Identity fraud has reached staggering levels. In 2022, 5.1 million reports were made with 46 percent related to fraud and 21 percent tied to identity theft. But what is ID proofing and why is it considered an essential layer of scrutiny for protecting innocent people from identity theft and fraud?
Source: The Federal Trade Commission
What is Identity Proofing?
Identity proofing, also known as identity authentication, is a crucial process of verifying the legitimacy of an individual’s identity claims, ensuring that the person accessing a system or service is indeed who they claim to be.
How Does Identity Proofing Work?
Identity proofing involves a multi-faceted approach to establishing the authenticity of an individual’s identity. It goes beyond mere identity verification, which confirms whether the presented credentials are valid. Instead, proofing delves deeper into the verification process, encompassing several key elements.
Initiation: Proofing begins when an individual seeks access to a system or service, prompting the need for proofing.
Attribute and Evidence Collection: During this phase, various attributes and pieces of evidence are collected to corroborate the identity claim. Evidence may include personal information, documents, biometrics, and historical data.
Verification: Collected data is meticulously cross-checked and verified against trusted sources to ensure accuracy. Verification may involve scrutinizing documents, running background checks, or confirming biometric traits like fingerprints or facial recognition.
Binding to the Applicant: Once the identity is verified, it is securely bound to the applicant, creating a strong link between the individual and their credentials.
Access Control: Proofing establishes the foundation for robust access control mechanisms, allowing legitimate users to access systems while keeping unauthorized users at bay.
Why is ID Proofing Important?
There’s a clear and undeniable link between ID authentication and fraud. Proofing is essential for preventing fraud by implementing safeguards that protect sensitive information. Proofing enhances security and trust in digital interactions in the following ways:
Verification of Authenticity: Proofing ensures that the individual claiming a particular identity is, in fact, who they say they are. This helps prevent unauthorized access to systems, services, or data, strengthening security.
Fraud Prevention: It acts as a robust defense against identity theft and fraudulent activities. By thoroughly verifying an individual’s identity, it becomes significantly more challenging for malicious actors to impersonate others for financial or personal gain.
Compliance: Many industries, such as finance and healthcare, are bound by strict regulatory requirements. Proofing helps organizations adhere to these regulations by ensuring that only authorized individuals access sensitive information or services.
Risk Mitigation: Proofing helps assess the level of risk associated with a particular transaction or interaction. Based on the proofed identity, organizations can apply appropriate security measures, such as multi-factor authentication, to mitigate potential risks.
Enhanced User Experience: While security is paramount, proofing also contributes to a smoother user experience. Legitimate users can access services more conveniently and with confidence, knowing their identity is protected.
Protection of Personal Data: Proofing safeguards personal and sensitive data by confirming that only authorized individuals can access it. This is especially important in an era of increasing data breaches and privacy concerns.
Trust Building: Effective Identity authentication builds trust between users and organizations. Users are more likely to engage with and trust platforms and services that prioritize their identity and security.
Methods for Implementing ID Proofing
There are several methods and techniques used to verify an individual’s identity, all of which enhance security and trust in digital interactions. Here are some common methods of identity authentication proofing:
Biometric Verification: Biometrics provide a high level of security as they are difficult to forge and require the user’s physical presence. Using unique physical or behavioral traits to confirm identity, such as fingerprint recognition, facial recognition, iris scanning, voice recognition, and even palm vein authentication adds a strong layer of security.
Knowledge-Based Authentication (KBA): KBA verifies identity by asking user-specific knowledge-based questions, such as personal details or historical information. The user must provide accurate answers, which are then compared to predefined data. KBA is commonly used in account recovery and password reset processes.
Database Methods: This method checks an individual’s identity against databases containing personal information, such as government records, credit bureaus, or public records.
Two-Factor Authentication (2FA): 2FA combines two different authentication methods to confirm identity. For example, it may require something the user knows (password) and something the user has (a mobile device for receiving a one-time code). This adds an extra layer of security making it harder to impersonate a user.
Document Verification: Identity documents like passports, driver’s licenses, and ID cards are scanned or photographed and then verified for authenticity. While many deepfakes are able to produce seemingly convincing doubles, advanced technology can detect forged or tampered documents, ensuring that the presented ID is legitimate.
Online Verification: Proofing leverages online data sources and digital trails to confirm an individual’s identity. This includes analyzing online activities, email addresses, and social media profiles to establish identity credibility.
These methods can be used individually or in combination, depending on the level of security and trust required for a specific digital interaction.
Examples of ID Proofing
Identity proofing can be used in various ways, from age verification to business verification. Here are three ways it is being used today:
Online Banking With Biometric Verification
Biometric Verification uses unique physical or behavioral characteristics to verify identity. Examples include fingerprints, facial recognition, iris scans, and voice recognition. Biometric verification has become a common choice for banks today. Most leverage device fingerprint readers, allowing clients to scan fingerprints for account authentication.
Account Recovery With KBA
KBA involves asking individuals questions that only they should know the answers to, such as personal information (e.g., mother’s maiden name, first pet’s name). Medical insurance companies and other organizations use KBA as part of their verification process to confirm a client’s identity during an account recovery.
Tenant Verification Using Credit Bureau-Based Authentication
Credit Bureau-Based Authentication is commonly used in financial and lending institutions to assess creditworthiness and detect fraudulent applications. When performing a credit check as part of a property lease application, an individual’s financial history and credit reports are used to verify their identity and creditworthiness.
During the verification process, the user’s credit information is checked against records maintained by credit bureaus. If the provided information matches the credit report, it is considered a successful identity verification.
The Need for a Hybrid Approach
Fraud has become harder to detect today due to the rise of deepfake technology. However, smart solutions that combine several detection methods, layered to spot fakes and fraud, have proven effective for the following reasons:
Enhanced Accuracy: Combining AI machine learning algorithms with human expertise results in a more accurate and reliable identity verification process. Machine learning can quickly analyze vast amounts of data, while human experts can provide nuanced assessments, reducing the chances of false positives or false negatives.
Fraud Prevention: Hybrid approaches leverage the strengths of multiple detection methods to identify sophisticated fraud attempts. Machine learning algorithms can identify patterns indicative of fraud, such as analyzing subtle behavioral cues, making it harder for fraudsters to bypass security measures.
Scalability: Machine learning allows for scalability, making it possible to process a high volume of identity verifications efficiently.
Adaptability: Machine learning models can continuously learn from new data and adapt their algorithms, making hybrid approaches adaptable to evolving fraud tactics.
Complex Cases: In situations where identity verification is challenging due to factors like incomplete data or unusual circumstances, human experts can provide invaluable insights and decision-making capabilities that machines may struggle with.
Regulatory Compliance: Some regulations may require human oversight in the identity verification process. A hybrid approach ensures compliance with such requirements while still benefiting from automation’s efficiency.
User Experience: Layered detection approaches aim to balance stringent security with a smooth user experience. By minimizing false positives and providing quick responses, users are more likely to have a positive interaction during the verification process.
Outsmart fraud, minimize abandonment, and unleash revenue potential
As identity fraud grows, there’s ample value in leveraging ID proofing. Forward-thinking organizations can better position themselves as safer, customer-focused entities by ensuring that sensitive customer information stays protected. And with the use of layered detection and security, they can provide a much-needed defense against fraud, creating hard-to-overcome barriers for fraudsters.
AU10TIX is the only identity verification solution that delivers zero human intervention KYC and AML solutions that are fast without compromising compliance. Our solution works on four critical levels to provide the safest, most secure, and smoothest user experience.