Why Identity & Fraud Teams Must Unite

Identity and fraud are two sides of the same coin, and emerging technologies have made it impossible (and risky) to separate the two. Leveraging stolen credentials, synthetic identities, and artificial intelligence (AI), fraudsters are exploiting vulnerabilities across organizations with siloed identity and access management (IAM) and fraud functions. Account takeover (ATO) fraud surged by 354% in 2023 alone, underscoring the need for a unified approach. Addressing today’s threat environment requires identity and fraud teams to share insights and adopt integrated strategies that proactively stop fraud before it occurs. Collaboration is not just a technological necessity but a strategic imperative to protect organizations and their customers from increasingly sophisticated attacks.

The evolution of cyber crime has blurred the lines between identity theft and fraud. Traditional fraud detection systems, which focus on transactional patterns, often fail to account for sophisticated identity-based attacks. 

How ATO Fraud Works

Bad actors use compromised credentials or session hijacking to exploit legitimate accounts. This type of fraud not only results in financial losses but also exposes sensitive personal information. Advanced techniques, such as man-in-the-middle (MiTM) attacks, can bypass even robust security measures.

How NAF Works

Fraudsters use stolen or synthetic identities to create fraudulent accounts, bypassing transactional fraud detection. Losses from new account fraud (NAF) totaled $3.2 billion in 2022. They often exploit weak identity verification processes, leveraging AI to create synthetic identities that pass simple checks.

How Automated Threats Work

Bots enable bad actors to scale their attacks, creating fake accounts or testing stolen credentials en masse. These automated systems are becoming increasingly adept at mimicking human behavior, making detection more challenging.

These threats thrive in environments where IAM and fraud teams operate independently. Fraud prevention historically begins at the transaction, while identity teams focus on upstream processes like registration and login. The gaps in coverage leave organizations vulnerable to attacks that exploit these blind spots.

Fraud teams typically concentrate on stopping suspicious transactions. However, many fraud scenarios can be thwarted earlier in the user journey through identity-based controls. For instance:

Identity Proofing

Implementing document verification and liveness detection at registration can block bots and bad actors from entering the system. Enhanced proofing methods, such as using AI to detect deepfakes, add another layer of security.

Behavioral Biometrics

These tools identify anomalies, such as erratic mouse movements or inconsistent typing speeds, to flag suspicious activity. Behavioral insights can also help predict potential fraud patterns before they manifest.

Liveness Detection

This method ensures the person attempting to create an account is a live individual, not a deepfake or photo. With advanced algorithms, liveness detection can differentiate between real users and sophisticated impersonation attempts.

Consider This: A bot-driven attack could have been stopped during account creation if identity verification tools flagged fake credentials or detected automated behavior. By integrating identity signals, fraud teams gain critical context to act sooner, reducing downstream risks.

While identity teams secure customer registration and manage access, they often lack visibility into downstream activities like fraudulent transactions. Collaboration with fraud teams can enhance security and customer experience in several ways:

Fraud Detection Signals

Incorporating bot detection and stolen credential monitoring into identity workflows helps detect threats early. Shared data can identify repeat offenders and emerging attack patterns.

Adaptive Security

Identity systems can leverage fraud indicators (e.g., anomalous login patterns) to trigger step-up authentication or terminate risky sessions. By integrating fraud detection capabilities, identity teams can better protect users throughout their journey.

Consider This: A fraud detection system might identify a suspicious login attempt from an unrecognized device. Identity workflows can respond dynamically, requiring step-up authentication to verify the user’s legitimacy, thereby preventing ATO fraud before it escalates. This proactive approach minimizes risks while maintaining trust.

Organizations often struggle with fragmented fraud prevention due to siloed identity and fraud teams. This lack of collaboration leads to:

Exploitable Vulnerabilities

Disjointed systems create blind spots, allowing bad actors to slip through the cracks. Fraudsters exploit these gaps, targeting weak points in the user journey.

Operational Inefficiencies

Redundant tools and manual processes result in wasted resources and inconsistent user experiences. Streamlined operations enable faster response times and better resource allocation.

Customer Friction

Overlapping security checks frustrate legitimate users, leading to higher abandonment rates. By aligning efforts, teams can minimize unnecessary friction while maintaining robust security measures.

Collaboration and shared capabilities, like device trust, behavioral biometrics, and orchestration, can help address these challenges. For example, integrating identity verification with fraud detection tools enables seamless, low-friction customer journeys while enhancing security. 

Breaking down silos between IAM and fraud teams requires actionable steps:

1. Create Cross-Functional Teams: Establish shared goals and KPIs that align both teams around reducing fraud and improving the customer experience. Cross-functional collaboration fosters innovation and ensures alignment across departments.

2. Invest in Unified Platforms: Use orchestration tools to integrate identity verification, fraud detection, and risk-based authentication. Centralized systems reduce complexity and enable real-time decision-making.

3. Adopt Shared Metrics: Focus on measurable outcomes, such as reduced fraud losses, enhanced user satisfaction, and faster resolution times. Unified dashboards can provide transparency and track progress.

4. Enhance Communication: Schedule regular reviews of fraud and identity risks to ensure alignment and information sharing. Collaborative workshops and shared training programs can build trust and improve teamwork.

5. Leverage Advanced Technologies: Tools like liveness detection, adaptive MFA, and AI-driven risk scoring can provide real-time insights across the user journey. Advanced analytics can uncover hidden threats and streamline mitigation strategies.

The convergence of identity and fraud capabilities is no longer optional. By uniting these teams, organizations can:

Enhance Security

Strengthen defenses and prevent fraudsters from exploiting gaps in the user journey by utilizing advanced detection tools and unified policies.

Streamline the Customer Experience

Apply friction only when necessary, ensuring legitimate users have seamless access, and implement tailored security measures to enhance trust and satisfaction.

Achieve Operational Efficiency

Reduce redundancy and maximize the value of shared tools, freeing up resources for strategic initiatives.

Fraud doesn’t begin at the transaction. It starts with a compromised identity. Addressing the root cause requires a unified approach that spans the entire customer journey. By integrating IAM and fraud operations, organizations can not only combat modern threats, but also build trust and loyalty with their customers. An integrated strategy will be crucial in staying ahead of increasingly sophisticated fraud strategies and technologies.