5 Ways to Combat Identity Fraud

What is identity fraud?

Identity fraud is the unauthorized use of an individual’s personal information, such as name, Social Security number or account details to commit fraudulent activities. This type of fraud is often seen in the financial services industry though it occurs in various forms across all industries. Identity fraud is pervasive and continually evolving as bad actors develop new methods to bypass security systems.

Once access is gained to a victim’s financial identity, they can manipulate accounts, withdraw funds, or accumulate debt in the victim’s name, often leading to severe financial and credit damage for the individual affected. Its impact not only affects individual victims but can also threaten an organization’s revenue stream, brand reputation, regulatory compliance, and operational costs.

How are organizations affected by identity fraud?

The impact of identity fraud can be substantial for your organization. Financial services institutions are particularly vulnerable to identity fraud due to the high volume of transactions, the high volume of customer data managed daily and the potential monetary benefit to bad actors. The potential negative outcomes are many, including:

• Financial Losses
• Damage to Brand Reputation
• Regulatory & Legal Consequences
• Operational Disruption
• Increased Security Costs
• Loss of Competitive Edge
• Impact on Partnerships
• Ethical and Industry Standards

How can organizations combat identity fraud?

Organizations should implement a multi-faceted approach to combat identity fraud. Here are some of the important actions they can take:

1. Strong Multi-Factor (MFA) Authentication Methods

Offering secure and flexible forms of verification (e.g., biometrics, document verification, identity proofing, one-time codes, device recognition) makes it much harder for bad actors to gain access, even if they obtain one piece of a user’s information. This approach significantly reduces the risk of identity fraud, as attackers would need multiple forms of authentication to succeed. Here are the most secure types of MFA:

• Biometric Authentication: Biometrics use physical characteristics unique to each individual, such as fingerprints, facial recognition, or voice recognition. These are highly secure because they rely on traits that are difficult to replicate.
• Document Verification: This method involves verifying official documents, such as a government-issued ID, driver’s license, or passport, often during the onboarding process or for high-risk transactions. Selfies – a technique that leverages a combination of biometric verification and liveness detection to confirm the user’s identity – are also used to verify documents.
• Identity Proofing: This method validates the user’s identity by cross-referencing information with third-party databases or using selfies as a method to verify that the person attempting to access an account or complete a transaction is genuinely who they claim to be.
• One-Time Codes (OTCs): One-time codes, often delivered via SMS, email, or an authenticator app, are unique codes that expire after a short period. Even if an attacker gains access to a user’s password, they will still need this additional, time- sensitive code to gain entry.
• Device Recognition: Device recognition, or device fingerprinting, identifies trusted devices through characteristics like the device’s IP address, browser settings, and hardware attributes.

2. Use AI-Powered Fraud Detection

Machine learning and AI are powerful tools that can be used to monitor and detect suspicious behavior in real time. AI can spot user behavior patterns that indicate potential fraud, like unusual login locations, transaction patterns, or account activity. By learning from this historical data, these systems continuously improve their accuracy, making it easier to identify new and evolving fraud tactics. Here’s how AI can be leveraged for fraud detection:

• Behavioral Analysis: AI can monitor user behavior and establish baseline patterns for each user. This might include typical login times, frequently accessed locations, preferred devices, and regular transaction amounts.
• Transaction Monitoring: Machine learning algorithms are effective at analyzing transaction data for irregularities that might indicate fraud, such as multiple high- value transactions in quick succession or unusual purchase locations.
• Real-Time Alerts: AI-powered fraud detection systems can issue real-time alerts when they detect suspicious activity, helping companies respond immediately. This real-time intervention minimizes potential damage by quickly locking down compromised accounts or blocking suspicious transactions until they can be verified.
• Anomaly Detection: AI can identify anomalies by analyzing a variety of data, such as IP addresses, device types, and session durations. By recognizing unusual patterns AI can help detect fraud attempts even if they don’t follow traditional patterns.
• Reduced False Positives: One challenge in fraud detection is balancing security with user experience, as too many false positives can frustrate legitimate customers. AI helps reduce false positives to ensure a smoother user experience while maintaining a high level of security.

3. Adopt Zero Trust Architecture

Zero Trust enforces a “never trust, always verify” zero trust security framework where users must verify their identity at each engagement point, regardless of whether they are inside or outside the organization’s network. This proactive and vigilant approach minimizes risk by assuming any access attempt is a potential threat. Zero Trust is ideal for today’s complex, hybrid digital environments in the following ways:

• Continuous Verification: In a Zero Trust model, verification isn’t a one-time step. Users are continuously re-authenticated and re-verified at every stage, especially when accessing sensitive data or applications. This ongoing verification makes it difficult for unauthorized users to maintain access if they somehow breach the system.
• Least Privilege Access: Zero Trust enforces the principle of least privilege, meaning users are granted the minimum access necessary to perform their tasks. This minimizes the potential damage that could be done if an account is compromised, as the attacker would only have limited access rather than unfettered control. Employees and contractors only have access to specific resources, and permissions are continually reassessed and updated as job roles or requirements change.
• Micro-Segmentation: In a Zero Trust architecture, networks are divided into smaller, isolated segments or zones. This approach is called micro-segmentation and ensures that if an attacker gains access to one part of the network, they cannot freely move to access other systems or data.
• Adaptive Authentication: Zero Trust uses adaptive or context-based authentication to evaluate each access attempt based on factors like location, device, and behavior. If a login attempt is made from an unusual location, on an unrecognized device, or at an odd time, the system can trigger additional authentication steps.
• Device and Endpoint Security: Devices and endpoints are also treated as potential threats, even if they are company-issued. By enforcing strict security measures on devices, Zero Trust prevents compromised or unsecure devices from becoming entry points for attackers.
• Visibility and Analytics: Zero Trust relies on comprehensive monitoring and logging of all user activities with real-time analytics help identify and respond to suspicious behaviors. This visibility enables better insights into how data is accessed and used across the organization.
• Automated Threat Response: Organizations can set up automated responses to potential threats, such as locking down accounts, terminating sessions, or requiring re-authentication. Automation ensures that responses to suspicious activity are immediate.

4. Regularly Train Employees on Security Awareness

Employees are often the first line of defense against identity fraud, as attackers frequently target them to gain access to a company’s systems. Helping employees better understand how to recognize threats like phishing, social engineering, and other tactics used to steal credentials is key to a well-rounded fraud prevention strategy. Regularly updating and training staff on new threats and conducting simulated attacks can significantly reduce the risk of account takeovers. Here are the key focus areas for employee training:

• Phishing Awareness Training: Phishing attacks are still one of the most common and successful methods for credential theft. Regular training – like recognizing red flags and hovering over links before clicking – can help employees spot suspicious emails, texts, and phone calls.
• Social Engineering Awareness: Social engineering tactics exploit human psychology rather than technical vulnerabilities, making them harder to detect. Attackers may impersonate colleagues, vendors, or authority figures to persuade employees to divulge sensitive information. Training employees to recognize social engineering attempts is crucial, and should include:
• Simulated Phishing and Social Engineering Attacks: Conducting simulated phishing emails or social engineering scenarios helps employees experience potential threats in a safe, controlled environment. Using simulations raises employee awareness to be cautious if they receive unusual requests for information or actions.
• Recognizing and Reporting Potential Insider Threats: Sometimes, fraud attempts may come from within the organization. Train employees to recognize signs of insider threats, such as colleagues accessing information they don’t need for their role or discussing sensitive data without authorization.
• Creating a No-Blame Reporting Culture: Employees may hesitate to report suspicious emails or incidents out of fear they’ll be blamed for falling for a scam. Encourage a supportive, no-blame reporting culture where employees feel comfortable reporting potential security incidents without fear of reprisal.

5. Monitor and Secure Privileged Access

To reduce the risk of identity fraud and data breaches, limit access privileges to only those who absolutely need them. Regularly review and update elevated permissions to ensure former employees or contractors no longer have access to your systems and use role- based access control to minimize risk. Here are some best practices for managing access privileges effectively:

• Enforce Least Privilege Access: Grant each employee the minimum level of access they need to perform their job functions. For example, a marketing team member likely does not need access to sensitive financial data. By limiting access, you reduce the chances of unauthorized data exposure if an account is compromised.
• Implement Role-Based Access Control (RBAC): RBAC lets you assign access based on job roles rather than individual users, making it easier to enforce consistent access policies. This simplifies user management and avoids giving too much access to any one individual.
• Periodic Reviews and Audits: Conduct regular audits to review and validate access permissions. This process helps ensure that only current employees, vendors and contractors with an active need for access retain it.
• Automated Provisioning and Deprovisioning: Use automated tools to assign and revoke access as employees join or leave the company or move into new roles. Automating this process reduces human error and ensures that former employees or contractors don’t retain access to systems and data longer than necessary.
• Quickly Revoking Access for Departing Employees: When an employee leaves the company, they should immediately lose their access to all systems and accounts. This reduces the risk of “orphaned accounts” that could be exploited by bad actors.

---

Talk to Our Experts