The closest alternatives to Unit21 on Lister are Feedzai, the companies that share the most rankings with it. Each is compared below on its stated best fit, starting price and Lister Score.
Unit21 alternatives, compared| # | ALTERNATIVE | BEST FOR | SCORE | FROM | RANKED |
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| 1 |  FeedzaiExplainable AI fraud detection for financial institutions | Banks and fintech companies requiring compliance-first fraud detection with explainable AI | 90.3 | Custom | #3 in Top 10 AI Fraud-Detection ToolsOn 2 of Unit21's rankings |
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| 2 |  Mastercard Decision IntelligenceEnterprise fraud intelligence for global payment networks | Large financial institutions and payment networks requiring global fraud coverage | 95.0 | Custom | #1 in Top 10 AI Fraud-Detection Tools |
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| 3 |  Stripe RadarMachine learning fraud detection built into payment processing | E-commerce platforms and SaaS companies using Stripe for payment processing | 92.7 | 0.5% of blocked transactions | #2 in Top 10 AI Fraud-Detection Tools |
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| 4 |  KountAI-powered fraud prevention across digital commerce and payments | Mid to large e-commerce retailers and online marketplaces seeking advanced fraud and chargeback prevention | 88.0 | Custom | #4 in Top 10 AI Fraud-Detection Tools |
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| 5 |  DataVisorUnsupervised machine learning fraud detection platform | Financial institutions and fintech platforms facing evolving fraud tactics and zero-day attacks | 85.7 | Custom | #5 in Top 10 AI Fraud-Detection Tools |
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| 6 |  EmailageEmail intelligence and identity verification for fraud prevention | E-commerce platforms and financial services looking for quick identity verification and account takeover prevention | 83.3 | Custom | #6 in Top 10 AI Fraud-Detection Tools |
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| 7 |  SiftAI-powered fraud and abuse prevention for digital platforms | Marketplaces and fintech platforms requiring comprehensive fraud and abuse prevention across multiple user interactions | 81.0 | Custom | #7 in Top 10 AI Fraud-Detection Tools |
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| 8 |  ForterReal-time fraud and chargeback prevention for online retailers | E-commerce retailers seeking to minimise both fraud and false declines during high-volume sales periods | 76.3 | Custom | #9 in Top 10 AI Fraud-Detection Tools |
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| 9 |  WorkFusionAI digital workers for operations | Financial services automation | 78.0 | Custom | #10 in Best AI AML tools |
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| 10 |  Symantec (formerly Blue Coat) DLPData loss prevention and insider threat detection | Enterprises requiring comprehensive insider threat detection and data protection alongside fraud prevention | 74.0 | Custom | #10 in Top 10 AI Fraud-Detection Tools |
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How to choose an alternative to Unit21
Start from what you need it for. Where each fits best, as Lister records it:
- Feedzai: Banks and fintech companies requiring compliance-first fraud detection with explainable AI
- Mastercard Decision Intelligence: Large financial institutions and payment networks requiring global fraud coverage
- Stripe Radar: E-commerce platforms and SaaS companies using Stripe for payment processing
- Kount: Mid to large e-commerce retailers and online marketplaces seeking advanced fraud and chargeback prevention
- DataVisor: Financial institutions and fintech platforms facing evolving fraud tactics and zero-day attacks
- Emailage: E-commerce platforms and financial services looking for quick identity verification and account takeover prevention
- Sift: Marketplaces and fintech platforms requiring comprehensive fraud and abuse prevention across multiple user interactions
- Forter: E-commerce retailers seeking to minimise both fraud and false declines during high-volume sales periods
- WorkFusion: Financial services automation
- Symantec (formerly Blue Coat) DLP: Enterprises requiring comprehensive insider threat detection and data protection alongside fraud prevention
Closest to Unit21 by the rankings they share: Feedzai (2 rankings).
Custom or quote-based pricing: Feedzai, Mastercard Decision Intelligence, Kount, DataVisor, Emailage, Sift, Forter, WorkFusion and Symantec (formerly Blue Coat) DLP.
Each Lister Score is the alternative's score on the ranking named in its row, so compare scores within one ranking rather than across rankings. How the score is made.
Each alternative in brief
01
Explainable AI fraud detection for financial institutions
#3 in Top 10 AI Fraud-Detection Tools: Feedzai provides cloud-based fraud detection and anti-money laundering solutions powered by machine learning. The platform emphasises explainability, allowing financial institutions to understand why transactions are flagged, which is critical for regulatory compliance.
PROS- Focus on explainable AI helps meet regulatory and audit requirements
- Handles both fraud detection and AML/KYC compliance in one platform
CONS- Enterprise-focused pricing with custom implementation required
- Steep learning curve for non-technical stakeholders
90.3
02
Enterprise fraud intelligence for global payment networks
#1 in Top 10 AI Fraud-Detection Tools: Mastercard's proprietary AI platform processes billions of transactions daily, using advanced machine learning to detect fraud patterns across payment systems. It combines network intelligence with behavioral analytics to identify emerging threats before they impact consumers.
PROS- Unmatched scale and real-time processing power across global payment systems
- Proprietary network intelligence leveraging trillions of data points
CONS- Typically accessible only to Mastercard partners and large institutions
- High implementation complexity and cost
95.0
03
Machine learning fraud detection built into payment processing
#2 in Top 10 AI Fraud-Detection Tools: Stripe's integrated fraud prevention tool uses machine learning models trained on Stripe's global transaction network to identify suspicious activity. It provides real-time risk assessment and automatic decline capabilities for online merchants.
PROS- Seamless integration with Stripe's payment infrastructure
- No additional setup required for basic protection; advanced rules available
CONS- Only available to Stripe customers
- Limited customisation for highly specialised fraud patterns
92.7
04
AI-powered fraud prevention across digital commerce and payments
#4 in Top 10 AI Fraud-Detection Tools: Kount offers real-time fraud decisioning and chargeback prevention for e-commerce, travel, and digital goods merchants. Its machine learning engine combines device fingerprinting with behavioural analysis to distinguish legitimate customers from fraudsters.
PROS- Comprehensive chargeback guarantee programme reduces merchant liability
- Strong device fingerprinting and bot detection capabilities
CONS- Pricing can be prohibitive for smaller merchants
- Integration complexity may require dedicated technical resources
88.0
05
Unsupervised machine learning fraud detection platform
#5 in Top 10 AI Fraud-Detection Tools: DataVisor's proprietary unsupervised learning technology detects novel fraud patterns without relying on historical fraud labels. This approach enables early detection of new fraud schemes before they become widespread.
PROS- Exceptional at detecting novel fraud schemes due to unsupervised learning approach
- Reduces false positives through anomaly detection rather than rule-based systems
CONS- Higher implementation and setup time compared to rule-based alternatives
- Requires significant historical transaction data for optimal performance
85.7
06
Email intelligence and identity verification for fraud prevention
#6 in Top 10 AI Fraud-Detection Tools: Emailage provides email-based identity verification and risk scoring to prevent account takeover and fraud. The platform leverages email data science, device intelligence, and user behaviour analysis to assess transaction risk in milliseconds.
PROS- Lightweight integration with minimal friction to user experience
- Rapid identity verification reduces account takeover incidents significantly
CONS- Primary value diminishes for high-risk profiles already identified by other signals
- Pricing structure may favour high-volume transaction processors
83.3
07
AI-powered fraud and abuse prevention for digital platforms
#7 in Top 10 AI Fraud-Detection Tools: Sift provides real-time machine learning fraud detection for e-commerce, fintech, and digital services. Its platform learns from billions of user interactions to identify fraud, account takeover, and content abuse across connected ecosystems.
PROS- Excellent for detecting account takeover and identity theft patterns
- Strong network effects provide improved accuracy across connected merchants
CONS- Pricing is consumption-based and can scale significantly with volume
- Requires integration across multiple transaction touchpoints for optimal accuracy
81.0
08
Real-time fraud and chargeback prevention for online retailers
#9 in Top 10 AI Fraud-Detection Tools: Forter delivers real-time transaction authorisation decisions for e-commerce merchants, reducing fraud losses and chargebacks whilst minimising false positives. Its AI engine analyses transaction context and customer behaviour to distinguish legitimate purchases.
PROS- Exceptionally low false positive rate preserves customer experience
- Real-time authorisation decisions prevent lost revenue from declined legitimate transactions
CONS- Pricing opaque and typically requires merchant volume discussions
- Primarily designed for e-commerce; limited applicability to other verticals
76.3
09
AI digital workers for operations
#10 in Best AI AML tools: WorkFusion provides AI Agents that act as digital analysts for financial crime compliance. These tools help organisations scale their teams to mitigate risk and improve efficiency.
PROS- Pre-built industry bots
- Strong document processing
CONS- Limited flexibility outside target industries
78.0
10
Data loss prevention and insider threat detection
#10 in Top 10 AI Fraud-Detection Tools: Symantec's data loss prevention platform uses machine learning to detect and prevent unauthorised data exfiltration and insider threats. Whilst traditionally a DLP solution, it includes fraud-relevant capabilities for detecting suspicious user behaviour and data access patterns.
PROS- Comprehensive insider threat detection prevents fraud from internal actors
- Integration with network and endpoint security creates holistic threat visibility
CONS- Can generate significant false positives without careful tuning
- Complex deployment and ongoing management required for optimal results
74.0