Fraud can affect almost every stage of a digital customer journey. It may appear during account registration, login, checkout, payments, withdrawals, or even after a transaction has been completed. For businesses operating online, relying only on basic payment checks is often not enough.
That is where fraud prevention software comes in. These platforms combine signals such as device information, IP reputation, payment data, behavioral activity, identity information, and transaction patterns to help businesses assess risk and decide what action to take.
The right solution depends on the type of fraud a company faces, its technical setup, regulatory requirements, transaction volume, and the amount of control its fraud team needs.
Below are seven fraud prevention platforms worth considering in 2026, with SEON examined in detail first.
What Is Fraud Prevention Software?
Fraud prevention software helps businesses identify suspicious activity and make risk-based decisions before or during potentially fraudulent events.
Depending on the platform, capabilities can include:
- Device and browser intelligence
- IP, VPN, proxy, and geolocation analysis
- Phone and email intelligence
- Payment and card information analysis
- Risk scoring
- Custom rules and decisioning
- Account takeover protection
- Transaction monitoring
- AML and sanctions screening
- Case management
- Manual investigation workflows
- API-based fraud checks
Rather than automatically treating every unusual transaction as fraud, modern systems can assign risk signals or scores and let businesses decide whether to approve, reject, challenge, or manually review an activity.
What Should Businesses Look for in Fraud Prevention Software?
Before choosing a platform, consider the following factors.
1. Data and intelligence
A useful platform should provide enough information to understand why an event may be risky. Depending on the business, this could include IP, phone, BIN, device, behavioral, identity, and transaction signals.
2. Rules and decisioning
Fraud patterns differ from one company to another. Custom rules allow risk teams to build decisions around their own policies instead of relying entirely on fixed models.
3. API flexibility
For businesses with custom applications, an API-first architecture can make it easier to incorporate fraud checks into registration, login, payment, withdrawal, and other workflows.
4. Investigation tools
Detection is only one part of fraud management. Analysts may also need tools for reviewing alerts, understanding related activity, documenting decisions, and managing cases.
5. Compliance capabilities
Fintech and financial-services businesses may need AML screening, sanctions checks, PEP screening, watchlists, and related compliance workflows alongside traditional fraud detection.
7 Best Fraud Prevention Software in 2026
| Software | Particularly relevant for | Key capabilities |
| SEON | Fintech, e-commerce, iGaming, marketplaces, digital businesses | Fraud API, device intelligence, risk scoring, custom rules, AML |
| Sift | E-commerce, marketplaces, digital businesses | Fraud decisioning, account protection, payment fraud, workflows |
| Sardine | Fintech and financial services | Fraud prevention, device intelligence, AML, transaction monitoring |
| Stripe Radar | Businesses using or integrating with Stripe payments | Payment fraud detection, risk scores, custom rules |
| Riskified | E-commerce merchants | Automated decisioning, payment protection, chargeback-focused tools |
| Forter | Digital commerce | Identity intelligence, payment and account protection, abuse prevention |
| Additional specialist solutions | Businesses with specific risk requirements | Options vary by industry, transaction type, and compliance needs |
1. SEON
SEON is an API-focused fraud prevention and risk management platform designed for businesses that need to evaluate users and transactions using multiple types of intelligence.
Its Fraud API combines email, phone, IP, BIN, AML, and device intelligence so businesses can request enriched information, rules, and scoring through a single API call. The API is modular, meaning organizations can enable or disable individual components according to their use case.
Businesses can learn more about the platform through the SEON fraud prevention solution.
Key SEON features
Fraud API:
SEON’s Fraud API brings several fraud and risk signals together through an API-first architecture. This can be useful for companies building fraud checks directly into their own applications.
Phone, IP, BIN, and device intelligence:
The platform provides dedicated APIs and intelligence for phone numbers, IP addresses, payment-card BIN information, and devices. Its Device Intelligence can collect device and behavioral information through web and mobile SDKs.
Custom rules and scoring:
Risk teams can create custom rules using available data points and suspicious signals. The scoring engine can then support decisions based on a company’s specific fraud policies.
AML screening:
SEON provides AML capabilities covering areas such as PEPs, sanctions, and high-risk names. Its documentation also recommends manual review of potential AML matches rather than treating screening as completely automated.
Case Management:
Case Management is included in SEON’s Premium offering, giving organizations a workflow for handling fraud and compliance investigations.
SEON pricing
SEON currently lists two main plans:
- Starter — $699/month: 2,500 fraud checks per month, 10 users, 50 custom rules, implementation assistance, basic monitoring, and standard reporting.
- Premium — Custom pricing: Unlimited API calls, users, and custom rules, along with Case Management & AML Compliance, dedicated implementation support, 24/7 support, and advanced monitoring/reporting.
Pricing and included capabilities can change, so businesses should confirm the current package directly with SEON before purchasing.
Who is SEON for?
SEON can be relevant to businesses that need a combination of fraud intelligence, API-based risk assessment, customizable decisioning, and AML capabilities. Typical use cases can include:
- Fintech
- Financial services
- E-commerce
- Online marketplaces
- iGaming
- Digital platforms
- Other businesses handling online accounts or transactions
SEON strengths
- API-first architecture
- Modular Fraud API
- Phone, IP, BIN, and device intelligence
- Custom rules and risk scoring
- Fraud and AML capabilities in the same ecosystem
- Device intelligence for web and mobile applications
- Case Management on the Premium plan
SEON limitations
SEON may not be the right fit for every business. The $699/month Starter price can be significant for very small companies with limited fraud volume. Premium pricing requires a custom quote.
The platform can also require technical integration and ongoing operational input. Businesses using advanced fraud and AML capabilities may need developers, fraud analysts, or compliance professionals to configure rules, investigate alerts, and review results.
AML screening should also be treated as part of an organization’s broader compliance process rather than as a substitute for internal review and risk controls. SEON itself notes that potential AML matches should be reviewed manually.
2. Sift
Sift provides a fraud prevention and decisioning platform covering multiple points in the digital customer journey. Its current platform includes capabilities for payment fraud, account takeover, fake accounts, e-commerce, and marketplaces.
The platform combines data enrichment, risk evaluation, decisioning, and workflow capabilities. It also provides analysts with visibility into the signals and decisions behind risk assessments.
Best suited to: Businesses looking for broader digital fraud decisioning across accounts, payments, and commerce.
Potential consideration: Companies should evaluate which Sift modules and services they actually require, as their needs may extend beyond straightforward payment-fraud detection.
3. Sardine
Sardine combines fraud prevention and financial-crime capabilities in a platform aimed particularly at fintech and financial-services use cases.
Its current offering includes device and behavioral intelligence, onboarding controls, account-takeover protection, bot detection, AML operations, transaction monitoring, sanctions screening, and case management.
Sardine also provides rules, workflows, machine-learning capabilities, and a connections graph for identifying relationships between users, devices, and transactions.
Best suited to: Fintechs and financial businesses that need fraud prevention alongside AML and financial-crime operations.
Potential consideration: Its broad financial-crime feature set may be more than a small online retailer needs if its main requirement is simple payment fraud detection.
4. Stripe Radar
Stripe Radar is particularly relevant for companies already using Stripe or businesses that want payment-focused fraud controls.
Radar uses machine learning for fraud prevention and provides features such as risk levels, fraud insights, rules, allowlists, blocklists, and manual review workflows.
Stripe has also expanded Radar beyond traditional card-payment protection, including support for additional fraud scenarios and capabilities for platforms and marketplaces.
Best suited to: Businesses that already operate within the Stripe ecosystem and want integrated payment fraud controls.
Potential consideration: Businesses seeking a broader standalone fraud and AML platform should compare Radar’s capabilities with their requirements beyond payment processing.
5. Riskified
Riskified focuses heavily on e-commerce fraud prevention and automated decisioning. Its platform uses device and behavioral information along with transaction and merchant-network data to assess online interactions.
Its product portfolio includes areas such as chargeback protection, policy abuse, account security, and payment optimization. The platform also provides dashboards and analytics intended to help teams understand fraud and payment activity.
Best suited to: E-commerce merchants that need fraud prevention closely connected to online shopping and payment workflows.
Potential consideration: Businesses outside e-commerce should check whether the platform’s focus aligns with their particular fraud and compliance requirements.
6. Forter
Forter provides fraud and trust technology focused on digital commerce. Its platform covers payment fraud, account protection, fake-account prevention, chargeback-related use cases, and different forms of commerce abuse.
The platform uses identity, behavioral, device, and payment signals as part of its decisioning approach. It also offers tools intended to help analysts investigate suspicious activity.
Best suited to: Large digital-commerce businesses managing payment, account, and customer-abuse risks.
Potential consideration: Companies should assess pricing, implementation requirements, and the specific products needed for their business model before selecting a platform.
7. Other Specialist Fraud Prevention Solutions
Not every business needs a broad fraud platform. Some companies may benefit from combining specialized tools around their existing payment, identity, or compliance infrastructure.
For example, a business may already have a payment processor and only need additional device intelligence, identity verification, transaction monitoring, or AML screening.
This approach can provide more control over the technology stack, but it can also introduce additional integration work. Multiple systems may mean more APIs, dashboards, data pipelines, and operational processes for fraud teams to maintain.
For that reason, businesses should compare the cost of individual tools against the operational simplicity of using a broader fraud management platform.
How to Choose the Right Fraud Prevention Software
The best choice depends less on the number of features and more on how those features fit your risk program.
For fintech and financial services
Look closely at AML screening, sanctions and PEP checks, transaction monitoring, case management, auditability, and API capabilities.
For e-commerce
Payment fraud, account takeover, card testing, device intelligence, chargebacks, and customer-abuse controls may be more important.
For marketplaces
Consider both sides of the marketplace. Seller onboarding, fake accounts, account takeover, payment fraud, and suspicious relationships between users may all require attention.
For iGaming
Device intelligence, geolocation-related controls, account abuse detection, AML capabilities, and responsible-gaming requirements can become important depending on the jurisdiction and business model.
For SaaS and digital platforms
Account creation, free-trial abuse, credential attacks, payment fraud, and automated abuse may be more relevant than traditional chargeback protection alone.
See also: Easy Ways to Cancel Online Subscriptions Quickly
Fraud Prevention Software Comparison
| Requirement | SEON | Sift | Sardine | Stripe Radar | Riskified | Forter |
| Fraud risk assessment | Yes | Yes | Yes | Yes | Yes | Yes |
| API-based capabilities | Yes | Yes | Yes | Yes | Yes | Yes |
| Device intelligence | Yes | Yes | Yes | Yes | Yes | Yes |
| Custom decisioning/rules | Yes | Yes | Yes | Yes | Yes | Yes |
| AML capabilities | Yes | Available capabilities vary | Yes | Not its primary focus | Not its primary focus | Not its primary focus |
| Case/investigation workflows | Yes | Yes | Yes | Manual review tools | Analytics/control tools | Investigation capabilities |
| E-commerce use cases | Yes | Yes | Yes | Yes | Strong focus | Strong focus |
| Fintech use cases | Yes | Yes | Strong focus | Yes | More commerce-focused | Yes |
The table is a high-level comparison of documented product capabilities, not a performance ranking. Availability can depend on product tier, configuration, region, or contract.
Why API-First Fraud Prevention Matters
Modern fraud prevention often needs to happen inside existing customer journeys rather than in a separate dashboard.
For example, a business might want to assess risk when someone:
- Creates an account
- Logs in from a new device
- Adds a payment method
- Makes a purchase
- Requests a withdrawal
- Changes important account information
An API-first system can allow those checks to become part of the existing workflow.
SEON’s documentation describes its Fraud API as a modular API that combines multiple data sources, including phone, IP, BIN, AML, and device intelligence, with rules and scoring.
However, API integration is not automatically better for every company. Businesses should consider developer resources, data requirements, latency expectations, privacy obligations, and how fraud decisions will be monitored after deployment.
Fraud Detection Is Only One Part of Risk Management
Buying fraud prevention software does not remove the need for a fraud strategy.
A strong program usually involves several connected elements:
- Clear risk policies
- Appropriate data collection
- Rules and decisioning
- Automated actions
- Manual investigation
- Customer verification
- Compliance review
- Feedback from confirmed fraud
- Regular rule maintenance
- Monitoring for false positives and false negatives
The software provides infrastructure and intelligence, but the business still needs to determine how risk should be handled.
Final Thoughts
Fraud prevention software has become an important part of digital risk management, but different businesses have very different requirements.
SEON stands out for organizations looking for an API-first approach that combines fraud intelligence, device data, customizable rules, scoring, and AML capabilities. Its modular architecture can be particularly relevant when a company wants to integrate risk checks directly into its own customer journeys.
Sift provides broader fraud decisioning across the customer journey, Sardine combines fraud and financial-crime capabilities, Stripe Radar is closely connected to payment workflows, while Riskified and Forter have strong digital-commerce orientations.
The practical choice should come down to the fraud types you need to address, the data you can provide, your technical resources, your compliance obligations, and how much control your team needs over risk decisions.
