What Is Photo ID Verification?
Identity verification is a practice of ensuring that someone is who they say they are. This practice guarantees that users are legitimate and that someone else is not abusing a person’s identity or creating false identities. Photo ID verification is a form of identity verification that identifies a person by comparing their actual appearance to an official ID photo.
When verifying identities, there are multiple methods you can use, including manual verification and digital verification. Manual verification occurs when a person is seen in person and is asked to present proof of their identity. For example, a driver’s license or passport. This method is often used in financial institutions, government offices, or adult-only venues like bars. It relies on the authority of the ID issuing body to have already verified the person’s identity.
Digital verification also relies on the authority of issuing institutions but cannot use possession of a hard copy ID as a means of proof. Instead, digital verification must rely on inputs from a person that cannot be immediately visually matched to the details on their ID.
In this article, you will learn:
- The Photo ID Verification Process
- The Technology Behind Photo ID Verification
- Identity Document Analysis
- Face Detection
- Trends in Identity Verification
- Artificial Intelligence
- Increased Concern for Security
- Decreased In-person Interactions
- Photo ID Verification with BlueCheck
The Photo ID Verification Process
While in-person photo verification is often a reliable way of verifying someone’s identity, it can be slow and requires face-to-face interaction. As many organizations move to online operations, these face-to-face situations are less frequent or helpful. However, organizations still need to be able to verify users, so digital means must be adopted.
While digital photo ID verification has not yet been perfected, numerous systems have already been developed and are in use. Generally, these systems implement the following workflow:
- ID collection—users upload their photo through a file upload screen or take a photo of themselves or their ID through a device camera. Generally, users are asked to submit a photo of the ID itself and a photo with them holding the ID as proof of possession.
- Comparison of ID to existing datasets—ID images are processed using optical character recognition (OCR) technologies, and the information from the ID is extracted. This information is then compared to known ID info stored in proprietary or public databases.
- Machine learning analysis of ID—algorithms are used to detect flaws, suspicious defects, or known security traits of the ID. These results can be used to rule out forgeries or manipulated images.
- Manual review of ID—if an ID passes automatic review, it is reviewed manually to confirm that all information makes sense. Digital solutions may also skip to this step directly if ID information is incomplete or if algorithms cannot process the information.
- ID is verified or rejected—the results are returned to the organization and possibly the user. Typically, results are also stored by the organization for future validation checks. Hard copies of the verification information may also be stored for auditing purposes.
The Technology Behind Photo ID Verification
Several technologies are commonly implemented in photo ID verification solutions. In addition to standard technologies, such as digital cameras and web applications, the following technologies form the base of these solutions.
Identity Document Analysis
ID document analysis technologies can catalog known characteristics of ID documents and compare a submitted ID against those characteristics. For example, comparing whether the edges of IDs are appropriately rounded, whether color variants match, which fonts or font sizes are used, and whether barcodes or holograms are valid.
Typically, these technologies take the information from these comparisons to generate a reliability score. If this score is too low, the ID is rejected. It is accepted or passed for manual verification if the score meets a certain threshold.
Face detection technologies enable solutions to measure and map the face in a photo ID or user image. Measurements are taken, or maps are created based on the location or arrangement of facial features. For example, the distance between a person’s eyes, the shape of their nose, or the existence of identifying marks like freckles or moles.
These measurements and maps are then converted into feature vectors or faceprints, essentially a numerical code representing that face. These vectors can be compared to known values to determine a match.
Trends in Identity Verification
Digital photo ID verification is still evolving as more organizations move to digital operations. As these technologies evolve, several trends are emerging, including AI, increased concern for ID fraud, and the increased use of digital services.
AI and machine learning technologies that allow for image classification and recognition significantly advance photo ID verification solutions. As these technologies become more reliable, the need for manual verification decreases.
These technologies can enable organizations to verify various IDs, including from other regions or countries. This is because attached databases can store many more data points that human verifiers can remember or access quickly. Additionally, AI can be used to account for factors like aging or glasses that may deceive human verifiers more accurately.
Increased Concern for Security
Many aspects of a consumer’s life are now tied to digital systems. This means that identity theft or fraud is becoming a larger concern.
While fraud was limited to local areas or communities that the consumer may have visited in the past, now, a user’s information is accessible globally. Due to this increased possibility, many consumers want accurate and consistent use of ID verification, particularly when it comes to financial information.
Identity theft is a major concern for organizations. It can expose an organization to insider threats and allow attackers to perform privilege escalation, gaining access to critical systems.
Decreased In-person Interactions
Even before the effects of COVID-19, many consumers were choosing online options over in-person. This is seen across industries, including eCommerce, online banking, and telehealth. While these online services are often more convenient for the customer, they can make it more difficult for organizations to verify a customer’s identity.
Through the adoption of digital verification methods, organizations can continue to serve these customers without risking the customer’s information. Additionally, if used carefully, these systems can even provide greater protections for both customers and organizations since verification is logged and auditable.
Photo ID Verification with BlueCheck
BlueCheck's industry-leading identity verification infrastructure enables merchants to grow their business faster. Serving a wide variety of industries, our solutions are custom-tailored to the unique needs of our customers.