Best Tools for Detecting Synthetic Identities

Summary

Synthetic identity fraud is rapidly becoming one of the most complex and persistent threats facing digital businesses today. As fraudsters blend real and fabricated data to create convincing new personas, legacy detection methods often fall short. To stay ahead, organizations are turning to advanced solutions that deliver deeper insight, adaptability, and precision across the evolving fraud landscape.

In this comparison, we provide a clear, strategic overview of the leading platforms built specifically to detect and disrupt synthetic identity fraud. Each solution is evaluated based on key features, practical use cases, and unique strengths-offering professionals an informed foundation for choosing the right technology to safeguard their operations.

1. FraudNet

Platform Summary:
FraudNet delivers an enterprise-grade ecosystem designed to unmask sophisticated synthetic identity threats. By leveraging the world’s largest anti-fraud data consortium, Fraud.net transforms risk management from a reactive measure to a proactive strategy, empowering organizations to detect hidden links, analyze behavioral patterns in real time, and make confident decisions throughout the customer lifecycle.

Key Benefits:

• Detects and prevents over 600 fraud schemes, including synthetic identity, account takeover, and chargeback abuse

• Leverages a global anti-fraud network for cross-industry intelligence sharing

• Orchestrates real-time, multi-layered identity verification across 185+ countries

• Streamlines onboarding, credit screening, and vendor vetting with automated workflows

Core Features:

• Adaptive algorithms analyze new account applications for subtle inconsistencies and links to known fraud patterns

• Access to anonymized intelligence from over one billion digital identities worldwide

• Comprehensive identity verification suite with real-time checks for device integrity, email/phone history, IP reputation, and dark web monitoring

• Unified data orchestration for seamless integration of third-party data sources and tools

Primary Use Cases:

• Secure customer onboarding for financial institutions

• Streamlined credit and loan application screening

• Automated vendor and merchant vetting

Recent Updates:
FraudNet has launched Entity Screening to centralize and automate business verification, and Policy Monitoring to proactively manage merchant compliance and contractual risks. The platform was recognized with the 2024 Datos Insights Award for its unified AML and fraud transaction monitoring solution, underscoring its leadership in financial crime prevention.

Setup Considerations:

• Collaborative integration with expert support to align with existing workflows

• Flexible data orchestration for unifying risk management stacks

• Customized rule and model implementation tailored to unique business logic and risk tolerance

2. Horizon Identity (ShadowDragon)

Platform Summary:
Horizon Identity specializes in deep identity resolution, correlating emails, phone numbers, and usernames across 550+ public sources and 15 billion breach records. The platform is designed to enrich investigations with open-source intelligence, providing crucial attribution and context for synthetic identity detection.

Core Features:

• Deep identity resolution and OSINT integration

• Exportable profiles and investigation timelines

• Dynamic profile expansion and noise filtering for faster, more accurate investigations

• Integration with Horizon Monitor and SocialNet for real-time monitoring

Primary Use Cases:

• Attribution and synthetic identity investigation

• Link analysis and network mapping for fraud rings

• Compliance and case management with exportable records

Recent Updates:
Recent improvements include seamless integration with Horizon Monitor and SocialNet for advanced link analysis, as well as enhanced dynamic profile expansion and noise filtering to accelerate and improve investigation accuracy.

Setup Considerations:

• Most effective as a complement to core transaction monitoring systems

• Requires investigator expertise in OSINT and digital investigations

• Not designed for real-time transaction monitoring

3. LexisNexis ThreatMetrix

Platform Summary:
LexisNexis ThreatMetrix aggregates intelligence from billions of global transactions and thousands of organizations, delivering real-time risk scoring and anomaly detection through its crowdsourced digital identity network. The platform is known for its advanced device analytics and explainable scoring.

Core Features:

• Crowdsourced digital identity network

• SmartID device fingerprinting and behavioral biometrics

• Explainable scoring with SHAP-based explanations

• Case management and workflow automation

Primary Use Cases:

• Real-time identity and device risk analytics

• Multi-channel fraud prevention across payments, onboarding, and account management

• End-to-end detection, investigation, and reporting

Recent Updates:
ThreatMetrix has enhanced explainability with SHAP values, expanded device fingerprinting capabilities, and introduced accelerated deployment options with no-code, self-service configuration tools.

Setup Considerations:

• Commercial pricing may be less accessible for smaller organizations

• Detection accuracy improves with broader network participation

• Customizing detection rules and policies may require specialized expertise

4. Kount

Platform Summary:
Kount provides robust, adaptive protection for e-commerce and payment environments, using dual-mode machine learning and real-time risk scoring to detect both established and emerging fraud patterns, including synthetic identities and account takeovers.

Core Features:

• Dual-mode machine learning (supervised and unsupervised)

• Real-time risk scoring analyzing hundreds of transaction signals

• Chargeback and dispute management tools

• Expanded integrations with major e-commerce platforms

Primary Use Cases:

• E-commerce and payment fraud prevention

• Account takeover and loyalty fraud detection

• Custom policy enforcement for fraud response

Recent Updates:
Kount has improved its engines for faster adaptation to new fraud tactics, expanded integrations with e-commerce platforms, and enhanced dashboards and case management tools for streamlined investigations.

Setup Considerations:

• Primarily focused on e-commerce and payment fraud

• Performance depends on regular tuning of business rules and models

• Relies mainly on internal and network data, with less emphasis on external intelligence

5. Resistant AI

Platform Summary:
Resistant AI delivers layered document and transaction forensics, applying over 500 forensic checks to financial documents and leveraging transaction monitoring to detect synthetic onboarding and document-based fraud.

Core Features:

• Document forensics for onboarding and KYC

• Transaction forensics for behavioral anomaly detection

• Persistent KYC and identity monitoring

• Integration with existing fraud monitoring systems

Primary Use Cases:

• Onboarding and synthetic identity detection

• Transaction monitoring enhancement

• Continuous KYC and compliance monitoring

Recent Updates:
Resistant AI has expanded its forensic analysis vectors, improved real-time evaluation speeds for high-volume environments, and enhanced the explainability of model outputs for analyst decision-making.

Setup Considerations:

• Most effective for organizations with significant document-based onboarding or KYC workflows

• Functions best as an overlay to existing fraud detection platforms

• Not a full replacement for core payment or account fraud monitoring tools

What Are Synthetic Identity Detection Tools?

Synthetic identity detection tools are sophisticated software solutions designed to identify and flag fraudulent identities that are not entirely real or entirely fake, but a combination of both. Fraudsters create these "synthetic" personas by piecing together fabricated information with legitimate, often stolen, data elements. These advanced tools utilize machine learning algorithms and vast data networks to analyze hundreds of data points in real time. They look for subtle inconsistencies, non-obvious correlations, and behavioral patterns that are hallmarks of a fabricated identity, providing a layer of defense that goes far beyond traditional identity verification checks. For a deeper dive into the latest synthetic identity fraud prevention strategies, explore our dedicated guide.

Why Is It Important?

Detecting synthetic identities is critically important because they represent one of the fastest-growing and most damaging types of financial crime. Unlike typical identity theft where a victim quickly notices fraudulent activity, synthetic identities can go undetected for years. Fraudsters "nurture" these accounts, patiently building a legitimate credit history before executing a bust-out scheme-maxing out credit lines and disappearing without a trace, leaving financial institutions with massive, unrecoverable losses. This type of fraud not only causes direct financial damage but also pollutes credit ecosystems, making it harder and more expensive to approve legitimate customers and manage risk effectively across the entire industry. Staying ahead of these threats requires leveraging best-in-class identity fraud protection tools that adapt to evolving tactics.

How to Choose the Best Software Provider

Choosing the right provider requires a methodology focused on data, technology, and integration. First, evaluate the provider's data network; the most effective tools are powered by a large, diverse data consortium that provides a historical and holistic view of identity elements across multiple industries. This network effect is crucial for spotting patterns that are invisible to a single organization. Second, scrutinize their analytical capabilities. Leading providers use advanced models that go beyond checking static PII and instead analyze dynamic linkages, device intelligence, and behavioral data to predict risk. Finally, assess the solution's integration capabilities. The tool must seamlessly integrate into your existing onboarding and underwriting workflows via robust APIs, delivering clear, actionable risk scores and reason codes that empower your team to make fast, accurate decisions without adding friction to the legitimate customer journey. For a comprehensive overview of top tools for detecting online payment fraud, review our curated resource.

Frequently Asked Questions

What is synthetic identity fraud and how does it differ from traditional identity theft?

Synthetic identity fraud involves the creation of new, fictitious identities by combining real and fabricated information-such as using a legitimate Social Security Number with a fake name or date of birth. Unlike traditional identity theft, which relies on stealing and using an existing person’s information, synthetic identity fraud creates entirely new personas that are harder to detect and can bypass legacy fraud controls. This makes it a growing threat for organizations that rely on digital onboarding and remote verification. For more on how organizations are fighting back against synthetic identity fraud, see our latest insights.

What features should Fraud Decision-Makers prioritize when evaluating synthetic identity detection tools?

Fraud Decision-Makers should look for tools that offer advanced machine learning capabilities, real-time data orchestration, and robust identity verification suites. Key features include the ability to analyze behavioral patterns, cross-reference multiple data sources, leverage global fraud intelligence networks, and provide explainable scoring. Integration with existing systems, automated case management, and compliance reporting are also critical for effective fraud prevention and regulatory adherence. Explore the enterprise risk management platform for a holistic approach to fraud and compliance.

How do machine learning models improve the detection of synthetic identities compared to traditional methods?

Machine learning models excel at identifying subtle inconsistencies, unusual behavioral patterns, and hidden links that traditional rule-based systems often miss. These technologies can adapt to new fraud tactics in real time, continuously learning from vast amounts of data to detect emerging threats. By leveraging crowdsourced intelligence and advanced analytics, these tools can flag suspicious activity earlier and with greater accuracy, reducing false positives and improving operational efficiency. For more on the advantages of these approaches, read about building a stronger defense with advanced fraud prevention.

Can synthetic identity detection tools be integrated with existing fraud prevention systems?

Yes, most leading synthetic identity detection platforms are designed for flexible integration with existing fraud prevention and risk management stacks. They often provide APIs, data orchestration hubs, and support for third-party data sources, enabling seamless interoperability. This allows organizations to enhance their current workflows, unify decision-making processes, and maximize the value of their existing technology investments without significant disruption. Learn more about data hub integration for streamlined fraud operations.

What are the main challenges organizations face when implementing synthetic identity detection solutions?

Common challenges include ensuring data quality and coverage, aligning new tools with existing workflows, and managing the complexity of integrating multiple data sources. Additionally, organizations may need to invest in staff training to interpret insights and customize detection rules. Balancing detection accuracy with customer experience and maintaining regulatory compliance are also ongoing concerns. Choosing a solution with strong support, flexible configuration, and proven industry expertise can help mitigate these challenges. For a look at top fraud prevention trends shaping the financial sector, visit our resource center.

Disclaimer: This article is based exclusively on publicly available information. The tools referenced have not been independently tested by us. Should you identify any inaccuracies or wish to provide recommendations, we invite you to contact us.