In most payment fraud cases, the fraudster accesses the victim’s account and makes the payment without their knowledge. With authorised push payment fraud in Africa, the victim is manipulated into making the payment themselves, believing the recipient is legitimate. By the time they realise something is wrong, the money may already be gone.

This is not a minor fraud problem. GSMA found that 88% of surveyed mobile money providers reported social engineering among the fraud typologies they experienced, while Visa's 2026 threat report highlights the growing use of AI and social engineering to manipulate people into authorising payments themselves.

This article looks at how APP fraud works, how it plays out on African platforms and what fintechs can do to detect it before the money moves.

What Authorised Push Payment Fraud Is

Authorised push payment (APP) fraud happens when a fraudster manipulates a victim into willingly transferring money to an account the fraudster controls. They may impersonate a trusted person or organisation, create a false emergency, or present a convincing investment opportunity.

To understand the detection challenge, start with how APP fraud works:

• The victim makes the payment: In an account takeover, the fraudster gains access and initiates the transfer. With APP fraud, you log in, enter the payment details, and confirm the transaction yourself. The platform sees a valid login, credentials, and payment authorisation.
• The fraud takes different forms: Investment scams, impersonation scams, fake purchases, and urgent payment requests all rely on the same tactic: manipulation. The fraudster convinces you that the payment is legitimate rather than breaking into your account.
• Recovery is difficult: With unauthorised fraud, the victim can dispute a transaction they did not initiate. Push payment fraud in Nigeria and across Africa can be harder to resolve because the customer authorised the payment under false pretences. 

Understanding how APP fraud plays out on African platforms is what tells a fraud team where detection needs to sit.

How APP Fraud Plays Out on African Platforms

APP fraud on African platforms usually follows a predictable chain. Each stage creates a potential detection point, but most platforms only see what happens once the payment reaches their system.

The fraud typically unfolds in these stages:

• Trust is built before the platform is involved: The fraudster may approach you through social media, messaging apps, or an unsolicited message. By the time you open your banking or payment app, the request already feels legitimate.
• Urgency pushes you to act: A fake fraud alert, limited-time investment, or emergency creates pressure to act quickly. The goal is to leave little time for you to pause, verify the request, or seek a second opinion.
• You initiate the transfer normally: You log in, enter the beneficiary details, and confirm the payment. From the platform's perspective, the credentials, device, and authentication are all valid, so there may be no obvious sign of account compromise.
• The funds move quickly: Once the payment lands, the recipient may move the money through mule accounts, other platforms, or cash-out channels. This leaves a narrow window for intervention before the funds become difficult to recover.

The fraud is often complete before most detection systems would flag it. That is the detection problem APP fraud creates.

Why African Platforms Are Particularly Exposed

APP fraud happens everywhere, but social engineering is a significant concern for African payment platforms, particularly mobile money providers. Visa's 2026 threat report also found that criminals are increasingly using AI and social engineering to manipulate people into authorising payments themselves.

Here is why APP fraud is difficult to stop:

• Instant payments & narrow intervention window: In African markets, mobile money platforms move large volumes of transactions at speed. Instant payments make transactions convenient for legitimate users, but they also benefit fraudsters. Funds can clear quickly into mule accounts, leaving platforms with little time to intervene.
• OTP authentication confirms the payment: APP fraud does not require the fraudster to intercept your OTP. You receive the code, enter it yourself, and confirm the payment. The authentication step therefore confirms a transaction you have been manipulated into making.
• Recovery frameworks vary: Where mandatory APP reimbursement frameworks exist, they give platforms a stronger incentive to detect and stop suspicious payments before they clear. Where such frameworks are limited or absent, recovering authorised payments can be more difficult, making early intervention even more important.

The conditions that make APP fraud effective in African markets are also what make it hard to catch at the transaction layer.

Why APP Fraud Is Hard to Detect

The payment can look completely legitimate because the account holder is the one making it. They use their usual credentials and device, so the signals that normally point to unauthorised access may be missing.

Here is where standard detection can fall short:

• Every credential signal is clean: You use your own device, password, and OTP to authorise the payment. There may be no unusual login, failed authentication, or unfamiliar device to trigger an alert. From an access perspective, everything looks normal.
• The transaction looks normal: A new beneficiary or larger-than-usual transfer is not automatically fraudulent. The payment may be unusual for you, but that does not make it fraudulent on its own. Without enough context about your normal behaviour, the platform may struggle to tell the difference.
• Rules alone are not enough: Rules can flag large transfers or first-time beneficiaries, but these signals can also appear in legitimate payments. Blocking every transaction that matches them would create unnecessary friction for genuine users. The challenge is combining these signals with the account's usual behaviour to identify a pattern that deserves attention.

Catching APP fraud requires looking beyond the transaction to the pattern around it.

What Detection Actually Requires

Knowing where standard checks fall short changes what you need to monitor. The goal is not to prove that a payment is fraudulent from one signal, but to spot behaviour that differs from the account holder's normal pattern.

These signals can help identify that difference:

• Unusual beneficiary and atypical amount: A first-time beneficiary combined with a transfer that is much larger than the account's usual amount is a stronger signal than either one alone. When both occur in the same session, the payment may warrant a step-up check or short hold before it clears.
• Time-of-day anomalies: A transfer made at an unusual time for a particular account can add another risk signal. It becomes more meaningful when it appears alongside other changes in the user's normal behaviour.
• First-time transfer with no prior relationship: A transfer to a beneficiary with no previous connection to the account deserves closer attention, particularly when other risk signals are present. A confirmation step or short hold can give the account holder time to reconsider the payment without automatically blocking it.
• Session behaviour that breaks the usual pattern: Rapid movement from login to a large transfer, several beneficiary searches, or an unusually short decision time can indicate a high-risk session. These signals become useful when compared with the account's established behaviour rather than treated as proof of fraud on their own.

These signals only help if the monitoring layer can detect them in real time, before the transfer clears.

How Dojah's Easy Detect Helps Stop APP Fraud on Your Fintech Platform

APP fraud becomes harder to catch when your monitoring layer only looks at the transaction itself. Easy Detect combines transaction and behavioural monitoring to help identify risk signals in real time, before a suspicious payment clears.

Here's how Easy Detect helps:

• Real-time behavioural and transaction monitoring: Easy Detect monitors transaction patterns alongside behavioural signals. This helps surface combinations such as a first-time beneficiary, an unusual transfer amount, and abnormal transaction timing.
• Configurable risk rules: You can configure risk rules around the APP fraud patterns relevant to your platform. This gives your team more control than relying on generic thresholds that may create unnecessary friction for legitimate transactions.
• Pre-clearance intervention: When a transaction meets your configured risk threshold, Easy Detect can trigger an intervention before the payment clears. This creates an opportunity to review or challenge the transaction before the funds move.
• Continuous account behaviour monitoring: Easy Detect monitors account behaviour beyond individual transactions. Risk can be assessed against the account's established behavioural pattern rather than relying only on generic thresholds.

For African payment platforms, Easy Detect brings behavioural and transaction monitoring together to help identify APP fraud before the funds move.

See how Dojah's Easy Detect helps African platforms detect authorised push payment fraud in real time.

Frequently Asked Questions About Authorised Push Payment Fraud in Africa

1. What is authorised push payment fraud in Africa?

Authorised push payment fraud occurs when a fraudster manipulates a customer into authorising a payment to an account they control. The customer makes the payment themselves, making the fraud harder to identify through traditional account-takeover signals.

2. Why is APP fraud difficult for African fintechs to detect?

APP fraud on African fintech platforms face a challenge in detection because the customer's credentials can all appear legitimate. Detection therefore needs to consider transaction and behavioural patterns, not just access signals.

3. How does push payment fraud in Nigeria work?

Push payment fraud in Nigeria often involves social engineering through channels such as WhatsApp, SMS, or email. The fraudster creates trust or urgency before convincing the customer to authorise the transfer.

4. What signals can help African fintechs detect APP fraud?

Useful signals include a first-time beneficiary, an unusually large transfer, unusual transaction timing, and session behaviour that differs from the customer's normal pattern. Looking at these signals together provides more context than relying on one rule.

5. How can fintechs prevent authorised push payment fraud?

You can reduce the risk by combining behavioural monitoring, transaction monitoring, configurable risk rules, and real-time intervention. The goal is to identify suspicious patterns before the payment clears, rather than investigating after the funds have moved.