As fraud tactics grow more sophisticated, enterprises need robust defenses to safeguard their financial assets, brand reputation and customer trust. According to the U.S. Federal Trade Commission, consumers reported over $12.5 billion in fraud losses in 2024, marking a record high and a 25% year-over-year increase.
In this landscape, choosing the right fraud management system is essential. This guide explores ten of the most capable enterprise fraud management systems and how to select the one best suited to your business needs.
What Is a Fraud Management System?
A fraud management system (FMS) is a comprehensive set of tools, technologies and processes designed to detect, prevent and mitigate fraudulent activities within an organization. These systems are typically used by businesses across various industries, especially those that deal with financial transactions, such as banks, ecommerce platforms, fintech companies and online service providers.
Key Features of a Fraud Management System
Components of a fraud management system deliver powerful tools to detect, prevent and respond to fraudulent activities in real time. These capabilities help businesses safeguard operations, protect customer data and maintain compliance while reducing financial risk. Key features include:
- Team management: Supports multiple logins with varied permissions for seamless team collaboration.
- Unified dashboard: Centralized interface for managing and sharing fraud prevention strategies across departments.
- Integration flexibility: Easily integrates with current systems and future tools, with solid API compatibility.
- Digital Footprint Analysis: Leverages digital and social signals to quickly validate user information, improving onboarding without compromising security.
- Dynamic Friction: Applies friction based on risk scores to streamline user experiences while screening for fraud.
- Customization: Offers flexible rule-setting and data handling to address specific fraud risks and adapt to new threats.
- Machine Learning: Automates rule adjustments and suggests new strategies for real-time fraud detection.
The 10 Best Fraud Management Systems
Disclaimer: This article is based on online research and user reviews. We did not manually test each tool. Last updated in Q2 2025. Contact us for updates or corrections.
There are a range of solutions available with varying expertise and focuses to factor in when making a decision, along with other important variables such as integration, costs, and time. See below some other products on the market today.
SEON – Unique Digital Footprinting and Custom Rules
SEON delivers a unified command center for fraud prevention and AML compliance powered by first-party, real-time data. By enriching email, phone, IP and device details with 900+ digital and behavioral signals, it helps businesses detect risks early, often before KYC, enabling smoother onboarding while keeping bad actors out.
Its modular platform supports industries such as fintech, iGaming, payments and eCommerce, covering the full customer journey from signup to transaction monitoring. SEON helps block fraudulent accounts, prevent payment fraud, reduce chargebacks and combat promo abuse while also streamlining AML screening and compliance workflows.
With customizable risk rules and explainable AI, fraud and AML teams can adapt strategies in real time and understand exactly which signals drive decisions. Trusted by global leaders, SEON combines transparency, flexibility and scalability, offering accessible solutions for businesses at every stage of growth.
SEON connects 900+ first-party data signals to show you what other solutions can’t. Enrich data, understand context and take action from one place.
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Ekata
Ekata, now part of Mastercard, provides identity verification and fraud prevention tools designed to reduce risk without adding customer friction. Known for its strong graph analysis and network visualization capabilities, Ekata helps businesses streamline manual reviews and detect fraud during onboarding and account creation. It supports global brands like AliPay, Microsoft, Stripe, and Airbnb.
Backed by Mastercard’s Identity Network, Ekata combines behavioral, device, and global fraud data to assess risk from the first customer interaction. Its solutions help businesses approve legitimate users faster, reduce fake account creation, and combat transaction fraud, all while improving customer experience and increasing approval rates.
Fraud.net
Fraud.net offers an AI-native fraud, risk, and compliance platform designed to help enterprises detect and prevent fraud in real time. Built for precision and scalability, it unifies fraud detection, transaction monitoring, and entity risk management within a single, adaptive system.
The platform combines machine learning, network intelligence, and advanced analytics to deliver accurate, real-time insights into emerging risks. By centralizing detection, investigation, and reporting, Fraud.net helps organizations strengthen their risk posture, reduce operational complexity, and maintain compliance across industries.
Signifyd
Signifyd provides an end-to-end fraud prevention platform with a 100% chargeback protection model in place to increase automation and remove fraud liability for the merchant. They also offer integrations available across Salesforce, Shopify, and Magento.
The chargeback guarantee model can be a double-edged sword. On one hand, you can be sure you’ll never have to pay for more chargeback admin fees, which can be costly and time-consuming to manage. However, certain fraud managers prefer having more control over false positives to manage chargebacks based on their risk appetite.
TruValidate
Initially making a name for itself as Iovation, TruValidate is a device-based fraud prevention and multi-factor consumer authentication solution acquired by TransUnion in 2018. The company has a database with over 10 billion unique devices and 117 million recorded instances of fraud and abuse.
Offers device-based fraud detection with a massive database of unique devices. Initially popular in iGaming, it remains a strong choice for industries needing device-based security.
Sift
A former Y Combinator accelerator beneficiary, Sift offers a complete Digital Trust & Safety suite utilizing blackbox machine learning to streamline operations to remove the pressure on human resources. The firm’s main industries are fintech, retail, food, and beverage.
Delivers a robust fraud prevention platform with blackbox machine learning that automates operations, which is especially suited for fintech and retail. It’s known for resolving chargebacks and addressing cybersecurity concerns.
Feedzai
Feedzai offers modular solutions aimed at retail banks and financial institutions. Its real-time transaction scanning detects fraud, and its AML compliance support makes it a strong choice for fintech.
Feedzai is a data science company focused on making banking and commerce safer by combining fraud prevention and AML into one platform. Founded by data scientists and aerospace engineers, it’s been recognized by Aite and Forbes as a top AI company. Leading banks, processors, and retailers use Feedzai to protect trillions in transactions while improving customer experience.
FraudHunt
Founded in 2013, FraudHunt is an anti-fraud platform that helps online businesses detect bots, fake accounts, and high-risk users. It uses advanced device fingerprinting, real-time scoring, and machine learning to analyze user behavior and identify threats across all devices. The system detects tactics like VPNs, proxies, emulators, and other masking techniques to uncover hidden risks.
FraudHunt assigns a unique device ID to each user and offers flexible integration via API or Google Analytics, enabling businesses to act instantly on risk signals. With continuous data analysis and pattern recognition, it protects against fraud in real time while minimizing friction for legitimate users.
SumSub
Launched as an identity verification solution in 2015, SumSub has grown into a KYC and IDV juggernaut. It also helps that the company offers compliance tools for KYC, AML – and even KYB, or Know Your Business.
Excels in identity verification, KYC, and AML compliance, offering video verification and case management tools to meet strict regulatory requirements.
SAS
SAS, which stands for Statistical Analysis System, is a legacy fraud prevention software that has been going since 1984. It offers a wide range of data analytics products, which have been adopted by a number of traditional financial institutions to manage risk and reduce fraud.
There is a handful of SAS products worth noting for fraud management, namely SAS Continous Monitoring for Procurement Integrity, SAS Detection and Investigation, and SAS Identity 360.
Choosing a Fraud Management System
When selecting a fraud management system, businesses should assess their unique needs, industry demands, and risks. Each platform has strengths, such as identity verification, real-time detection, or chargeback prevention. To ensure alignment with operational goals and adequate protection against evolving threats, consider the following:
- Analyze Business Requirements: Identify the types of fraud, channels, and products that need protection. Consider current and future transaction volumes and regulatory requirements. Documenting these factors ensures you choose a solution tailored to your needs, rather than a one-size-fits-all option.
- Evaluate Key Features: Prioritize key features like real-time detection, advanced analytics, machine learning, customizable rules, risk scoring, and case management. A user-friendly interface for analysts is also crucial for system effectiveness.
- Assess Scalability and Performance: It is vital that the chosen system can handle your current and projected transaction volumes. Scalability is key, as the system should be able to grow alongside your business. Additionally, ensure that the system can process data in real time to enable rapid fraud detection, which is essential for minimizing potential losses.
- Review Integration and Compatibility: Verify that the fraud management system can integrate smoothly with your existing technology stack. Look for solutions that support API integrations and SDKs for easier implementation. Compatibility with your current databases and data formats is also critical to ensure a seamless transition and operation.
- Consider Adaptability and Machine Learning: A robust fraud management system should leverage advanced machine learning to adapt to new and evolving fraud patterns over time. This capability allows the system to provide automated rule suggestions and optimizations, ultimately enhancing its effectiveness.
- Evaluate Vendor Expertise and Support: Request case studies and client testimonials to gauge vendor expertise. Ask about their fraud detection experience, trend awareness, implementation timelines, and ongoing support for smooth operation.
- Conduct Demos and Trials: Request product demos from shortlisted vendors and, if possible, conduct a trial to test the system in your environment. This hands-on approach helps ensure the solution meets your needs and protects against evolving fraud threats.
Get access to SEON’s flexible fraud tools and a dedicated team ready to help your business scale with confidence.
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Frequently Asked Questions
Any company trying to reduce fraud rates such as chargeback fees, account takeover, or fake identities can use a fraud management system. There are many ways to deploy these tools, and their features and pricing vary greatly from one provider to the next.
Fraud management systems automatically allow or block certain user actions. They calculate how risky a signup, login, or transaction is based on preset rules. Some fraud management systems also focus on providing risk management teams with more data to make better decisions.
Managing fraud risks efficiently means that less fraud goes through. A reduction in fraud means an increase in revenue and much more, from happier staff to a smoother customer experience.
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Learn more about:
Browser Fingerprinting | Device Fingerprinting | Fraud Detection API | Digital Footprint
Sources
- Fortune Business Insight: Global fraud detection and prevention market value
- Neil Patel: Customer Onboarding: Your Secret Sauce to Reducing SaaS Churn
- The Verge: Forty percent of ‘AI startups’ in Europe don’t actually use AI, claims report
- Juniper Research: Online Payment Fraud Losses to Exceed $343 Billion Globally Over the Next 5 Years
