Our solutions are designed to provide multiple layers of security that protect against various types of fraud.
In the past five years—accelerating particularly over the last two—attackers have significantly evolved their methods, leveraging advances in artificial intelligence, video manipulation, and vulnerabilities in authentication systems.
Traditional identity fraud attacks, such as screen presentations, remain prevalent. However, they are now combined with more sophisticated techniques, increasing the complexity of fraud detection and prevention, including:
- Video injection attacks
- Man-in-the-Middle (MITM) attacks
- Remote Access Attacks (RATs)
These advanced attacks have raised security standards, not only in facial verification but also by incorporating complementary technologies such as behavioural biometrics, fraud pattern detection, and real-time forensic analysis (mule accounts).
Below are the three main security levels integrated into our solutions.
Level 1: Identity theft
Identity theft is one of the most widespread threats in digital security and poses a critical risk to any identity verification process. This type of fraud involves the manipulation of images, videos, and documents to deceive biometric systems.
Facephi addresses this challenge with a comprehensive approach that combines advanced biometric technologies and document verification, ensuring robust protection without compromising the user experience:
- Passive liveness detection: Identifies whether the person is physically present during authentication.
- Facial authentication: Ensures that the individual registering or authenticating is the rightful person through biometric comparison.
- Document verification with morphological analysis: Examines the integrity and authenticity of identity documents.
- Connection with civil registries: Accesses official databases to verify images and personal information.
- Manipulation and deepfake detection: Identifies synthetic or altered images.
- Blacklist comparison: Alerts when authentication attempts are made by individuals previously identified as fraudulent.
Additionally, we implement frontline controls to mitigate Man-in-the-Middle (MITM) attacks, and all transmitted information is encrypted to protect biometric data from interception attempts.
Level 2: Unauthorised Fraud
Unauthorised fraud represents an evolution in attack methods, where fraudsters do not attempt to impersonate a user directly but exploit system vulnerabilities to manipulate legitimate processes.
This type of fraud often goes undetected by traditional identity controls, as the attacker does not need to pose as another person but instead uses real access credentials or accounts to carry out illicit activities.
To tackle this threat, Facephi has developed a security approach based on behavioural biometrics, enabling the identification of anomalous patterns in user interaction with the device and application, adding an extra layer of protection:
- Behavioural biometrics: Detects fraud by analysing how a user types, moves the mouse, or touches the screen, comparing it in real-time with legitimate patterns.
- Protection against remote access attacks: Prevents attackers from taking control of a device by detecting remote access tools.
- Secure communication channels: Prevents Man-in-the-Middle (MITM) attacks, where attackers intercept and manipulate communication between the user and the application.
- Prevention of video injection attacks: Blocks virtualised cameras and detects attempts to inject false images during authentication.
- Fraud detection from day one: Identifies fraud without requiring prior user history, monitoring onboarding, authentication, and transactions from the first interaction.
With these capabilities, Facephi not only protects against fraudulent access but also strengthens digital channel security, preventing attackers from manipulating devices or real-time authentications.
Level 3: Authorised Fraud
Authorised fraud is one of the most complex forms of illicit activity, as it involves the use of legitimate identities and accounts to commit financial crimes without raising immediate suspicion.
A common case is mule accounts, where real individuals—whether knowingly or unknowingly—lend or sell their bank accounts to criminals for moving illicit funds.
To address this threat, Facephi has developed a security approach based on detecting anomalous patterns and analysing transactions in real-time, enabling the identification of fraud indicators before funds are moved out of the system.
This security level includes:
- Mule account pattern detection: Analyses account history and financial behaviour to identify signs of unusual activity.
- Real-time analysis of suspicious transactions: Applies dynamic risk detection models that assess factors such as frequency, volume, and the origin of funds to determine if an account is acting as a “mule.”
- Linking identities and fraudulent networks: Identifies connections between seemingly independent accounts to detect potential organised fraud networks.
- Early alerts and mitigation measures: Provides continuous monitoring tools, generating real-time alerts when suspicious behaviour is detected in an account. This allows for automated actions such as fund retention.
Authorised fraud, particularly the use of mule accounts, poses a critical risk to the financial system.
Evolving digital security
Challenges in identity verification and digital security are constantly evolving, driven by increasingly sophisticated attacks and the use of new technologies by fraudsters.
In this context, Facephi offers a comprehensive solution that not only responds to current threats but also anticipates and prevents future risks through a proactive, multi-layered security approach.
In an environment where trust and security are essential, Facephi positions itself as the ideal strategic partner to prevent fraud and ensure the integrity of digital processes, protecting both businesses and their users.
