Fraud is no longer just a financial nuisance, in 2026 it’s a global security crisis. The Financial Action Task Force (FATF) warns that no region is immune, with fraud rising across every continent. In 2024, UK Finance recorded 3.31 million cases in the United Kingdom, totaling £1.6 billion in losses, while the Federal Deposit Insurance Corporation (FDIC) reported a 25% increase in fraud-related losses in the US.
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Key Features of Fraud Detection Software
Fraud detection software brings several technologies together into one system. When comparing vendors, these are the features that most affect detection accuracy, efficiency and compliance coverage:
- Real-time risk monitoring: Analyzing device, email, phone and IP signals as events happen, rather than in batch reviews, lets teams catch fraud before a transaction completes. Look for coverage of non-transaction events such as logins and profile changes, plus screening against sanctions and watchlists.
- Explainable AI: Machine learning surfaces patterns that static rules miss, but the model should explain why each alert fired. Explainability lets analysts trust and defend decisions, and it matters for regulatory audits.
- Configurable rules and thresholds: A flexible rules engine lets teams apply different thresholds by customer tier or risk profile and adjust as fraud tactics change. The ability to tune rules independently reduces reliance on the vendor.
- Combined fraud and AML coverage: Handling fraud detection and anti-money laundering in a single platform removes data silos between teams and reduces the cost of running separate tools. It also gives investigators one view of risk across both use cases.
- Fast integration: Deployment time is exposure time, so how quickly a solution connects to existing systems affects how soon it starts preventing loss. Check for a documented API and support during onboarding.
Top Fraud Detection Software Companies
Disclaimer: This article is based on publicly available information and was last updated in 18h August 2026. We haven’t tested each tool directly. For corrections or updates, please contact us.
SEON
SEON is a fraud prevention platform that began by addressing fraud in the crypto space and now serves companies including Afterpay, Revolut, Wise, Bilt and Branch. It combines fraud prevention, AML compliance and identity verification in one system, built on a unified data foundation spanning digital footprint analysis, device intelligence, behavioral biometrics and AI agent detection.
The platform connects 900+ first-party data signals to enrich and score risk in real time across the customer lifecycle, from pre-onboarding through payments, transaction monitoring and regulatory reporting. SEON supports both rules-based and AI-driven analysis with transparent decisioning, letting teams build granular rules and fine-tune thresholds. The company reports more than $300 billion in fraud prevented and holds over 300 reviews on G2, Capterra and the AWS Marketplace.
Key capabilities include real-time digital footprint and device intelligence, combined fraud and AML coverage, transparent AI-driven rules, and single-API integration.
Read More About SEON’s Reviews on G2
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Feedzai
Feedzai is a fraud detection solution targeting banks and PSPs, combining AI-based risk assessment, behavioral analytics, and explainable decisioning. In 2025 the company acquired Demyst to expand its access to external data for fraud detection and customer onboarding. Its RiskOps product integrates identity, credit, and behavioral signals into a unified fraud and AML offering.
Key capabilities include contextual intelligence across identity, credit, and behavior, combined fraud and AML coverage, and scalable deployment for financial institutions.
TruValidate
After acquiring Iovation, is TransUnion’s fraud prevention offering, formed after the 2018 acquisition and rebranding of iovation. It combines device recognition, identity verification, and transaction analysis to provide multi-layered fraud detection, linking device identifiers, proprietary data, and online behavior to assess risk.
Key capabilities include device intelligence, identity and transaction analysis, and integrations across finance, insurance, and tenant screening.
ThreatMetrix
ThreatMetrix, part of LexisNexis Risk Solutions, focuses on user identity verification through behavioral analytics and a shared intelligence network drawing on over 78 billion data points. It is geared toward larger organizations with existing technical infrastructure and integrates with other LexisNexis tools, which suits enterprises already invested in that ecosystem.
Key capabilities include near real-time verification, customizable risk rules, scalable fraud prevention, and global identity intelligence across the digital customer journey.
Sift
Sift offers fraud prevention tools targeting retail, food and beverage, travel, and ticketing industries. Its Digital Trust & Safety Suite covers the customer journey through real-time decisioning and dynamic friction capabilities, applying stricter checks only when a transaction looks risky.
Key capabilities include AI-driven fraud prevention, scalable deployment, and dispute management across digital channels.
Emailage
Acquired by LexisNexis in 2020, Emailage is a fraud prevention solution using email intelligence for real-time risk assessment. It combines LexisNexis’ Digital Identity Network with proprietary email data to support fraud scoring across use cases including account opening, card-not-present transactions, guest checkouts, and account management, making email the primary risk signal.
Key capabilities include predictive risk scoring, ML models, and integration with the LexisNexis Digital Identity Network.
Quantexa
Quantexa is a fraud detection and decision intelligence company that connects internal and external data to build entity relationship views for identifying hidden risk. Its contextual approach supports fraud detection across banking, insurance, and government sectors.
Key capabilities include network analytics, AI-driven entity resolution, and flexible rules engine. The approach is aimed at reducing false positives and accelerating fraud investigations.
Kount
Acquired by Equifax in 2021, Kount is a fraud prevention solution combining AI-based decisioning with device fingerprinting, IP tracking, transaction scoring, and real-time analytics. It draws on Equifax identity data to inform its risk decisions.
The product suite includes Kount 360 for payment risk, Command for card-not-present fraud, Central for workflow management, and Control for account takeover protection, alongside chargeback management tools.
Key capabilities include AI-driven fraud detection, device fingerprinting, IP tracking, transaction scoring, chargeback management, and ecommerce integrations.
How to Choose a Fraud Detection Software
Choosing the right software is a strategic decision. It should meet your needs now, scale with growth, and integrate smoothly with your operations.
Here are key factors to consider for effective risk management:
- Detection features: It’s crucial to ensure the software provides the necessary features to combat specific types of fraud, such as identity theft, payment fraud, or unauthorized account access. Tailor your choice to address your most pressing fraud concerns.
- Integration flexibility: Although many fraud detection systems are offered as Software as a Service (SaaS), depending on your company’s infrastructure and security requirements, on-premise integration might be necessary.
- Payment model: Avoid lengthy contracts that may not be cost-effective in the long run. Opt for a solution that offers a trial period or a short-term payment option to evaluate the software’s effectiveness before making a long-term commitment.
- Support and documentation: Confirm that the vendor provides comprehensive customer support and free assistance, particularly during the software integration phase. The availability of clear, detailed documentation is essential, allowing you to resolve issues independently without constant reliance on customer support.
Balancing these factors against your own fraud risks and infrastructure helps you choose a solution that fits your needs rather than the broadest feature set.
Still deciding whether to build or buy your fraud solution? This guide compares costs, scalability and long-term ROI to help you choose with confidence.
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Frequently Asked Questions
What is fraud detection software?
Fraud detection software is designed to automatically stop online fraud. The software analyses online user actions and, based on your risk rules, blocks those that are deemed high risk.
A high-risk user action can be a payment, signup, or login, among others. The fraud detection software must be setup to analyse user or payment data, analyse that data via risk rules, and decide if it is risky or not.
What features should I look for in fraud detection software?
To choose the right fraud detection software, start by assessing your company’s fraud risks, existing security tools, and risk tolerance. Key features to look for include customizable risk rules, device fingerprinting, alternative data scoring, real-time analysis, and machine learning for automation.
Why is fraud detection and prevention software required?
Today, all businesses are at risk from fraud, no matter their sector. In fact, the current fraud landscape demonstrates that those companies and decision-makers who think they couldn’t be affected are more likely to be targeted – exactly because they are less likely to invest in their defenses.
Should I build or buy fraud detection software?
The decision to build or buy fraud detection software depends on your company’s resources, priorities, and long-term strategy. Building a solution offers full control but requires significant investment, technical expertise, and ongoing maintenance. Buying an end-to-end platform provides faster deployment, scalability, and access to regularly updated fraud models—often at a lower long-term cost.
