Synthetic identity fraud is one of the fastest-growing types of financial crime. As the FTC (Federal Trade Commission) continues to report unprecedented levels of fraud and identity theft1, organizations are turning to modern ID verification solutions to fight back with advanced technology like biometrics and layered ID verification workflows.
In this blog post we’ll explore what a synthetic identity is, why it can be hard to detect in a traditional document ID verification workflow, and how a digital trust solution can help.
A synthetic identity is a fake identity created by combining both real and fake information.
For example: A fraudster might combine a real Social Insurance Number (SIN) and a real address with a fake name and fake date of birth to create a synthetic driver’s license.
Traditional document ID verification reviews typically focus on reviewing individual data points–like a name, address, or date of birth—in isolation, without cross-referencing multiple sources to ensure the entire identity is authentic. Since synthetic identities often include some real data, they can more easily pass these basic checks.
Additionally, traditional reviews often focus on the authenticity of the document itself (e.g., verifying if a driver's license looks legitimate) rather than on the verification of the identity behind it. Synthetic identities can exploit this by using genuine-looking documents but with fraudulent data.
Artificial Intelligence (AI) can play a significant role in modern document ID verification. Machine learning algorithms can help provide a much faster and more complete analysis of an ID; checking for security features like holograms, watermarks and microprints, while examining the overall structure of the document and cross-referencing the data using multiple, independent sources.
AI algorithms can also recognize patterns and discrepancies in the actual document that can indicate the likelihood of a forgery, like inconsistent fonts, altered photos or tampered barcodes.
A modern ID verification solution can offer:
Document Authenticity: A comparison of the provided ID against known templates of authentic documents. The solution looks for specific design elements such as watermarks, holograms and microprinting to verify the document’s authenticity.
Photo Matching and Liveness Detection: Many ID verification solutions use facial recognition technology to match the photo on the ID with a live or previously uploaded selfie. This step helps ensure that the person presenting the ID is the same person to whom the ID was issued, reducing the risk of spoofing attempts using photos or videos.
Optical Character Recognition (OCR): OCR technology can automate the extraction of data from the presented ID and cross-reference it with data that is manually entered by the user. This can significantly reduce both the time required for manual data entry as well as the risk of human error.
Barcode and MRZ Validation: Most government-issued IDs include barcodes or Machine Readable Zones (MRZs). ID verification solutions decode these elements to verify their accuracy and ensure they align with the visible information on the document.
While AI can help identify fake or forged ID documents, the technology cannot always verify if the information on those documents is legitimate. This is where the complexity of synthetic identities becomes a significant challenge — the combination of real and fake data can outsmart even the most advanced systems.
So what else can modern, digital trust solutions offer to businesses to help combat synthetic identities? The answer lies in layered ID verification.
To help fight back against synthetic identity fraud, businesses need to look for an ID verification solution that combines AI-enhanced document ID verification with layered ID verification workflows.
Layered ID verification uses multiple, independent sources of data to cross-reference a single piece of information.
For example: A layered ID verification workflow might take a presented name, address, and phone number, and verify that information using telecom data, a government-issued document ID like a driver’s license, and financial credentials. If the presented information is accurate and consistent across these multiple points of verification, there is a higher chance that the identity is authentic.
Your best defense against synthetic identity fraud is an advanced, layered ID verification solution. Here’s what to look for:
ID Verification: Verifying document authenticity as well as ID authenticity adds an important layer of review. The use of OCR technology can streamline and simplify the customer experience while reviewing the risk of human error.
Biometric Information Reviews: Adding a liveness check to a photo ID review can more accurately tie the individual to the presented identity in a way that is more difficult to fake.
Layered ID Verification Workflows: Cross-referencing multiple, independent sources of identity information such as credit bureau checks, telecom data, and government databases can help indicate consistency and a greater chance that the identity is real.
Synthetic identity fraud is a complex and evolving challenge, but modern ID verification solutions are increasingly equipped to tackle it. While no solution can guarantee absolute authenticity, a multi-layered approach significantly mitigates the risk of fraud and protects both businesses and consumers in the long run.
Oliu’s state-of-the-art ID verification solution offers both AI-enhanced document ID verification and customizable, layered ID verification workflows.
If your organization is looking for a way to help combat synthetic fraud, book a demo with us today!