What is Passive Fraud?
In fintech, passive fraud refers to fraudulent activities that occur without the active participation of the legitimate account holder. This includes fraudulent activities by criminals who take advantage of flaws in the fintech ecosystem, such as account takeover, identity theft, synthetic Identity fraud, phishing, money mules, and unauthorized transactions, often without the victim’s knowledge.
For instance, a fraudster gains access to someone’s account due to poor security practices, such as using a password. Once signed up, the fraudster conducts illegal transactions, transfers money to their account, or applies for loans or credit cards in the person’s name, all without the account holder’s participation or knowledge. The account holder may not become aware of the fraudulent activity until they review their account statements, receive unexpected bills, or face financial difficulties.
What is Passive Biometrics Verification Check?
Passive biometrics does not involve active user participation in the authentication or identification process, and sometimes user involvement is not necessary. Authentication occurs during regular user activities. The subject is not required to act directly or physically in these cases. The highest level of authentication is provided when the system operates without the user’s knowledge. Automated technology systems analyze a person’s behavioral or physiological characteristics, with or without the user’s knowledge.
For example, any fingerprint or hand geometry technology, as well as signature recognition and retinal scanning, would be considered active biometrics. This is because the user must place their hand or inspect the scanning device for identification. Passive biometrics verification, on the other hand, includes voice, facial, and iris recognition patterns.
Passive Behavioral biometrics
A passive biometrics verification check examines a person’s current behavior, comparing it to previous observations to prove that it is correct. Unlike physiological biometrics such as fingerprint scanning, behavioral biometrics collect and analyze behavioral events in the background without interfering with the user experience.
The technology can be used safely in many situations because behavioral biometrics are generally harmless. It can be used as a part of two-factor or multi-factor authentication (2FA and MFA). Passive behavioral biometrics can be used independently for analysis or in conjunction with other biometrics to improve the accuracy of identity verification processes. Passive behavioral biometrics examples include:
- Mouse dynamics
- Keystroke dynamics
- Touchscreen Gestures
- Gait Recognition Technologies (GRT)
- Voice Biometric
Passive Voice Biometrics requires the user to complete the registration process by providing a unique voice. To function properly, passive voice biometric technology necessitates a single recording of the user’s voice lasting at least 20 seconds.
Passive Psychological Biometrics
Passive biometrics verification can also include physiological characteristics such as:
During a user’s interaction with a device, facial features such as facial geometry and unique facial expressions are analyzed. The majority of facial liveness detection solutions rely on passive observation via software that detects eye movement, lip movement, or blinking. These passive liveness detection systems can be fooled by masks, photos with eye holes cut out, and videos.
Using biometric wearables or specialized sensors to monitor a user’s heartbeat or ECG data to confirm their identity.
What is Passive Liveness Detection?
Liveness detection involves determining whether the images sent were taken from a live state. Passive liveness detection is an important component of passive biometric verification checks. Passive biometrics confirm identity based on behavioral or physiological characteristics, whereas passive liveness detection ensures the user’s physical presence during the authentication process.
Passive liveness technology is used by identity verification solution providers to provide a simple and easy user experience. It requires no action just simply taking a photograph. Passive liveness detection outperforms active liveness detection, with completion rates ranging from 60% to 95%.
Passive liveness detection is thought to be a good way to protect from fraudsters. They are unaware that the liveness check is happening because all that is needed is to take a photo. I’m not sure if life detection is enabled because it can detect at the same time as face recognition. They have no idea if the liveness detection was turned on because it can detect both during the face recognition process.
Shufti Pro launched an IDV service that provides facial recognition, document verification, and viability detection for fast identity verification, assisting businesses in combating fraud and complying with KYC/AML regulations. The service combines active and passive verification methods, with a five-second identity verification process and a selection of 30 digital identification options to help businesses efficiently verify customer identities.
How Does it work?
The method is simple but effective. It scans users’ biometric facial data effectively, removing the need for user interaction to provide a seamless experience. This is how it works:
- The user takes a selfie or uses an image from their identification document. The system starts evaluating the service criteria without requiring any specific user input.
- The system examines the image and determines the various facial expressions, shapes, and expressions of the face. Advanced algorithms detect small details and differences in photos, videos, masks, and live faces.
- The software is designed to detect changes in light reflectance, skin changes, and depth perception, which aid in distinguishing between 3D masks and photographs of a real human face.
- Following real-time analysis, the system checks the selfie and the identity document, perfecting the fit and eliminating potential issues.
- The results are calculated automatically, and a confirmation level is displayed, adding a layer of security to the facial recognition system without interfering with the user experience.
Passive liveness detection provides a strong defense against passive fraud, and malicious attacks, making passive biometric verification check an important component of an anti-fraud strategy’s wheel.
The Role of Passive Biometric Verification Checks in KYC/AML Compliance
- Passive biometric verification streamlines the KYC process by continuously monitoring user behavior and physiological characteristics.
- Passive biometrics verify customer identity at login and during interactions, increasing security.
- Passive biometrics verification checks can detect unusual behavior, raising the bar for further investigation into fraudulent activity.
- Passive liveness detection confirms the customer’s physical presence, making impersonation and spoofing difficult.
- These technologies improve the customer experience by allowing for seamless browsing without the need for extra steps.
- Strong customer profiling and detection of suspicious activity aid in the reduction of false positives and AML levels.
- Passive biometrics align with regulatory expectations for improving due diligence and verifying customer identities while ensuring KYC/AML compliance
Passive biometric verification check is transforming online security. It protects against passive fraud, improves the user experience, and provides a method for identity verification recovery. Passive biometrics and passive liveness detection play an increasing role in protecting our digital lives as technology advances. Integrating passive biometric verification into KYC AML processes improves security, reduces false alarms, and improves regulatory compliance.