Fraud Detection

Q: Does fraud detection add friction for legitimate users?

No. Our risk-based approach only adds friction (e.g. step-up verification) for high-risk interactions. Low-risk users experience a seamless flow.

Q: Can I customise the risk rules?

Yes. Our visual rules builder lets you create, test, and deploy custom rules without writing code. You can also use our API to integrate your own models.

Q: How does the system learn from my data?

You can provide feedback on decisions (correct/incorrect) via the dashboard or API. Our models retrain on this feedback to improve accuracy for your specific use case.

Q: What is a fraud ring?

A fraud ring is a group of coordinated fraudsters sharing devices, IPs, or identity data. Our network analysis detects these clusters even when individual accounts appear legitimate.

Stop fraud before it costs you — with AI that learns.

VerifyAfrica's AI-powered fraud detection engine analyses behavioural signals, device intelligence, and identity patterns to catch fraudsters at onboarding and throughout the customer lifecycle. Protect your platform without adding friction for legitimate users.

Request a Demo Explore Dashboard

94%

Fraud Catch Rate

<0.1%

False Positive Rate

200+

Risk Signals

Real-time

Detection Speed

How It Works

From submission to decision in seconds

A transparent, auditable process designed for speed and compliance.

Signal Collection

Device fingerprint, IP intelligence, behavioural biometrics, and identity data are collected at the point of interaction.

AI Risk Modelling

Our ML models analyse 200+ risk signals simultaneously, comparing against known fraud patterns and your historical data.

Pattern Recognition

Cross-customer pattern analysis detects coordinated fraud rings, synthetic identity clusters, and account takeover attempts.

Decision & Action

A risk score and recommended action (allow/challenge/block) is returned in real time. Rules are fully configurable.

Capabilities

Everything included, out of the box

No stitching together multiple vendors. Every capability you need in a single API.

Device Intelligence

Device fingerprinting, emulator detection, and VPN/proxy identification.

IP & Geolocation

IP reputation scoring, impossible travel detection, and geolocation risk signals.

Behavioural Biometrics

Typing patterns, mouse movements, and interaction timing to detect bots and account takeovers.

Network Analysis

Graph-based analysis to detect fraud rings and shared identity signals across accounts.

Custom Rules Engine

Build and deploy custom fraud rules without code using our visual rules builder.

Adaptive ML

Models continuously learn from your feedback to improve accuracy over time.

Use Cases

Built for every industry in Africa

Trusted by fintechs, banks, iGaming operators, and more across the continent.

Neobanks

Detect synthetic identities and account takeovers during onboarding and login.

iGaming

Identify bonus abuse, multi-accounting, and payment fraud before they impact your margins.

Lending

Catch fraudulent loan applications using identity and behavioural signals.

E-commerce

Prevent payment fraud and account takeovers on your marketplace or store.

FAQ

Common questions

Everything you need to know about Fraud Detection.