Best Fraud Detection Software for E-Commerce Businesses

Summary

Choosing the right B2B fraud detection software is critical for e-commerce businesses aiming to safeguard revenue, streamline operations, and uphold customer trust. Today’s advanced platforms deliver risk scoring, seamless integrations, and adaptive analytics to address the ever-evolving tactics of fraudsters. As digital commerce grows more complex, selecting a solution that aligns with your business’s unique transaction flows and compliance needs becomes more important than ever.

In this guide, we offer a strategic, data-driven comparison of leading fraud detection, risk, and compliance tools. Our goal is to equip you with clear, actionable insights so you can confidently identify the best fit for your e-commerce business-balancing innovation, efficiency, and robust security.

1. FraudNet

Platform Summary:
FraudNet is a comprehensive fraud detection and risk management platform purpose-built for the demands of B2B e-commerce. It empowers enterprises to proactively defend against sophisticated fraud threats, reduce chargebacks, and maximize revenue-all while maintaining a seamless customer experience. FraudNet’s modular, end-to-end solutions are designed to protect every stage of the transaction lifecycle, from onboarding to payment, across all channels.

Key Benefits:

• Instantly identifies and blocks sophisticated fraud patterns using adaptive risk scoring and collective intelligence.
• Reduces false positives, enabling more legitimate high-value orders to be approved and boosting revenue.
• Automates compliance (KYC/AML) and risk workflows, reducing manual review and audit burden.
• Provides unified protection for omni-channel and marketplace operations, consolidating risk management across the business.

Core Features:

• Machine learning for real-time risk scoring and anomaly detection.
• Global Anti-Fraud Network for proactive, collective threat intelligence.
• Intelligent, no-code rule engine for rapid adaptation to new fraud tactics.
• Modular tools for Entity Screening, Entity Monitoring, and Transaction Monitoring.

Primary Use Cases:

• Maximizing revenue by reducing false declines on high-value B2B orders.
• Preventing account takeover and securing customer trust through continuous behavioral monitoring.
• Protecting omni-channel and B2B marketplace operations with unified, real-time risk management.

Recent Updates:
FraudNet has recently enhanced its platform with dynamic risk orchestration, advanced explainability in risk scoring, and expanded support for multi-currency and multi-entity operations. The latest release integrates cognitive computing, deep learning, and streaming analytics to deliver enterprise-scale, real-time fraud detection.

Setup Considerations:

• Collaborative integration ensures the solution is tailored to your unique risk environment and business goals.
• Strategic data orchestration is key-identify all relevant data sources early for a unified risk view.
• Modular, phased rollout allows you to prioritize the most critical protections and scale as needed.
• Custom model development is available for unique fraud challenges, leveraging in-house data science expertise.

2. Sift

Platform Summary:
Sift is a fraud detection platform focused on delivering accurate risk scoring and behavioral analytics for e-commerce businesses. Its user-friendly interface and rapid deployment make it accessible for teams with varying technical backgrounds, while its adaptive models scale with business growth.

Core Features:

• Behavioral analytics and real-time risk scoring
• Comprehensive API and workflow integration
• Intuitive, user-friendly setup

Primary Use Cases:

• Real-time fraud detection at checkout to reduce chargebacks
• Automated risk scoring for account creation and login events
• Scalable fraud management for growing e-commerce operations

Recent Updates:
Sift has introduced an enhanced user timeline view for faster investigations, improved alerting features, and expanded support for large dataset processing.

Setup Considerations:

• May require manual review for flagged legitimate customers
• Transparency in risk scoring may be limited for some users
• Performance can slow with very large datasets

3. Mastercard Identity Review 360

Platform Summary:
Mastercard Identity Review 360 provides layered, real-time identity verification for e-commerce and financial services. Its investigator-friendly interface and deep network intelligence make it especially valuable for regulated industries and high-risk payment flows.

Core Features:

• Real-time identity checks using phone, email, IP, and address data
• Investigator-friendly interface for rapid manual review
• Deep network and device intelligence
• KYC/AML data enrichment and reporting

Primary Use Cases:

• Payment verification for financial institutions
• Accelerating manual review for flagged transactions
• Supporting regulatory compliance in high-risk sectors

Recent Updates:
The platform now features expanded integration with Mastercard’s global identity network, improved redundancy in data signals, and enhanced support for manual review workflows.

Setup Considerations:

• Redundant data points can complicate risk analysis
• International coverage is strongest in core markets
• Some queries may yield no results for uncommon identifiers

4. Signifyd

Platform Summary:
Signifyd is a fraud protection platform offering automated decisioning and guaranteed chargeback protection for online retailers. Its seamless integrations and financial liability coverage make it a strong choice for merchants seeking both automation and risk transfer.

Core Features:

• Automated fraud decisioning
• Guaranteed chargeback protection
• Seamless integration with major e-commerce platforms
• Real-time alerting and dispute management

Primary Use Cases:

• High-volume order processing with minimal manual intervention
• Outsourcing chargeback management and dispute resolution
• Device and behavior-based risk analysis for improved acceptance rates

Recent Updates:
Signifyd has improved dashboard consistency across devices, enhanced real-time alerting, and expanded support for payment dispute workflows.

Setup Considerations:

• Occasional false positives may require manual review
• Pricing may not suit low-margin businesses
• Minor inconsistencies between mobile and desktop interfaces

5. ClearSale

Platform Summary:
ClearSale combines automation with expert human review to deliver balanced fraud detection for global retailers. Its hybrid model reduces false declines and provides chargeback reimbursement, making it ideal for businesses seeking both accuracy and customer experience.

Core Features:

• Hybrid automation and analyst review
• Chargeback reimbursement on approved orders
• Easy integration with major e-commerce platforms
• Manual analyst intervention for complex cases

Primary Use Cases:

• Global fraud prevention for international retailers
• Reducing false declines during peak sales periods
• Improving operational efficiency for mid-sized businesses

Recent Updates:
ClearSale has streamlined onboarding resources, improved analyst review workflows, and updated customer support processes for faster response times.

Setup Considerations:

• Manual review can slow order approvals during peak periods
• Frequent interface changes may disrupt workflows
• Customer support response times may vary

6. NoFraud

Platform Summary:
NoFraud offers fast, automated fraud screening for small and mid-sized e-commerce businesses. Its real-time order screening and low-maintenance setup make it accessible for teams without dedicated fraud specialists.

Core Features:

• Real-time order screening
• Customizable blocklists and allowlists
• Seamless onboarding and integration
• Automated, low-maintenance fraud prevention

Primary Use Cases:

• Automated fraud prevention for lean teams
• Handling high transaction volumes during sales events
• Flexible approval for small online stores

Recent Updates:
NoFraud has enhanced its real-time monitoring engine, improved onboarding resources, and expanded reporting capabilities for order status and risk insights.

Setup Considerations:

• Occasional false flags may require manual intervention
• Manual verification can slow orders during peak periods
• Limited proactive human review for high-value transactions

7. SEON

Platform Summary:
SEON delivers modular, API-first fraud prevention with deep digital footprinting and a highly customizable rules engine. Its flexibility and data-rich approach make it ideal for businesses seeking tailored fraud strategies and granular control.

Core Features:

• Modular APIs for data enrichment and risk scoring
• Deep digital footprinting from minimal user attributes
• Customizable rules engine for adaptive fraud strategies
• Dynamic risk orchestration for real-time and post-transaction analysis

Primary Use Cases:

• Flexible fraud detection for high-risk transaction flows
• KYC and ongoing transaction monitoring for compliance-heavy industries
• Integration with diverse tech stacks and business systems

Recent Updates:
SEON has launched dynamic risk orchestration, expanded onboarding support, and introduced best-practice templates for faster rule customization.

Setup Considerations:

• Initial setup and customization may require time due to data volume
• Occasional false positives may need manual review
• Advanced features may benefit from additional documentation and onboarding resources

For additional strategies and best practices, explore our guide to top fintech fraud prevention tools and our overview of anti-fraud solutions in fintech.

What is B2B fraud detection software for e-commerce?

B2B fraud detection software for e-commerce is a specialized system designed to protect businesses that sell goods or services to other companies online. Unlike B2C solutions that focus on individual consumer transactions, B2B fraud software analyzes the unique complexities of business-to-business commerce. This includes verifying business identities, securing corporate accounts against takeover, and scrutinizing high-value, large-volume orders. It leverages sophisticated technology to differentiate legitimate corporate purchasing patterns-such as bulk orders, shipping to commercial addresses, and payments via credit lines or purchase orders-from fraudulent activities orchestrated by sophisticated criminals targeting the larger payloads of B2B transactions.

Why is it important?

The importance of robust B2B fraud detection cannot be overstated, as the financial and reputational stakes are significantly higher than in the B2C space. A single fraudulent B2B transaction can result in losses of tens or even hundreds of thousands of dollars due to higher average order values. Beyond the immediate financial impact, falling victim to fraud can irrevocably damage your company's reputation and erode trust with legitimate business partners. Furthermore, conventional fraud tools are often ill-equipped to handle B2B signals, leading to high false positives that block good customers or, worse, high false negatives that allow massive fraud events to slip through, causing significant operational and logistical chaos.

How to choose the best software provider

Choosing the right provider requires a methodology focused on B2B-specific capabilities. First, evaluate the provider's core logic: can their models distinguish between a legitimate, large corporate purchase and a fraudulent one? The solution must be built for B2B, not just adapted from a B2C model. Second, assess its integration capabilities and scalability. The software must integrate seamlessly with your e-commerce platform and be able to scale with your transaction volume. Finally, look for a true partnership that offers customization and control. The best providers allow you to tailor rules to your specific risk tolerance and provide expert support, acting as an extension of your team to continuously refine your fraud prevention strategy in the face of evolving threats.

Frequently Asked Questions

What features should B2B e-commerce businesses prioritize when selecting fraud detection software?

B2B e-commerce businesses should prioritize fraud detection solutions that offer adaptive machine learning for real-time risk scoring, seamless integration with existing platforms, automated compliance (such as KYC/AML), and robust data orchestration. Features like customizable rules engines, comprehensive reporting, and support for complex transaction flows are also essential. Additionally, consider the vendor’s ability to scale with your business, provide unified protection across channels, and offer dedicated support for onboarding and ongoing optimization.

How does modern fraud detection differ from traditional rule-based systems?

Modern fraud detection systems use advanced algorithms to analyze vast amounts of data and identify complex, evolving fraud patterns in real time. Unlike traditional rule-based systems, which rely on static, predefined rules that can quickly become outdated, these models continuously learn from new data and adapt to emerging threats. This reduces false positives, improves detection accuracy, and enables businesses to respond proactively to sophisticated fraud tactics.

Can these fraud detection platforms help with regulatory compliance such as KYC and AML?

Yes, many leading B2B fraud detection platforms-such as FraudNet, Mastercard Identity 360, and SEON-offer automated compliance features, including Know Your Customer (KYC) and Anti-Money Laundering (AML) workflows. These tools streamline customer verification, monitor transactions for suspicious activity, and generate audit-ready reports, helping businesses meet regulatory requirements efficiently and reduce the risk of non-compliance penalties.

How do these solutions minimize false positives while maintaining strong fraud prevention?

Modern fraud detection solutions leverage adaptive analytics, behavioral analysis, and collective intelligence to distinguish between legitimate and fraudulent activities more accurately. By analyzing a wide range of signals-such as transaction history, user behavior, device data, and global threat intelligence-they reduce the likelihood of false declines (legitimate transactions flagged as fraud). Some platforms also combine automated decisioning with expert human review for complex cases, further balancing security and customer experience.

What integration and setup considerations should B2B enterprises keep in mind?

Successful implementation of fraud detection software requires careful planning around integration with existing e-commerce platforms, payment gateways, and data sources. Enterprises should assess the vendor’s API capabilities, support for custom workflows, and the availability of modular deployment options. It’s important to identify all relevant data sources early, involve key stakeholders, and consider a phased rollout to prioritize critical protections. Ongoing support, training, and access to customization or data science expertise can also enhance long-term value.

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.