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The Ultimate Guide to Identity Proofing

Updated : February 21, 2025 Published: March 13, 2023 by Guest Contributor

What Is Identity Proofing?

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Identity proofing, authentication and management are becoming increasingly complex and essential aspects of running a successful enterprise. Organizations need to get identity right if they want to comply with regulatory requirements and combat fraud.

It’s also becoming table stakes for making your customers feel safe and recognized. 63 percent of consumers expect businesses to recognize them online, and 48 percent say they’re more trusting of businesses when they demonstrate signs of security.

Identify proofing is the process organizations use to collect, validate and verify information about someone. There are two goals — to confirm that the identity is real (i.e., it’s not a synthetic identity) and to confirm that the person presenting the identity is its true owner.

The identity proofing process also relates to and may overlap with other aspects of identity management.

Identity proofing vs identity authentication

Identity proofing generally takes place during the acquisition or origination stages of the customer lifecycle — before someone creates an account or signs up for a service. Identity authentication is the ongoing process of re-checking someone’s identity or verifying that they have the authorization to make a request, such as when they’re logging into an account or trying to make a large transaction.

How does identity proofing work?

Identity proofing typically involves three steps: resolution, validation, and verification.

  • Resolution: The goal of the first step is to accurately identify the single, unique individual that the identity represents. Resolution is relatively easy when detailed identity information is provided. In the real world, collecting detailed data conflicts with the need to provide a good customer experience. Resolution still has to occur, but organizations have to resolve identities with the minimum amount of information.
  • Validation: The validation step involves verifying that the person’s information and documentation are legitimate, accurate and up to date. It potentially involves requesting additional evidence based on the level of assurance you need.
  • Verification: The final step confirms that the claimed identity actually belongs to the person submitting the information. It may involve comparing physical documents or biometric data and liveness tests, such as a comparison of the driver’s license to a selfie that the person uploads.

Different levels of identity proofing may require various combinations of these steps, with higher-risk scenarios calling for additional checks such as biometric or address verification. Service providers can implement a range of methods based on their specific needs, including document verification, database validation, or knowledge-based authentication.

Building an effective identity proofing strategy

By requiring identity proofing before account opening, organizations can help detect and deter identity fraud and other crimes. You can use different online identity verification methods to implement an effective digital identity proofing and management system. These may include:

  • Document verification plus biometric data: The consumer uploads a copy of an identification document, such as a driver’s license, and takes a selfie or records a live video of their face.
  • Database validations: The proofing solution verifies the shared identifying information, such as a name, date of birth, address and Social Security number against trusted databases, including credit bureau and government agency data.
  • Knowledge-based authentication (KBA): The consumer answers knowledge-based questions, such as account information, to confirm their identity. It can be a helpful additional step, but they offer a low level of assurance, partially because data breaches have exposed many people’s personal information.

In part, the processes you’ll use may depend on business policies, associated risks and industry regulations, such as know your customer (KYC) and anti-money laundering (AML) requirements. But organizations also have to balance security and ease of use.

Each additional check or requirement you add to the identity proofing flow can help detect and prevent fraud, but the added friction they bring to your onboarding process can also leave customers frustrated — and even lead to customers abandoning the process altogether.

Finding the right amount of friction can require a layered, risk-based approach. And running different checks during identity proofing can help you gauge the risk involved.

For example, comparing information about a device, such as its location and IP address, to the information on an application. Or sending a one-time password (OTP) to a mobile device and checking whether the phone number is registered to the applicant’s name.

With the proper systems in place, you can use high-risk signals to dynamically adjust the proofing flow and require additional identity documents and checks. At the same time, if you already have a high level of assurance about the person’s identity, you can allow them to quickly move through a low-friction flow.

Experian goes beyond identity proofing

Experian builds on its decades of experience with identity management and access to multidimensional data sources to help organizations onboard, authenticate and manage customer identities. Our identity proofing solutions are compliant with National Institute of Standards and Technology (NIST) and enable agencies to confidently verify user identities prior to or during account opening, biometric enrollment or while signing up for services.

 
This article includes content created by an AI language model and is intended to provide general information.

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Fake IDs have been around for decades, but today’s fraudsters aren’t just printing counterfeit driver’s licenses — they’re using artificial intelligence (AI) to create synthetic identities. These AI fake IDs bypass traditional security checks, making it harder for businesses to distinguish real customers from fraudsters. To stay ahead, organizations need to rethink their fraud prevention solutions and invest in advanced tools to stop bad actors before they gain access. The growing threat of AI Fake IDs   AI-generated IDs aren’t just a problem for bars and nightclubs; they’re a serious risk across industries. Fraudsters use AI to generate high-quality fake government-issued IDs, complete with real-looking holograms and barcodes. These fake IDs can be used to commit financial fraud, apply for loans or even launder money. Emerging services like OnlyFake are making AI-generated fake IDs accessible. For $15, users can generate realistic government-issued IDs that can bypass identity verification checks, including Know Your Customer (KYC) processes on major cryptocurrency exchanges.1 Who’s at risk? AI-driven identity fraud is a growing problem for: Financial services – Fraudsters use AI-generated IDs to open bank accounts, apply for loans and commit credit card fraud. Without strong identity verification and fraud detection, banks may unknowingly approve fraudulent applications. E-commerce and retail – Fake accounts enable fraudsters to make unauthorized purchases, exploit return policies and commit chargeback fraud. Businesses relying on outdated identity verification methods are especially vulnerable. Healthcare and insurance – Fraudsters use fake identities to access medical services, prescription drugs or insurance benefits, creating both financial and compliance risks. The rise of synthetic ID fraud Fraudsters don’t just stop at creating fake IDs — they take it a step further by combining real and fake information to create entirely new identities. This is known as synthetic ID fraud, a rapidly growing threat in the digital economy. Unlike traditional identity theft, where a criminal steals an existing person’s information, synthetic identity fraud involves fabricating an identity that has no real-world counterpart. This makes detection more difficult, as there’s no individual to report fraudulent activity. Without strong synthetic fraud detection measures in place, businesses may unknowingly approve loans, credit cards or accounts for these fake identities. The deepfake threat AI-powered fraud isn’t limited to generating fake physical IDs. Fraudsters are also using deepfake technology to impersonate real people. With advanced AI, they can create hyper-realistic photos, videos and voice recordings to bypass facial recognition and biometric verification. For businesses relying on ID document scans and video verification, this can be a serious problem. Fraudsters can: Use AI-generated faces to create entirely fake identities that appear legitimate Manipulate real customer videos to pass live identity checks Clone voices to trick call centers and voice authentication systems As deepfake technology improves, businesses need fraud prevention solutions that go beyond traditional ID verification. AI-powered synthetic fraud detection can analyze biometric inconsistencies, detect signs of image manipulation and flag suspicious behavior. How businesses can combat AI fake ID fraud Stopping AI-powered fraud requires more than just traditional ID checks. Businesses need to upgrade their fraud defenses with identity solutions that use multidimensional data, advanced analytics and machine learning to verify identities in real time. Here’s how: Leverage AI-powered fraud detection – The same AI capabilities that fraudsters use can also be used against them. Identity verification systems powered by machine learning can detect anomalies in ID documents, biometrics and user behavior. Implement robust KYC solutions – KYC protocols help businesses verify customer identities more accurately. Enhanced KYC solutions use multi-layered authentication methods to detect fraudulent applications before they’re approved. Adopt real-time fraud prevention solutions – Businesses should invest in fraud prevention solutions that analyze transaction patterns and device intelligence to flag suspicious activity. Strengthen synthetic identity fraud detection – Detecting synthetic identities requires a combination of behavioral analytics, document verification and cross-industry data matching. Advanced synthetic fraud detection tools can help businesses identify and block synthetic identities. Stay ahead of AI fraudsters AI-generated fake IDs and synthetic identities are evolving, but businesses don’t have to be caught off guard. By investing in identity solutions that leverage AI-driven fraud detection, businesses can protect themselves from costly fraud schemes while ensuring a seamless experience for legitimate customers. At Experian, we combine cutting-edge fraud prevention, KYC and authentication solutions to help businesses detect and prevent AI-generated fake ID and synthetic ID fraud before they cause damage. Our advanced analytics, machine learning models and real-time data insights provide the intelligence businesses need to outsmart fraudsters. Learn more *This article includes content created by an AI language model and is intended to provide general information. 1 https://www.404media.co/inside-the-underground-site-where-ai-neural-networks-churns-out-fake-ids-onlyfake/

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