Beating Identity Fraud: Four Ways to Validate an Identity Document

The global rise in identity fraud has been a major worry in the last few years, especially with so many important transactions increasingly taking place online, such as opening a bank account, applying for a loan, filing taxes, and so on. Yet organizations are feeling the pressure to conduct more business online, including high-risk interactions. This is a particular challenge for highly regulated organizations that are under substantial regulatory pressure to prevent unauthorized access to sensitive user and financial data. This pressure also comes from both customers and internal forces; the former want convenience, and the latter want more productive, streamlined processes and enhanced experiences for higher customer retention.

More identity theft reports (21.5%, according to the Federal Trade Commission) were filed in 2022 than all other kinds of complaints, and researchers at Canadian consumer credit firm TransUnion found that synthetic identity fraud increased by over 100% year-over-year. It’s no wonder experts are predicting that by 2029, the market for identity theft protection services will total $28 billion.

Synthetic identity fraud poses significant financial and reputational risks to major digitized organizations as technology enables the creation of realistic-looking identification documents. Successful fraud of this kind can pay off big for bad actors and cost these organizations a lot in terms of both monetary and reputational consequences.

ID fraud detection must-haves

Traditional methods of identity verification involve physically checking documents to verify their security features, holograms, watermarks and expiration dates. This is typically less secure and results in very long response times, consequently providing a negative user experience. Manual checks don’t scale well, either; this method is not well-equipped to manage different peaks in demand. And with synthetic identities becoming more sophisticated and further complicating the landscape, these legacy solutions can’t keep up.

Companies across sectors, including financial services, gaming, and many more, have to ensure their identity verification approach can defeat synthetic identity fraud – their reputations and bottom lines depend on it.

How do you ensure the approach your organization is taking can keep up with today’s demands?

The four must-haves for validating ID documents are tamper checks, automation, cross-referencing with government sources, and opting for a high score severity threshold. Best-in-class document validation providers use advanced techniques like machine learning to detect tampered documents. Next-generation identity document verification solutions that leverage AI and biometrics make the process regulatory-compliant and seamless.

The importance of tamper checks and liveness

Incorporating standards like Optical Character Recognition (OCR), document integrity checks, and paper ID liveness into the verification process can help form the foundation of a robust defense against fraud. OCR technology digitizes the information present on identity documents like passports, driver’s licenses, and national IDs, making it easier to verify the authenticity of the documents and the identity of the people presenting them. Document integrity checks are a set of processes used to assess the authenticity and integrity of a document, making sure that it hasn’t been altered or tampered with. Paper ID liveness requires the document holder to provide a live image or video of the physical paper document during the verification process; this helps ensure the document hasn’t been digitally altered or fabricated.

Biometric comparison helps prevent imposters or fraudsters from successfully using stolen or forged documents. Liveness checks ensure that the image on an identity document is clear and well-defined, enabling accurate and reliable verification. It can tell whether the captured face is a real face and not a picture, video, or mask. A passive liveness solution doesn’t require user actions (blinking, moving the head, or performing any other awkward activity) and is done simultaneously with selfie capture. This minimizes user onboarding time, offers a better UX, and results in more converted users. Some solutions can handle large volumes of users concurrently and are scalable.

Leveraging automation and machine learning

Certain aspects of document validation, such as barcodes and watermarks, are hard to do manually. Machine learning algorithms in the verification process ensure more accurate and efficient fraud detection. Furthermore, automation removes the need for humans in the loop to ensure 100% privacy. Automation can also support rapid scalability (such as for tax season or natural disasters) and protect privacy.

The ability to cross-reference

To boost the effectiveness of identity validation, organizations should conduct additional checks and balances against government sources of truth. Integrating government data verification as an extra layer makes the validation process more reliable and supports in-house document verification efforts – and it’s now possible to automate this step. Organizations need to use multiple signals to combat fraud effectively.

The right scoring

A confidence score is a numerical value given to the overall verification result, showing the level of confidence in how authentic the identity document is and the information it contains. The score is typically generated by looking at several factors, such as those already discussed above. Score severity is related to the confidence score and is used to determine the appropriate action based on the verification results. If the score severity threshold is set high, only verification results with very high confidence scores will be accepted.

Creating trust

As technology continues to advance, it opens new possibilities for using biometrics in identity document validation, fostering a world of collaboration and trust. Recognizing that data security is a shared responsibility, providers and companies can work together to safeguard their collective information. Just make sure to balance user experience with detection by finding a solution that gets the job done without causing too much friction to the end users, which improves user experience and conversion. Look for solutions that include the best-practice criteria described above to ensure a safer and more secure digital environment – not only for organizations but for individuals, as well.