Best AI Tools for E-commerce Fraud Prevention
Introduction
E-commerce fraud prevention refers to the systems and technologies that help online businesses identify, stop, and mitigate fraudulent activities such as stolen credit card payments, fake accounts, chargebacks, refund abuse, and bot-based attacks. As online shopping grows, so does the sophistication of fraudsters — making fraud prevention a critical part of every digital store’s risk strategy.
Fraud prevention plays a crucial role in maintaining customer trust and protecting revenue, and it becomes even more effective when connected with the broader intelligence systems across your store. For instance, combining fraud detection models with the operational oversight found in Best AI Tools for E-commerce Sales Analytics helps identify irregular patterns faster and more accurately. Fraud control also improves downstream logistics when aligned with workflows from Best AI Tools for E-commerce Order Fulfillment, reducing the chances of problematic shipments. Customer-facing systems benefit as well, especially when support workflows outlined in Best AI Tools for Customer Support Automation help resolve issues quickly and consistently. Store-wide reliability increases when fraud prevention tools integrate with operational automation described in Best AI Tools for E-commerce Store Automation. Meanwhile, SEO traffic protection becomes relevant when combined with strategies in Best AI Tools for E-commerce SEO, ensuring legitimate users are prioritized while suspicious behaviors are filtered early. Together, these layers create a secure environment where growth can happen without compromise.
Fraud challenges in e-commerce typically include:
- High transaction volume that makes manual review impossible
- Stolen card attacks and synthetic identity fraud
- Refund abuse, return manipulation, and chargeback fraud
- Fake accounts or bots used to exploit promotions
- Difficulty balancing fraud protection with a smooth customer experience
AI tools solve these challenges through real-time behavioral analysis, machine learning fraud scoring, device fingerprinting, identity verification, anomaly detection, and automated decision workflows. Instead of reactive review, AI can detect suspicious activity instantly, block risky transactions, and reduce false declines — protecting revenue while maintaining seamless checkout flow.
Below are the 25 best AI tools for e-commerce fraud prevention, organized with full details for each tool.
TOOL 1 — Signifyd
Overview
Signifyd provides AI-driven commerce protection that analyzes transactions in real time to detect fraud, approve legitimate buyers, and reduce chargebacks. Its machine learning models use behavioral analysis, identity data, and global commerce patterns to assess risk and automate order decisions.
Best For
Small to large e-commerce stores, especially those with international orders or high transaction volume.
Key Features
- Real-time AI fraud scoring
- Automated approve/decline decisions
- Chargeback protection on approved orders
- Identity and behavioral analysis
Use Cases
- Instantly block stolen-card purchases
- Reduce manual review for high-risk orders
- Approve more legitimate overseas orders
- Prevent return and refund abuse
Pricing
Tier-based pricing; typically pay-per-order or based on approved order volume.
Pros
- Very high fraud detection accuracy
- Reduces false declines significantly
- Scales for enterprise e-commerce operations
Cons
- Can become costly for low-margin products
Alternatives
Riskified
Forter
TOOL 2 — Riskified
Overview
Riskified uses machine learning and a global merchant network to automatically approve or decline orders. It focuses on maximizing legitimate order approvals while blocking fraud and reducing chargebacks.
Best For
Mid to large merchants needing guaranteed fraud decisions with minimal internal review.
Key Features
- Instant fraud decisioning
- Device and behavioral analysis
- Global identity and transaction intelligence
- Full chargeback guarantee
Use Cases
- Safely approve high-value or cross-border orders
- Reduce payment fraud and friendly fraud
- Protect revenue at checkout with full liability coverage
Pricing
Typically performance-based; charged on approved orders.
Pros
- Extremely accurate model
- Eliminates internal fraud liability
- Helps increase approval rates
Cons
- Higher pricing than rule-based systems
Alternatives
Signifyd
Forter
TOOL 3 — Kount
Overview
Kount provides AI-driven fraud scoring using identity data, device intelligence, and behavioral analytics. Instead of automatically approving/declining orders, it offers a flexible scoring system allowing merchants to set their own thresholds.
Best For
Merchants wanting deeper control over fraud policies and risk decisions.
Key Features
- Real-time risk scoring
- Device fingerprinting
- Custom rule engine + machine learning
- Multi-channel fraud prevention
Use Cases
- Flag risky orders for manual review
- Customize fraud thresholds for various product categories
- Detect card testing, bot abuse, or suspicious behavior patterns
Pricing
Based on transaction volume and fraud screening needs.
Pros
- Extremely flexible control
- Reduces false declines
- Strong device and identity graph
Cons
- Liability remains with the merchant
Alternatives
Sift
Forter
TOOL 4 — Sift
Overview
Sift is a digital trust and safety platform that protects e-commerce, SaaS, and marketplaces from payment fraud, account takeover, bot activity, and promotion abuse using AI-driven behavioral intelligence.
Best For
Businesses dealing with fraud beyond checkout — especially account-based fraud.
Key Features
- Behavioral AI fraud detection
- Account takeover protection
- Bot and abuse prevention
- Real-time risk scoring
Use Cases
- Detect unusual login behavior
- Block fraudulent checkout attempts
- Prevent mass fake account creation
- Automate fraud workflows across user lifecycle
Pricing
Usage-based depending on event volume.
Pros
- Protects more than just payments
- Excellent behavioral analytics
Cons
- Merchants must manage risk decisions internally
Alternatives
Kount
Signifyd
TOOL 5 — Forter
Overview
Forter delivers real-time AI decisions to approve or decline orders instantly. It provides identity intelligence and behavioral profiling to reduce fraud while improving conversion rates.
Best For
Large and high-volume e-commerce retailers needing immediate, automated decisions.
Key Features
- Instant approve/decline decisions
- Identity graph for global shoppers
- Automated fraud workflows
- Multi-channel fraud protection
Use Cases
- Speed up checkout with automated decisions
- Reduce manual review teams
- Accept more legitimate orders while blocking fraud
Pricing
Performance-based; varies by transaction volume.
Pros
- Strong accuracy and low false declines
- Designed for enterprises and high-speed checkout flows
Cons
- Less flexible than risk-scoring tools
Alternatives
Riskified
Signifyd
TOOL 6 — SecurionPay Fraud Suite
Overview
SecurionPay provides an AI-powered fraud detection suite designed to detect suspicious payment patterns, unusual transaction behavior, and identity inconsistencies. It strengthens checkout protection without increasing payment friction.
Best For
Small to mid-size e-commerce stores needing lightweight yet accurate fraud filtering.
Key Features
- AI-driven transaction risk scoring
- Rule-based triggers for suspicious activity
- Device and IP reputation tracking
- Adaptive checkout risk controls
Use Cases
- Block high-risk or suspicious payment attempts
- Reduce chargebacks with automated screening
- Identify unusual buyer patterns instantly
Pricing
Plan-based, depending on the transaction volume.
Pros
- Easy to integrate
- Effective for smaller stores
Cons
- Lacks advanced enterprise capabilities
Alternatives
FraudLabs Pro
Fraud.net
TOOL 7 — FraudLabs Pro
Overview
FraudLabs Pro uses machine learning, geolocation analysis, email/IP intelligence, and device fingerprinting to detect suspicious orders. It is known for its affordability and flexible rule engine.
Best For
Small businesses and online stores needing cost-effective fraud prevention.
Key Features
- Fraud scoring based on risk indicators
- Rule-based filtering
- Device fingerprinting and IP analysis
- Transaction monitoring alerts
Use Cases
- Filter suspicious orders automatically
- Identify mismatched location/payment info
- Reduce smaller-scale fraud attacks
Pricing
Offers multiple tiers including low-cost entry plans.
Pros
- Very budget-friendly
- Straightforward setup
Cons
- Not ideal for high-volume enterprise needs
Alternatives
SecurionPay
NoFraud
TOOL 8 — NoFraud
Overview
NoFraud screens every transaction in real time and makes automated decisions to approve or decline orders. It blends machine learning, identity verification, and behavioral analytics.
Best For
Merchants wanting outsourced fraud screening without manual review.
Key Features
- Real-time automated decisioning
- AI-driven identity analysis
- Chargeback protection options
- Quick integration for e-commerce platforms
Use Cases
- Eliminate manual review workload
- Reduce legitimate customer declines
- Identify fraud patterns quickly
Pricing
Typically percentage-based per transaction.
Pros
- High decision accuracy
- Very easy to deploy
Cons
- Less transparent decision logic
Alternatives
Signifyd
Riskified
TOOL 9 — ClearSale
Overview
ClearSale combines machine learning fraud detection with a human review team. Orders flagged as suspicious are reviewed manually to reduce false declines.
Best For
Merchants wanting a hybrid approach of AI + human review.
Key Features
- AI fraud scoring
- Manual review for flagged orders
- Chargeback reimbursement options
- Order approval notifications
Use Cases
- Reduce false positives for borderline orders
- Handle complicated fraud patterns
- Protect high-value purchases with second-level review
Pricing
Performance-based based on approved orders and fraud coverage.
Pros
- Extremely low false-decline rates
- Human review improves edge-case decisions
Cons
- Review process may add slight delay
Alternatives
Signifyd
NoFraud
TOOL 10 — Bolt Fraud Detection
Overview
Bolt integrates AI-based fraud detection directly into the checkout experience. It evaluates identity signals, behavior patterns, and device data to approve or block orders instantly.
Best For
Fast-growing D2C brands wanting optimized checkout + built-in fraud protection.
Key Features
- Real-time fraud scoring
- Identity authentication
- Behavioral pattern detection
- Checkout friction reduction
Use Cases
- Faster and safer checkout flows
- Detect bot-driven attempts or fake accounts
- Reduce abandoned carts due to unnecessary verification
Pricing
Included within Bolt’s commerce and checkout products.
Pros
- Turnkey checkout + fraud solution
- Designed to reduce friction
Cons
- Works best within Bolt’s ecosystem
Alternatives
Forter
Signifyd
TOOL 11 — Stripe Radar
Overview
Stripe Radar is built into Stripe’s payment processing system and uses machine learning to block fraudulent card payments, detect suspicious activity, and reduce chargebacks.
Best For
Merchants already using Stripe for payments.
Key Features
- AI-based fraud detection
- Custom rule builder
- Machine learning trained on global transactions
- Card risk scoring
Use Cases
- Automatically block fraudulent card activity
- Adjust risk rules for different product types
- Analyze patterns behind declined transactions
Pricing
Included in Stripe; advanced features offered at additional cost.
Pros
- Extremely easy to activate
- Strong global data training
Cons
- Limited beyond card payment fraud
Alternatives
Adyen RevenueProtect
Braintree fraud tools
TOOL 12 — Adyen RevenueProtect
Overview
Adyen RevenueProtect uses machine learning, device intelligence, and risk rules to automatically detect fraud while optimizing conversion and authorization rates.
Best For
Mid to large merchants processing global transactions.
Key Features
- AI-based risk engine
- Device fingerprinting
- Behavioral analysis
- Comprehensive rule configuration
Use Cases
- Improve authorization rates with optimized fraud rules
- Detect unusual payment attempts
- Protect cross-border transactions
Pricing
Included with Adyen payment processing.
Pros
- Highly scalable for global use
- Integrated with payments for better approval rates
Cons
- Best for businesses already using Adyen
Alternatives
Stripe Radar
Braintree
TOOL 13 — Braintree Fraud Protection
Overview
Braintree offers built-in fraud detection that uses AI, risk indicators, and behavioral analysis to screen transactions and reduce payment fraud.
Best For
Businesses using Braintree for payment processing.
Key Features
- Risk scoring for every transaction
- Device and location analysis
- Rule-based filtering
- Integration with checkout flow
Use Cases
- Reduce credit card fraud
- Detect risky patterns early
- Screen suspicious international orders
Pricing
Included in Braintree payments; advanced tools require add-ons.
Pros
- One-click implementation
- Good for small and mid-sized stores
Cons
- Not suitable as a standalone enterprise solution
Alternatives
Stripe Radar
Adyen RevenueProtect
TOOL 14 — Ekata (Identity Verification AI)
Overview
Ekata uses AI-driven identity verification to examine email, phone, address, and device data to determine whether a buyer is genuine. It focuses on identity confidence rather than transaction activity alone.
Best For
Merchants struggling with identity fraud, synthetic accounts, or account takeover.
Key Features
- Real-time identity risk scoring
- Email, phone, and address intelligence
- Identity behavior insights
- Device + network linking
Use Cases
- Block identity-based fraud attempts
- Prevent fake or synthetic account creation
- Reduce checkout fraud by verifying identity data
Pricing
Based on identity checks performed.
Pros
- Excellent for identity-focused fraud
- Works across account and checkout stages
Cons
- Not a full fraud prevention platform by itself
Alternatives
SEON
TruValidate
TOOL 15 — SEON
Overview
SEON provides fraud detection through digital footprint analysis, email/phone profiling, device fingerprinting, and AI-powered scoring. It is known for its depth and visibility into user identity signals.
Best For
E-commerce stores, fintech platforms, and marketplaces needing modular fraud detection.
Key Features
- Email and phone profiling
- Digital footprint lookup
- Device intelligence
- Machine learning fraud scoring
Use Cases
- Detect fake identities
- Prevent account takeover
- Screen suspicious buyers before checkout
Pricing
Modular usage-based pricing.
Pros
- Transparent insights for investigation
- Highly customizable
Cons
- Requires some expertise to tune
Alternatives
Ekata
TruValidate
TOOL 16 — TruValidate (Formerly Iovation)
Overview
TruValidate provides device intelligence, identity verification, and risk scoring to stop fraud across checkout, login, and account creation. Its strength lies in analyzing device reputation to detect risky or previously associated fraudulent activity.
Best For
Merchants dealing with repeat fraud attempts from recurring devices or networks.
Key Features
- Device reputation scoring
- Identity confidence analysis
- Behavioral risk detection
- Multi-layer identity verification
Use Cases
- Block known fraudulent devices automatically
- Identify bots or suspicious repeated attempts
- Detect login fraud before checkout occurs
Pricing
Based on identity and device checks performed.
Pros
- Excellent device reputation database
- Strong for account-based fraud
Cons
- Not a full standalone platform for payment fraud
Alternatives
SEON
Ekata
TOOL 17 — Fraud.net
Overview
Fraud.net uses AI, collaborative intelligence, and multi-channel risk signals to detect payment fraud, account takeover, and suspicious behavior patterns across commerce channels.
Best For
Mid to enterprise merchants needing unified fraud intelligence.
Key Features
- Machine learning fraud detection
- Email, IP, and device intelligence
- Behavioral monitoring
- Collaborative fraud network signals
Use Cases
- Block high-risk transactions
- Identify unusual behavior patterns
- Reduce cross-channel fraud attempts
Pricing
Enterprise pricing based on transaction volume.
Pros
- Very comprehensive data signals
- Strong enterprise configuration options
Cons
- Requires technical setup for full capabilities
Alternatives
Kount
Sift
TOOL 18 — PerimeterX (HUMAN Security)
Overview
PerimeterX (now HUMAN Security) uses AI to block bot attacks, credential stuffing, fake account creation, and automated fraud attempts that target e-commerce platforms.
Best For
Stores experiencing bot-based fraud, scraping, or mass account abuse.
Key Features
- AI bot detection and mitigation
- Behavioral traffic analysis
- Account and login abuse prevention
- Fraudulent checkout attempt blocking
Use Cases
- Stop automated bots executing stolen-card purchases
- Prevent mass fake account creation
- Protect high-demand drops from automated scalping
Pricing
Tier-based depending on traffic and attack volume.
Pros
- Best-in-class bot mitigation
- Protects multiple e-commerce touchpoints
Cons
- Not focused on payment fraud specifically
Alternatives
Kasada
Arkose Labs
TOOL 19 — Arkose Labs
Overview
Arkose Labs focuses on stopping bots, abuse, and fake accounts using adaptive challenges powered by AI. It raises friction only for attackers while keeping real customers friction-free.
Best For
Marketplaces, e-commerce brands, and apps facing high levels of automated fraud.
Key Features
- Bot and abuse prevention
- Adaptive risk-based challenges
- Behavioral analysis
- Account integrity protection
Use Cases
- Stop credential-stuffing attacks
- Prevent bulk fake account creation
- Protect signup, login, and checkout flows
Pricing
Based on traffic and volume of verification challenges.
Pros
- Strong defense against automated fraud
- Very low friction for real customers
Cons
- Requires integration effort
Alternatives
PerimeterX
Kasada
TOOL 20 — Kasada
Overview
Kasada provides AI-driven bot detection and anti-automation tools that help e-commerce brands detect sophisticated bot networks, fraud bots, and automated scrapers.
Best For
Brands targeted by bot-driven fraud or large-scale scraping.
Key Features
- AI bot detection
- Script and automation fingerprinting
- Behavioral anomaly detection
- Real-time bot mitigation
Use Cases
- Stop bot-driven card testing
- Prevent scraping of product and pricing data
- Protect limited-edition launches
Pricing
Subscription-based.
Pros
- Highly effective for bot mitigation
- Protects multiple layers of the user journey
Cons
- Does not focus on payment fraud
Alternatives
PerimeterX
Arkose Labs
TOOL 21 — Fingerprint (Device Intelligence AI)
Overview
Fingerprint provides device intelligence and behavioral signal analysis to give merchants deep insight into device identity and legitimacy, helping identify repeat fraudsters or risky devices.
Best For
Stores needing device-level fraud analysis beyond standard transaction checks.
Key Features
- Device fingerprinting
- Browser and network identity mapping
- Behavioral signal detection
- Fraud pattern monitoring
Use Cases
- Block devices linked to past fraud
- Detect shared or spoofed device environments
- Reduce synthetic identity fraud
Pricing
API usage-based.
Pros
- Highly accurate device identity profiles
- Helps catch hard-to-detect fraud
Cons
- Requires integration with risk scoring system
Alternatives
TruValidate
SEON
TOOL 22 — ThreatMetrix (LexisNexis Risk Solutions)
Overview
ThreatMetrix provides identity intelligence using global shared data, device behavior, and AI risk scoring to stop identity fraud, payment fraud, and account takeover attempts.
Best For
Enterprise e-commerce brands protecting multiple customer touchpoints.
Key Features
- Global identity intelligence
- Device and behavioral biometrics
- AI risk scoring
- Cross-channel fraud detection
Use Cases
- Prevent account takeover before it escalates
- Block high-risk or suspicious transactions
- Detect synthetic identities early
Pricing
Enterprise-tier.
Pros
- Very high accuracy
- Broad fraud coverage
Cons
- Complex implementation
Alternatives
Riskified
Sift
TOOL 23 — Shield AI Fraud Platform
Overview
Shield provides AI-driven fraud detection for commerce and fintech environments. It detects suspicious behaviors, high-risk payments, and identity irregularities using adaptive machine learning.
Best For
Mid-size e-commerce stores needing flexible fraud analytics.
Key Features
- Adaptive ML fraud scoring
- Behavioral pattern detection
- Transaction risk evaluation
- Customizable rule automation
Use Cases
- Identify unusual buying patterns
- Detect high-risk payment attempts
- Improve approval rates without increasing fraud
Pricing
Usage-based plans.
Pros
- Flexible and tunable
- Good fit for mid-size merchants
Cons
- Lacks full lifecycle trust and safety features
Alternatives
Fraud.net
Kount
TOOL 24 — DataDome
Overview
DataDome focuses on AI-powered bot detection, blocking automated attacks, scraping, and fraudulent bot-driven purchases. It safeguards checkout, login, and inventory.
Best For
Brands facing bot traffic, scraping, scalping, or card-testing.
Key Features
- Real-time AI bot detection
- Behavioral traffic scoring
- Fraud bot blocking
- Dashboard with traffic intelligence
Use Cases
- Stop automated card testing
- Block scalper bots during limited releases
- Protect site resources from malicious automation
Pricing
Subscription-based.
Pros
- Strong at bot-based fraud
- Easy to deploy on modern storefronts
Cons
- Not a payment fraud platform
Alternatives
Kasada
PerimeterX
TOOL 25 — ChatGPT Fraud Detection Assistant
Overview
ChatGPT can analyze exported transaction data, detect fraud patterns, and generate rule suggestions or risk explanations. While not a full fraud platform, it enhances investigation and decision-making workflows.
Best For
Analysts, small stores, and teams needing flexible insights without complex software.
Key Features
- Pattern identification from transaction data
- Fraud cluster detection
- Rule and workflow recommendations
- Explanations for risky behaviors
Use Cases
- Analyze suspicious order lists
- Generate insights for rule tuning
- Support manual fraud review teams
Pricing
Subscription-based usage.
Pros
- Extremely flexible
- Works with any dataset
Cons
- Not a standalone fraud prevention system
Alternatives
Custom ML tools
SEON
Final Verdict
AI-driven fraud prevention is essential for modern e-commerce because fraud is more sophisticated, faster, and more automated than ever. These tools help businesses detect suspicious activity in real time, reduce operational burden, and protect revenue without affecting customer experience.
Best for small stores
- Stripe Radar
- FraudLabs Pro
- NoFraud
- SecurionPay
Best for mid-size brands
- Kount
- SEON
- ClearSale
- TruValidate
Best enterprise-grade solutions
- Signifyd
- Riskified
- Forter
- ThreatMetrix
Best for bot and automation fraud
- PerimeterX
- Kasada
- DataDome
Each merchant should select tools based on:
- Fraud type (payment fraud vs bots vs account takeover)
- Transaction volume
- Geography and customer base
- Need for chargeback protection vs scoring flexibility
Combining AI fraud tools with strong operational policies achieves maximum protection.
FAQs
1. Do AI fraud prevention tools slow down checkout?
No. Modern AI fraud systems make decisions instantly, keeping checkout smooth while blocking risky transactions.
2. Can AI stop both payment fraud and account takeover?
Some tools specialize in payment fraud, while others protect accounts. Full coverage often requires a combination of both.
3. What causes false declines?
Overly strict rules or outdated fraud systems can block legitimate customers. AI reduces false declines by analyzing more data points.
4. Do fraud tools protect against bots?
Yes. Tools like DataDome, PerimeterX, and Kasada focus specifically on bot-driven fraud and automated threats.
5. Should small stores invest in fraud prevention?
Yes. Even small stores face chargebacks, card testing, and refund abuse — AI tools help minimize financial loss early.