Securing the Contact Center: Why Fraud is Moving to Customer Support

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<p>For years, organizations viewed the contact center strictly as a service hub. The primary goal was to resolve customer issues quickly and efficiently, and security was often a secondary concern — managed through basic <a href="https://www.socure.com/glossary/identity-verification">identity verification</a> questions or simple passcodes.</p>
<p>That dynamic has shifted. As companies across all industries have hardened their login perimeters with multi-factor authentication (MFA) and device fingerprinting, fraudsters have pivoted to a more vulnerable target, <a href="https://www.socure.com/blog/call-center-fraud">increasingly targeting the support team</a>.</p>
<p>The modern contact center is no longer just a place for service, but a critical defensive line against sophisticated fraud attacks.</p>
<p>Whether through live chat, email, or traditional voice channels, bad actors are targeting support agents to bypass security controls — leveraging social engineering to reset passwords, update contact information, or unlock dormant accounts. For executives, the challenge is securing these support channels without dismantling the speed and efficiency that customers demand.</p>
<h3>How Fraud Attacks Scale in Support Channels</h3>
<p>The threat landscape facing support teams has grown from sporadic social engineering to organized fraud operations. In the past, a fraudster might have spent hours grooming a specific target. Today, criminal networks utilize automation and AI to execute attacks at scale across every available support channel.</p>
<p>Live chat has emerged as a particularly attractive vector for these attacks. The same efficiency gains that make chat desirable for businesses — such as concurrent sessions and automation — make it ideal for fraudsters. They can utilize Large Language Models (LLMs) to generate perfectly scripted, context-aware requests that mimic legitimate customer urgency. These tools allow a single bad actor to conduct dozens of simultaneous conversations with support agents to probe for a weakness in the verification process.</p>
<p>However, the threat is not limited to chat. Fraudsters treat the contact center as a comprehensive menu of options. If they encounter friction on a voice call, they pivot to chat. If the chatbot denies a request, they attempt to manipulate a human agent. The objective is to manipulate the support function to gain unauthorized access or benefits by any means necessary.</p>
<h3>Lack of Visibility in Support Interactions</h3>
<p>The core vulnerability in most contact center operations is a lack of visibility. Support agents, whether human or virtual, are trained to empathize and assist. They operate in an environment designed for trust. When a user claims to be locked out of an account or requests a refund, the primary objective for the agent is to resolve the issue rather than to interrogate the user.</p>
<p>This service-first mindset becomes a liability when the person on the other end is a criminal utilizing a stolen identity. In a digital support interaction, the agent cannot see who is actually behind the screen. They see a customer name and a verified phone number, but they often lack the tools to verify the integrity of the device or the network connection.</p>
<p>Fraudsters exploit this blindness by using emulator farms to mimic mobile devices and residential proxies to mask their true location. To a legacy support system, a request coming from a botnet in a foreign country can appear identical to a legitimate request from a customer’s living room. Relying on an agent to detect these sophisticated technical anomalies is ineffective.</p>
<h3>Refund Fraud &amp; Policy Abuse Risks</h3>
<p>While <a href="https://www.socure.com/glossary/account-takeover">account takeover</a> grabs the headlines, support centers face a spectrum of fraud types that damage the bottom line. Refund fraud and policy abuse, for example, have become rampant in retail and service industries.</p>
<p>In these scenarios, fraudsters contact support claiming a package never arrived or a service was unsatisfactory. They use social engineering to pressure agents into issuing instant refunds or credits.</p>
<p>Without real-time intelligence on the device or the identity history, agents often grant these concessions to close the ticket. Automated systems are equally vulnerable as sophisticated bots can navigate refund flows faster than human teams can detect the pattern.</p>
<h3>Using Support for Data Collection</h3>
<p>Another growing threat is the use of support channels for data extraction. Fraudsters often contact support not to take over an account immediately but to gather the missing pieces of an identity.</p>
<p>They might claim to be a user who has forgotten their username or needs to confirm the email address on file. By engaging a helpful agent, they can validate personal details that allow them to bypass security checks elsewhere. This reconnaissance phase is difficult to detect because the individual interaction seems harmless. However, when viewed through the lens of <a href="https://www.socure.com/products/digital-intelligence">digital intelligence</a>, the high-velocity probing from a single device reveals the malicious intent.</p>
<h3>Using Data Instead of Security Questions</h3>
<p>To secure the contact center against these diverse threats, organizations must change how they validate support requests. The traditional model relies on active authentication, such as asking a customer to verify their mother’s maiden name. These answers are easily purchasable on the dark web, making the traditional questions ineffective against targeted attacks.</p>
<p>A more robust strategy focuses on passive digital intelligence. This approach validates the interaction before the agent is even involved. By analyzing invisible risk signals, organizations can determine the legitimacy of a request without adding friction to the customer experience.</p>
<p>This involves three layers of assessment:</p>
<ol>
<li><strong>First, device intelligence is critical</strong>. Security systems must determine if the device connecting to the support chat or portal is a physical phone associated with the account holder or a virtualized emulator often used in fraud farms.</li>
<li><strong>Second, network analysis provides essential context</strong>. It is vital to know if the connection is routing through a high-risk VPN or a proxy service designed to obfuscate identity.</li>
<li><strong>Third, identity correlation ties the digital footprint to the real-world human</strong>. It is not enough to know the phone number matches the account. The system must verify that the current interaction aligns with the established behavioral history of that identity.</li>
</ol>
<h3>Protecting the Agent &amp; the Brand</h3>
<p>Integrating digital intelligence into the contact center workflow does more than prevent fraud losses — it protects the operational efficiency of the support team.</p>
<p>By filtering out high-risk traffic upstream, organizations can ensure that support agents are spending their time helping legitimate customers rather than battling fraudsters. High-risk requests can be automatically deflected or routed to specialized fraud teams while trusted customers are fast-tracked to resolution.</p>
<p>This segmentation not only reduces Average Handle Time, it also prevents agent burnout and frees them from pressure to act as security guards, allowing them to focus on more complex service issues.</p>
<p>As the <a href="https://www.socure.com/use-cases/contact-center">contact center</a> continues to serve as the primary interface for customer problem resolution, it will remain a primary target for attack. Securing it requires discerning between a customer in need and a criminal in disguise instantly and accurately.</p>


Securing the Contact Center: Why Fraud is Moving to Customer Support

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Mark Bahl