A fraudster does not always need to break into a fintech platform to steal from a user. Sometimes, all it takes is a convincing message, a phone call, or a well-timed impersonation that gets the user to hand over what the fraudster needs. No system is hacked, no ID is forged, and no liveness check is bypassed because the user has unknowingly opened the door themselves.

NIBSS identified social engineering as the most prominent fraud technique in Nigeria’s banking and digital payments ecosystem in 2025. The tactics are becoming more convincing, the networks behind them more organised, and social engineering fraud remains a growing challenge for financial institutions.

This article looks at how social engineering fraud works across African fintech platforms and what fintechs can do to stop it.

What Social Engineering Fraud Actually Is

Social engineering fraud exploits human trust, urgency, or authority rather than technical vulnerabilities. Instead of attacking the system, the fraudster convinces the user to reveal information or authorise an action. The system works as designed; the fraud succeeds because the user was manipulated into helping the attacker.

Here's what that looks like:

• It targets people not systems: A technical attack tries to defeat a security control. Social engineering works around it by getting the user to cooperate. You can have strong authentication, identity verification, and fraud controls in place and still have a problem if a user is convinced to give an attacker the information or access they need.
• The platform sees a legitimate transaction: Once the user enters their real password and OTP or approves a transfer themselves, the activity can look legitimate. The credentials are valid, the authentication succeeds, and the transaction comes from the account holder. At the technical layer, there may be nothing obviously wrong to flag.
• Urgency and authority make the request believable: The attacker usually gives the user a reason to act immediately or makes the request sound official. It could be a warning that an account will be blocked or a caller claiming to be from the bank's fraud team. The goal is to make the user act before they stop to question or verify the request.

The approach varies by channel, but the goal remains the same: get the user to act on the attacker's behalf.

The Main Types Hitting African Fintech Platforms

The method may differ, but the goal is the same. The fraudster needs the user to take the action for them.

They can take different forms:

• Phishing: A fake email or message directs the user to a replica login page that looks like the real platform. A security alert, failed login, or account suspension creates urgency, making the user more likely to enter their credentials without checking the link or domain.
• Vishing: A phone call impersonates a bank official, support agent, or regulator. Details such as the user's name, account type, or recent transaction can make the call sound legitimate before the fraudster asks for an OTP, credentials, or a transfer.
• Smishing: A fraudulent SMS mimics a message from a bank or fintech platform, often containing a fake login link or an OTP request. Because users already receive legitimate alerts and authentication codes through SMS, a convincing message can make it difficult to distinguish the fake from the real.
• Fake customer support impersonation: A fraudster poses as a support agent through WhatsApp, social media, or a spoofed number and claims there is a problem with the user's account. The conversation then leads the user to share credentials, approve a transaction, or transfer funds.

From the platform's perspective, these attacks can produce the same result: a legitimate-looking session followed by unusual behaviour.

Why African Fintech Users Are Particularly Vulnerable

Social engineering works across markets, but African fintechs rely on channels that fraudsters can exploit. Mobile-first access, SMS communication, and fast digital transactions give users convenience while creating more opportunities for manipulation.

Several factors make these attacks effective:

• OTP-heavy authentication is a key target: An OTP can block unauthorized access, but it cannot help when a user willingly shares it. Social engineering turns the user into the final step of the authentication process, giving the fraudster what they need without breaking the security control.
• Familiar channels can make fake requests believable: Users receive OTPs, transaction alerts, and account notifications through channels such as SMS. A fraudulent message or call that looks familiar can therefore appear legitimate, especially when it creates pressure to act quickly.
• Fraud networks can operate at scale: Social engineering does not always involve a lone fraudster. During INTERPOL's Operation Red Card 2.0, Nigerian authorities dismantled a fraud ring that used phishing, identity theft, and social engineering, with more than 1,000 fraudulent social media accounts linked to the operation. 

By the time your platform detects the fraud, the user may have already completed the action the fraudster needed.

How Social Engineering Plays Out in Practice

A successful social engineering attack can look normal at the authentication layer. The login is legitimate, the OTP is valid, and the session is authorised. The first useful signal may appear in what the user does immediately afterwards.

Here’s how it plays out:

• Everything checks out at login: The user logs in with valid credentials and completes the required authentication. The device, location, and OTP may all appear legitimate, so the platform has little reason to block the session at this stage.
• Unusual behaviour follows authentication: The first warning sign may appear seconds or minutes later. A user who has just logged in may add a new beneficiary, change account details, or make a large transfer. When these actions happen in quick succession, they can indicate that the session no longer matches the user's normal behaviour.
• The pattern matters more than one signal: A new beneficiary is not automatically fraud, and neither is an unusual transaction time. But when several unusual actions occur in the same session, especially after a login from an unfamiliar device or location, the combined pattern becomes more significant than any single event.

Detection therefore needs to move beyond authentication and into behaviour, with enough speed to intervene before the funds leave the account.

How Your Platform Can Detect Social Engineering Fraud

For African fintechs, detecting social engineering fraud requires more than user education. A convincing call or message can still persuade a user to authorise a legitimate transaction. Your platform needs controls that detect suspicious behaviour after authentication and intervene before funds move.

The right controls focus on what happens after login:

• Step-up authentication for risky post-login behaviour: If a session shows a new device, an unusual location, or a first-time beneficiary, require an additional verification step before allowing a high-risk action. This adds a barrier when the fraudster has the user's credentials but cannot complete the additional check.
• Device consistency checks across sessions: Build a baseline of the devices each account normally uses. When a login comes from an unfamiliar device, raise the risk level before allowing high-value actions, especially when other unusual signals appear in the same session.
• Transaction holds on first-time beneficiaries: Place a short hold on transfers to beneficiaries the account has never used before. Notify the account holder through a verified channel during the hold so they can flag a transfer they did not authorise before the funds leave the account.
• Behavioral monitoring for session anomalies: Compare each session with the account's normal behaviour. A login followed by a new beneficiary and a high-value transfer within minutes can indicate risk when that sequence is unusual for the account.

These controls are stronger when they work together, with each signal adding context to the others.

How Dojah's Profiled Risk Detects Social Engineering Fraud

Social engineering can pass authentication because the user provides valid credentials and completes the required verification. Profiled Risk brings identity, device, behavioural, and transaction signals together so your fraud team can assess what happens after login, not just whether the login was valid.

Profiled Risk connects the signals that matter:

• Device and login signals: Profiled Risk uses device and location data alongside other risk signals to identify activity that differs from an account's normal profile. This can help surface suspicious sessions even when the credentials are valid.
• Post-login behavioural changes: Instead of assessing events in isolation, Profiled Risk brings behavioural and transaction activity into the same risk view. A sudden change in account behaviour can therefore contribute to the overall risk assessment.
• Transaction risk signals: Transaction activity forms part of the risk profile, allowing your fraud team to assess suspicious activity alongside the device and behavioural context surrounding it.
• Continuous risk assessment: Profiled Risk combines multiple signals into a unified risk profile and provides real-time monitoring and alerts, helping fraud teams identify changes as they happen rather than reviewing each event separately.

For African fintechs and banks facing social engineering fraud, Profiled Risk provides your fraud team with post-authentication behavioural monitoring to detect suspicious activity before it results in a loss.

See how Profiled Risk helps your fintech detect social engineering fraud beyond the authentication layer.

Frequently Asked Questions About Social Engineering Fraud: How It Works and How African Fintechs Can Stop It

1. What is social engineering fraud in African fintech?

Social engineering fraud manipulates users into revealing sensitive information or authorising actions for a fraudster. It exploits trust, urgency, or authority instead of attacking the platform's technical controls.

2. How does a social engineering attack affect fintech in Nigeria?

A social engineering attack can result in a legitimate login followed by unusual activity, such as adding a new beneficiary, changing account details, or transferring funds. Because the user may have completed authentication themselves, the platform needs to monitor what happens after login.

3. What are phishing, vishing, and smishing in Africa?

Phishing uses emails or online messages, vishing uses voice calls, and smishing uses SMS to manipulate users into sharing sensitive information or taking an action. These attacks often impersonate trusted organisations such as banks and fintech platforms.

4. How can African fintechs detect social engineering fraud?

Your platform can combine device, behavioural, and transaction signals to identify activity that differs from the user's normal pattern. Step-up authentication, device checks, transaction monitoring, and real-time risk alerts can help your team respond before funds move.