 2024
The reality
By the Time a Fraud Transaction Is Reported, the Money Is Already Gone.
Traditional fraud management relies on post-transaction monitoring — reviewing transactions after they complete and then attempting to recover funds. In the context of real-time digital payments, this approach is inadequate. By the time a suspicious transaction is flagged, investigated and a recovery attempt is made, the funds have already been moved multiple times.
Effective fraud management requires detection before or during transaction completion — using behavioural analytics, device intelligence and real-time rules engines to identify and block fraudulent transactions at the point of initiation, not after the damage is done.
How fraud management works
Three detection layers that stop fraud before it completes.
Each layer addresses a distinct fraud vector — from digital channel fraud to internal employee abuse to payment card fraud.
01
Detect behavioural anomalies.
Legitimate users behave consistently. Fraudsters do not. Our behavioural analytics engine builds profiles of normal activity for every account and user — flagging deviations in login patterns, transaction amounts, beneficiary registrations and device usage that indicate account takeover, identity theft or internal abuse.
02
Apply real-time rules.
Configurable rule-based engines evaluate every transaction against defined fraud indicators at the point of initiation — velocity rules, geographic anomalies, device trust scores and cross-channel correlation. Suspicious transactions are flagged, challenged or blocked in milliseconds, before funds are transferred.
03
Manage cases intelligently.
Not every alert requires the same response. Our case management workflows prioritise alerts by risk score, route cases to the appropriate investigation team and track resolution from detection through to customer communication and chargeback management — reducing case handling time and improving recovery rates.
What we deploy
A complete enterprise fraud management stack — covering all channels and fraud types.
Deployed across your digital channels, core banking system and card payment infrastructure — providing unified cross-channel fraud visibility rather than siloed detection tools that miss fraud that moves between channels.
Digital channel fraud
- Account takeover detection and prevention
- New beneficiary registration monitoring
- Unusual fund transfer pattern detection
- Device fingerprinting and trust scoring
- SIM swap and social engineering detection
- Mobile and internet banking fraud monitoring
Payment card fraud
- Real-time card transaction authorisation screening
- Card-not-present (CNP) fraud detection
- Card testing and enumeration attack detection
- Geographic velocity and cross-border anomaly detection
- 3D Secure integration for e-commerce transactions
- Chargeback and dispute management workflows
Internal fraud
- Employee transaction behaviour monitoring
- Unusual account access pattern detection
- Teller and branch operation anomaly detection
- Collusion pattern identification
- Privileged user transaction monitoring
- Integration with PAM for comprehensive insider threat coverage
Case management
- Risk-scored alert prioritisation and routing
- Automated case creation and assignment workflows
- Investigation documentation and evidence management
- Customer communication and authentication challenge workflows
- Recovery and chargeback management
- Fraud loss reporting and trend analytics
Delivery framework
Three stages. From fraud exposure assessment to real-time fraud prevention.
01
Assess
Fraud exposure & channel risk assessment
Your current fraud losses, detection capability and channel risk profile are assessed. High-risk fraud scenarios specific to your institution, customer base and transaction profile are identified and used to design the detection rule framework.
02
Deploy
Platform implementation & rules configuration
The fraud management platform is deployed and integrated with your core banking system, digital channels and card payment infrastructure. Detection rules are configured and tuned to your specific risk profile. Investigation team training is delivered.
03
Optimise
Continuous rule tuning & performance management
Fraud detection rules are continuously monitored and refined as fraud patterns evolve. Regular performance reviews assess detection rates, false positive levels and loss prevention outcomes — ensuring your fraud defences improve as fraudsters adapt their techniques.
Reduce fraud losses. Protect your customers. Maintain your institution's reputation.
Speak to our fraud management specialists about implementing real-time, cross-channel fraud detection that stops fraud before it completes — not after your customers call to report it.