What Is Identity Proofing and Why Is It Crucial?

Is your current fraud detection system letting imposters slip through? Let’s crack the code on rock-solid identity proofing with this blog. Learn how to leverage AI and ML solutions to streamline processes, & customer journeys, ensure compliance & safeguard your organization.
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Ravi Sandepudi

June 6, 2024

Cybersecurity threats are escalating in tandem with economic volatility, leaving banks increasingly vulnerable. 

The “Cybersecurity: 2022 Banking Industry Survey” by KPMG* reveals that 81% of bankers anticipate a surge in threats, yet 34% admit inadequate investment in cybersecurity. 

While robust security remains essential to safeguard sensitive information and systems, financial institutions (FIs) should prioritize proactive measures to mitigate risks and prevent major incidents before they occur.

This calls for more proactive risk management systems. This is where the concept of identity proofing comes into play as a crucial component of a comprehensive cybersecurity strategy.

Data on cyberattacks and Identity proofing policy

What is Identity Proofing? 

Identity proofing is a comprehensive process that verifies an individual’s identity before granting access to sensitive systems, accounts, or data. This verification ensures that only authorized users gain access, significantly reducing the risk of identity theft, financial fraud, and data breaches.

How It Helps Prevent Bank Fraud and Identity Theft

The Federal Trade Commission (FTC) received a staggering 1.1 million identity theft reports in 2022, and that number barely dipped in 2023. These alarming statistics paint a clear picture: businesses can’t afford to be complacent about security.

However, simply prioritizing security isn’t enough. To build trust and foster long-term success, they need a proactive approach. 

Identity proofing is the first line of defense in this fight. It goes beyond basic verification, rigorously establishing the legitimacy of users and mitigating the risks of identity theft and fraud.

However, before we understand the supporting science, let’s understand how it differs from identity verification.

Identity Proofing vs Identity Verification

Although “identity proofing” and “identity verification” are often used interchangeably, understanding the subtle difference is crucial for robust security. 

Here’s how they differ:

Identity proofing

Identity verification

It’s like when you first join a firm and you have to show your prior experience and other documents to prove that you are who you say you are.

It’s like showing your ID card every day when you enter the official premises to prove that you work here.

It happens only once, when you first sign up for something, like a new school or a library card.

It happens every time you want to use something, like borrowing a book from the library or accessing your school account online.

It’s about making sure that you are a real person and that the information you give about yourself is true.

It’s about making sure that you are the same person who signed up and that nobody else is pretending to be you.

Examples: Showing your passport when you first open a bank account or proving your age with a birth certificate when you sign up for a sports team.

Examples: Using your fingerprint to unlock your phone or entering a password to log in to your computer at school.

Understanding the distinction between identity proofing and verification sets the stage for a deeper exploration into how identity proofing is practically implemented to enhance security.

How Identity Proofing Works

The National Institute of Standards and Technology (NIST) emphasizes maintaining a robust identity-proofing process that adapts to evolving threats and technologies.

This may involve implementing security measures, such as continuous monitoring and risk assessment, fraud detection and prevention mechanisms, regular audits, and compliance checks

NIST’s Special Publication 800-63A sets forth a comprehensive framework for identity proofing. Their 3-step framework to ensure authenticity includes:

Step 1 – Resolution

Distilling a claimed identity to a singular, unique entity within the system’s user base. This ensures that an identity is not only claimed but recognized as a distinct and singular entry.

Step 2 – Validation

Collecting and meticulously examining identifying information provided by the user. Validation serves a dual purpose: 

  • Confirming the veracity of the supplied evidence as both accurate and authentic; 
  • Establishing that the claimed identity has a legitimate presence in the real world.

Step 3 – Verification

Ensuring the claimed identity is indeed tied to the person presenting it. This involves a conclusive demonstration that the individual claiming the identity is the rightful owner of that identity.

Approaches to ID Proofing

With the NIST framework in mind, let’s examine the practical approaches to identity proofing, which can be categorized into data-centric and document-centric methods.

Data-Centric Approach

The Data-Centric Approach focuses on verifying Personally Identifiable Information (PII) such as names, social security numbers, and addresses against third-party databases. This method is designed to assess the accuracy of self-reported information, confirming the authenticity of an individual’s identity claims. 

It is cost-effective and can mitigate known fraud risks through network intelligence. However, it can be complex to integrate into systems and may result in false positives.

Document-Centric Approach

The Document-Centric Approach, as outlined by Gartner, requires individuals to upload a photo of a government-issued ID and take a live selfie for liveness detection. 

This approach checks static information and the validity of the document, ensuring that the ID photo matches the person. While generally reliable, this method must be regularly updated to guard against sophisticated fraud and maintain its effectiveness in identity verification.

How Do Banks Verify Your Identity?

To keep customer’s money safe, banks employ a multi-pronged approach. 

This approach includes the use of a sophisticated toolbox of methods to verify your identity and protect accounts from unauthorized access. 

Here’s a breakdown of some common methods:

Government-Issued Identification

Banks require a valid government-issued ID to confirm your identity when opening an account or for certain transactions.

Proof of Address

To verify your residence, banks ask for documents like utility bills or rental agreements showing your current address.

Social Security Number (SSN)

Your SSN serves as a crucial identifier for banking activities.

Biometric Data

Advanced banks use biometrics, such as fingerprints or facial recognition, for secure identity verification.

Knowledge-Based Authentication (KBA)

You may be asked to answer personal security questions or provide specific transaction details only you would know.

Two-Factor Authentication (2FA)

For online transactions, banks often send a unique code to your mobile device as an additional security measure.

From Paper to Pixels: How Identity Verification Evolved

Banks have traditionally relied on verifying identity through physical documents. However, with a demand for a shift, there has been a significant increase in tech-driven solutions.  

Limitations of Traditional Manual Methods

Traditional manual methods of identity proofing, such as document verification and in-person interviews, are fraught with limitations:

  • High False Rejection Rates: 

 Manual processes were prone to inaccuracies, leading to a significant number of legitimate customers being wrongly rejected. This not only resulted in customer dissatisfaction but also represented lost revenue opportunities for banks.

  • Time-Consuming and Costly: 

Verifying identities manually was a slow and labor-intensive process. It required significant human resources and was costly, making it unsustainable in the long run, especially for large-scale operations.

  • Prone to Human Error: 

The manual verification process was highly susceptible to human error. Misinterpretation of documents or oversight could lead to incorrect verification, increasing the risk of identity theft and fraud.

Digital Identity Proofing Solutions

To address the inefficiencies and security vulnerabilities of manual methods banks began adopting digital identity proofing solutions. 

Digital Identity Verification

Knowledge-Based Authentication (KBA) 

As an initial step towards digital verification, KBA involved asking users to answer personal questions based on their history. However, this method soon showed vulnerabilities to social engineering and data breaches.

Two-Factor Authentication (2FA) 

2FA added an extra layer of security by requiring users to provide a second form of verification, such as a one-time password sent to their mobile device. While 2FA enhanced security, it still was at the risk of SIM swapping attacks. 

Biometric Authentication

It offered a more secure alternative as unique physical characteristics like fingerprints or facial recognition were employed. However, biometric data, if compromised, could not be easily changed, presenting its own set of risks.

The AI/ML Revolution in Cybersecurity 

The adoption of large language model technology in cybersecurity is catalyzing a shift from reactive to proactive defense mechanisms. Take the use of AI in the ID proofing process, for example, the process that usually goes through is;

Data Collection

AI systems gather diverse user data, including biometrics and behaviors, forming the basis for identity verification.

Pattern Recognition

This data is then analyzed to identify unique user patterns, continually adapting to behaviors for accurate identification.

Anomaly Detection 

AI/ML also continuously monitors user activities, swiftly flagging any deviations from established patterns as potential threats.

Increased Accuracy and Speed

AI/ML-driven data integration vastly improves ID proofing by analyzing large data volumes in real time, ensuring faster and more precise results compared to manual methods.

Reduced Friction and Improved User Experience

With streamlined identity verification processes, friction is minimized. Furthermore, automated business and customer onboarding creates a positive experience for both parties.

Enhanced Fraud Detection and Risk Assessment Capabilities

Device fingerprinting technology such as DeviceIntel assesses risk levels and adjusts the identity-proofing process accordingly. These techs use real-time analytics to identify risks based on digital identities and behaviors, enabling tailored security measures.

Gain real-time insights and accelerate decision-making with Effectiv’s unified dashboard.

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Identity Proofing: Best Practices and Considerations

Biometric authentication methods isometric composition with mobile device fingerprint identification dna match and facial recognition vector illustration

According to a 2021 study by Javelin Strategy & Research, identity fraud affected 15.4 million individuals in the United States alone, resulting in $56 billion in losses. As we embrace digital solutions and AI-driven technologies for ID proofing, it becomes imperative to follow a comprehensive strategy that not only enhances security but also ensures compliance and user satisfaction. 

When implementing identity proofing, consider the following best practices:

Next-Generation Verification

Incorporate verifications such as Multi-Factor Authentication (MFA) mechanisms such as SMS codes, biometric verification, or hardware tokens to add layers of security beyond mere passwords.

Leverage biometric data such as fingerprints, facial recognition, or iris scans for reliable and convenient user authentication.

Adapting to Trends

Stay adaptable by embracing emerging technologies and trends in identity proofing, such as AI and ML models, to enhance identity verification processes. Implement biometric authentication, liveness detection, and document verification to boost security and prevent fraud. 

Explore tools to analyze user behavior and assess risk to create unique profiles and spot suspicious activities. Explore continuous authentication and federated identity management for smooth and secure experiences across different platforms. By keeping up with the latest developments, organizations can prepare for the future and stay competitive in the digital world.

Privacy and Compliance

Prioritize user privacy and comply with regulations such as the European Union’s General Data Protection Regulation (GDPR) and state laws like the California Consumer Privacy Act (CCPA) by ensuring transparent data handling practices.

Balancing Security and User Experience

Strike a balance between stringent security measures and a seamless user experience to avoid deterring legitimate users. Employ adaptive authentication and user-centric design to maintain robust security without compromising the ease and speed of user interactions, thus retaining customer satisfaction and trust.

Collaboration with Experts

Partner with reputable identity verification service providers such as Effectiv to streamline the implementation and management of identity-proofing solutions. Leverage their advanced technologies and deep domain knowledge. This collaboration helps in refining identity proofing frameworks, ensuring compliance, and enhancing the overall security infrastructure with expert insights and innovations.

Blueprint for AI/ML Integration in Identity Proofing Process

To successfully integrate AI and ML into your identity-proofing process, follow these steps:

Step 1: Data Collection and Analysis

Begin by gathering comprehensive datasets containing various forms of user information, including biometric data, personal identifiers, and behavioral patterns. AI algorithms can analyze this data to establish a baseline for legitimate user behavior.

Step 2: Model Training and Validation

Utilize ML techniques to train models on historical data, teaching them to recognize patterns associated with valid identity verification. Continuously validate and refine these models to adapt to evolving fraud tactics and user behavior.

Step 3: Real-time Monitoring and Detection

Implement AI-powered systems capable of monitoring user interactions in real-time. These systems can detect anomalies and suspicious activities indicative of fraudulent behavior, triggering additional verification steps when necessary.

Step 4: Adaptive Risk Assessment

Develop AI-driven risk assessment models that dynamically adjust risk scores based on contextual factors such as transaction amount, device information, and user location. This enables tailored identity verification measures for different risk levels.

Step 5: User Experience Optimization

Strive for a seamless user experience by leveraging AI to streamline the identity verification process. Techniques such as biometric authentication and natural language processing can simplify verification steps while maintaining security standards.

Step 6: Compliance and Transparency

Ensure compliance with regulatory requirements by incorporating AI/ML models that adhere to data privacy laws such as GDPR and CCPA. Transparency in AI decision-making processes is essential to build trust and accountability.

Navigating Compliance Challenges in Identity Proofing

The financial services sector faces a complex landscape of regulations and standards for verifying customer identities. Know Your Customer (KYC) and Anti-Money Laundering (AML) protocols remain critical cornerstones, but navigating their global and regional variations can be challenging. Failure to comply with these regulations exposes institutions to significant legal repercussions, financial penalties, and reputational damage.

Ensuring compliance in identity proofing is a critical yet complex challenge for organizations. According to a recent study by the Ponemon Institute, non-compliance with identity proofing regulations can cost organizations an average of $14.8 million per incident. One key challenge is keeping up with changing regulations, such as the European Union’s GDPR and NIST 800-63-3 guidelines that help organizations choose the right security measures for managing identities.

Regulatory fines for non-compliance with identity-proofing standards can be crippling, often exceeding millions of dollars. The year 2020 saw a staggering $2.2 billion in fines levied against companies – a potential death knell for a business.

The evolving regulatory landscape-related challenges require a constant lookout at the trends and predictions that will shape the future of identity proofing.

The Future of Identity Proofing: Trends, Prediction 

The future of identity proofing is likely to see increased integration of biometric technologies and cloud solutions, driven by the need for more adaptable and scalable security infrastructures. Technologies such as biometric authentication, decentralized identity solutions (e.g., blockchain-based identity), and advancements in artificial intelligence and machine learning are the key drivers.

According to a Biometric Update report, the identity-proofing industry is predicted to grow from $23.3 billion in 2021 to $49.5 billion in 2026, fueled by the widespread adoption of technologies like fingerprint and face recognition. Cloud technologies are expected to outpace on-premise solutions, promoting a shift towards more flexible identity-proofing infrastructures.

The regulatory landscape is also shifting, with a focus on establishing consistent privacy and legal frameworks for biometric data collection and digital IDs. This emphasizes the need to balance security needs with privacy rights.

Remote Identity Verification: Balancing Security and Convenience

Remote identity verification plays a vital role in protecting customer privacy. By eliminating the need for physical disclosure of sensitive information, FIs and businesses can ensure data confidentiality remains a top priority. This not only fosters trust but also demonstrates a commitment to respecting and safeguarding personal data. In an era where data breaches can have severe consequences, prioritizing data confidentiality through identity proofing is a must.

smartphone woman face scan recognition biometric vector illustration

By prioritizing identity proofing, FinTechs create a win-win scenario. Customers enjoy a secure and user-friendly experience, while banks can build a stronger, more resilient business. It’s a strategic investment that pays off in the long run.

Strengthening Identity Proofing with AI/ML

Today, robust identity proofing isn’t just about compliance – it’s a strategic weapon. Large language models integrated with biometrics and advanced algorithms offer unparalleled security and streamlined onboarding, giving you a clear edge.

Effectiv’s AI-driven features and solutions ensure frictionless compliance with KYC/AML regulations, freeing risk teams to focus on core business activities. 

Imagine the cost savings and efficiency gains from faster, smoother customer onboarding. More importantly, these technologies minimize fraud risk, protect brand reputation, and safeguard the bottom line – imperative for building long-term success and resilience.

Gain a Competitive Advantage in Risk Management with Effectiv’s Real-Time Risk Insights.

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What is an example of identity proofing?

An example of identity proofing is verifying a person’s government-issued ID, such as a passport or driver’s license, along with biometric data like a facial recognition scan, to confirm their identity before granting access to a service or system.

What is the difference between identity proofing and authentication?

Identity proofing establishes the unique identity of an individual, while authentication verifies that the person attempting to access a system or service is who they claim to be, often through methods like passwords or biometric data.

What is digital identity proofing?

Digital identity proofing is the process of verifying an individual’s identity through digital means, such as analyzing biometric data, verifying government-issued IDs, or using knowledge-based authentication questions, before granting access to digital services or systems.

What is the identity-proofing level of assurance?

Identity proofing level of assurance refers to the degree of confidence in the identity verification process, with higher levels requiring more stringent methods like biometric data and in-person verification, while lower levels may rely on less secure methods like knowledge-based authentication.

What can happen without Proper Identity Proofing?

Without proper identity proofing, organizations face increased risks of fraud, data breaches, and unauthorized access to sensitive information, which can lead to financial losses, reputational damage, and legal consequences.

Which Sectors Require Identity Proofing?

Identity proofing is crucial in sectors that handle sensitive personal and financial information, such as banking, healthcare, government services, and e-commerce, to prevent fraud and ensure compliance with regulations like KYC and AML.

How can organizations improve their identity-proofing processes?

Organizations can improve their identity-proofing processes by implementing multi-factor authentication (MFA), leveraging biometric data, staying updated with the latest trends and technologies, ensuring compliance with relevant regulations, and striking a balance between security and user experience.

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