Trouble-Free
Document Authentication.
The Document Fraud Detection module, known as DocFraud, is designed to scrutinise images of IDs and passports submitted during the KYC process. By performing a series of detailed inspections, the system assesses the authenticity of the documents and identifies any signs of tampering or fraud. This module performs a range of advanced checks to detect fraudulent activities, ensuring the authenticity of submitted documents and enhancing security in identity verification.
Book a Demohow it works
Inspect. Assess. Verify.
The Document Fraud Detection module scrutinises images of IDs and passports submitted during the KYC process, performing detailed inspections to assess authenticity and identify signs of tampering or fraud.
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Image Submission
The user submits an image of their ID document or passport.
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Metadata Analysis
The system analyses the metadata of the submitted image for inconsistencies or anomalies, including file type verification, metadata presence check, device information, modification flags, date consistency, and file type consistency.
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Fraud Detection Checks
The system performs various checks, including photocopy/scan detection, security zones check, physical tampering detection, screen-recapture detection, and digital tampering detection.
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Verification
The system verifies the authenticity of the document based on the results of the fraud detection checks.
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Alerting
If any signs of fraud are detected, the system alerts the relevant parties for further investigation.
why it works
Stop Fraud in its Tracks.
Leveraging cutting-edge image analysis and machine learning, our Document Fraud Detection module boasts advanced technology to effectively identify fraudulent documents. It conducts comprehensive checks to ensure the authenticity of submitted documents, leaving no stone unturned. By automating the entire process, it dramatically reduces the need for manual review, significantly boosting verification efficiency, while the enhanced security layer safeguards the identity verification process from fraudulent attempts.
the difference
Detailed Inspections
Beyond the Basics.
Our fraud detection system performs comprehensive checks, including file type verification, metadata analysis, and physical tampering detection, offering a level of scrutiny that sets it apart from traditional methods.
It delivers robust document verification through a combination of advanced fraud detection techniques. The automated process minimises manual intervention, streamlining the experience and boosting efficiency. High accuracy in fraud detection is achieved thanks to powerful algorithms, all while maintaining a user-friendly interface for a smooth document submission process.
why choose us
Flexible. Modular. Advanced.
Our solution leverages cutting-edge technology to detect document fraud through metadata checks, photocopy/scan detection, and physical tampering detection, ensuring robust security and compliance.
Expertise
Backed by years of experience in document fraud detection and identity verification technologies.
Innovation
A continuously evolving our platform with the latest advancements in image analysis and machine learning.
Modular Approach
The solution can be purchased as a standalone module, allowing for a lower cost of ownership and the ability to expand as needed.
Enhanced Compliance and Security
Provides strong compliance and reduced risk through advanced fraud detection techniques.
Flexibility
Can be deployed on-premise or hosted in a cloud environment, offering deployment flexibility.
Support
Dedicated customer support team to assist with setup, customisation, and ongoing maintenance.
features
Robust Fraud Detection Tools.
Key features include metadata checks, photocopy/scan detection, physical tampering detection, screen-recapture detection, and digital tampering detection, all designed to ensure the authenticity of submitted documents.
Metadata Checks
File Type Verification: Verifies if the file type of the input image is permitted.
Metadata Presence Check: Checks whether the metadata has been stripped. Metadata can be removed when sharing files over the internet to save space, but this information is crucial for performing fraud checks.
Device Information: Ensures that metadata contains information about the capturing device, such as make and model.
Modification Flags: Analyses metadata flags to determine if any fields have been updated, indicating that the image has been edited. The presence of new metadata flags can also suggest tampering.
Date Consistency: Verifies that the modification date and creation date are consistent and have not been altered.
File Type Consistency: Checks that the file type matches its extension, for example, ensuring that a .jpg file extension corresponds to a JPEG file, not a PNG that was renamed.
Security Zones Check
Verification of Security Features: Examines specific security features and zones on the document, such as holograms and watermarks, to ensure that they are genuine and have not been tampered with.
Screen-Recapture Detection
Detection of Screen-Recapture Attacks: Identifies one of the simplest forms of forgeries, screen-replay attacks or screen recaptures. In these attacks, an ID image displayed on a device's screen is captured. Unlike more sophisticated forgeries, screen recaptures require minimal skill, yet produce realistic results that are increasingly challenging to detect due to advancements in camera and screen technology.
Photocopy/Scan Detection
Photocopy Detection: Identifies if the document image is a photocopy (i.e., a printout on a page).
Scanned Document Detection: Detects if the document image has been scanned.
Grayscale Detection: Identifies if the document is in grayscale, regardless of whether it is a printout, scanned, a loose cutout, or even a precise cutout. This component can detect grayscale areas even if the rest of the document is in colour.
Physical Tampering Detection
Identification of Tampering: Detects signs of physical tampering, such as facial images with coloured backgrounds, insufficient lighting rendering the ID holder's identity indiscernible, and black borders surrounding the facial image. These indicators are typical of a portrait substitution attack, where an attacker physically pastes a new ID image over the existing facial region of the ID.
Isolation and Analysis: Isolates the facial image from the document and analyses it to determine whether tampering has occurred. Various image processing techniques are employed to identify irregularities indicative of physical manipulation.
Digital Tampering Detection
Identification of Digital Manipulation: Detects images that have been digitally manipulated using tools like Photoshop or GIMP. Digital tampering involves taking elements from other images and pasting them into the current image, such as inserting a different face into the face region of an ID card.
Localisation of Tampered Regions: Not only classifies whether an image has been digitally tampered with but also attempts to localise the tampered regions, providing detailed information about the manipulation.
benefits
and Security.
Implementing our Document Fraud Detection module enhances compliance with regulatory standards, reduces the risk of identity fraud, decreases manual review effort, and improves overall document security.
Enhanced Security
Ensures the authenticity of submitted documents, reducing the risk of fraud.
Efficiency
Automates fraud detection, speeding up the verification process and reducing manual workload.
Accuracy
Advanced algorithms and machine learning techniques ensure high accuracy in detecting fraudulent documents.
Cost Savings
Reduces the need for manual review and investigation, lowering operational costs.
use cases
Agent-Assisted Banking: Enable agents to assist customers while ensuring the authenticity of submitted documents through advanced fraud detection.
Retail Banking: Ensure the authenticity of customers’ identity documents during the onboarding process.
Digital Banking: Enhance security in remote identity verification by detecting fraudulent documents.
Business Banking: Verify the authenticity of business clients' identity documents, ensuring compliance and security.
Self-Onboarding: Allow customers to submit their identity documents independently while ensuring authenticity through automated fraud detection.
Remote Onboarding: Facilitate remote verification of identity documents, ensuring their authenticity and reducing the need for branch visits.
E-commerce: Verify customer identities during high-value transactions by scrutinising submitted documents.
Telecommunications: Ensure secure and efficient identity verification for new service activations by detecting fraudulent documents.