In the world of digital crime, you no longer need to be an expert hacker to commit fraud. All you need are intentions and a budget. Today, there is a market on the dark web that sells tools, bots, fake identities, and even personalized advice to carry out attacks. This is known as Fraud as a Service, or FaaS: a model where fraud is rented out, outsourced, and has become a massive, scalable, and professionalized threat.
And yes, fraud now operates like a business: with “technical support,” scalable packages, and 24/7 service.
What is Fraud as a Service (FaaS)?
FaaS is the offering of tools, services, or complete platforms that enable anyone (without technical knowledge) to execute digital fraud. This ranges from bots that create fake accounts to deepfakes designed to bypass identity verification systems.
FaaS “providers” offer:
- Customizable phishing kits.
- Thousands of stolen credentials.
- Human behavior simulators.
- Facial and voice deepfakes.
- Synthetic identity generators.
- Real-time assistance to evade anti-fraud measures.
The problem is clear: fraud is no longer handcrafted; it is now scalable, automated, and available to anyone with access to cryptocurrencies.
Why is FaaS such a serious threat?
Its impact is especially critical in sectors like finance and fintech, where the integrity of digital identity is key to preventing economic losses and protecting users. This is because Fraud as a Service has made executing complex scams accessible to a much wider audience. FaaS has democratized fraud. Now, anyone can rent these services on the dark web and attack financial organizations, technology platforms, and public systems alike.
This leads to direct consequences:
- Exponential increase in simultaneous and coordinated attacks.
- Greater difficulty distinguishing between real and malicious users.
- Increased sophistication in the use of fake identities and mule accounts.
- Escalation of fraud such as Account Takeover and New Account Fraud (NAF).
And worst of all: many traditional anti-fraud solutions are not equipped to detect complex, contextual, or behavioral signals. FaaS is faster, cheaper, and harder to trace.
How to stop Fraud as a Service?
The answer lies in technology that not only detects fraud when it happens but anticipates it before it materializes. At Facephi, we have been working for over a decade with technologies designed to protect every point of the user lifecycle.
The key is based on three pillars:
1. Verified digital identity from the start
With solutions like Facephi Onboarding and Facephi Authentication, we ensure that whoever accesses a platform is a legitimate user.
This includes:
- Document verification with OCR and NFC chip.
- Facial, voice, or fingerprint biometrics.
- Passive liveness detection (frictionless proof of life).
- Compliance with KYC, AML, GDPR.
This prevents fake or synthetic accounts from being easily created or activated.
2. Strong, continuous, and adaptive authentication
Our solutions combine Multifactor Authentication (MFA), which strengthens access with multiple factors (biometrics, trusted devices, etc.), with continuous authentication based on behavioral and contextual analysis. This enables real-time risk assessment and adapts security measures according to the context of each session or transaction, following the Zero Trust model.
Includes:
- Multi-biometric authentication.
- Trusted devices.
- Contextual analysis (device, IP, network, behaviour, etc.).
- OTP codes, mobile number verification, and push notifications.
All of this without impacting the legitimate user’s experience, achieving an optimal balance between security and usability.
3. Advanced monitoring and detection with AI
Where Facephi goes a step further is in proactive real-time fraud detection, with solutions designed for highly sophisticated environments, such as:
Behavioural Biometrics
Behavioral biometrics allows detection of fraud hiding behind seemingly legitimate access, analyzing over 3,000 signals—such as typing rhythm, mouse trajectories, mobile gestures, browsing habits, or contextual variables—to create a unique behavioral profile or “cyber-DNA.”
This enables detection of:
- Account Takeover (ATO).
- New Account Fraud (NAF).
- Advanced bots or malicious automation.
- Anomalies in legitimate sessions or deepfakes.
All this operates invisibly to the user, with continuous validation and no friction. The AI adjusts in real time, learns from each session, and improves its predictive ability with every interaction. Always under strict privacy and security standards, ensuring data is processed anonymously without compromising user identity.
Mule Account Detection
Mule accounts are key in financial fraud and money laundering schemes. They may be operated by deceived users, accomplices, or created with fake identities. Often, they go unnoticed until it’s too late.
Our proactive mule account detection solution identifies these accounts before fraud occurs, thanks to:
- Pre-fraud signal analysis from account registration.
- Dynamic real-time role classification (victim, accomplice, synthetic).
- Tracking devices connected to multiple suspicious accounts.
- Collaborative intelligence consortia among entities, without compromising privacy.
- Adaptive risk scoring based on account behavior.
This technology not only identifies individual accounts but uncovers patterns among organized fraud networks and activates defenses at all points of the transactional cycle.
Anticipation is the greatest defense
aaS has changed the rules of the game. It’s not enough to react; you must anticipate fraud. At Facephi, we have designed an ecosystem of solutions that combine advanced biometrics, AI, and contextual and real-time signal analysis to protect organizations from onboarding to the final transaction. Because in a world where fraud can be rented by the hour, trust cannot be just a promise: it has to be an architecture.
Want to know how to protect your organization against the new Fraud as a Service?
Contact us and discover how to anticipate threats with advanced technology.