Fraud & risk analytics · Unit21, Inc.

Unit21

No-code rules and case-management platform that lets fraud/AML ops teams build detection logic and investigate without engineers.

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Unit21 is built for the fraud and AML operations team itself rather than for data scientists: its core value is a no-code rules and workflow builder that lets analysts define velocity rules, device-risk checks and watchlist/sanctions screening without writing code, then investigate resulting alerts in a built-in case-management console. It layers behavioral modeling and graph analysis connecting entities across shared data points on top of the rules layer, and automates evidence collection, narrative drafting and SAR/CTR filing for compliance teams. It integrates directly with an institution's existing data warehouse (Snowflake, BigQuery, Databricks) and core banking or crypto data sources rather than requiring data migration. Deployed as a cloud SaaS platform, Unit21 differs from Featurespace or Feedzai by targeting fast self-configuration by non-technical risk teams over deep proprietary ML modeling, and from Alloy by focusing on ongoing transaction monitoring/investigation rather than onboarding decisioning.

At a glance

Vendor Unit21, Inc.
Pricing model Quote only
Free tier —
Deployment Cloud
Open source No
Best for Fraud and AML ops teams that want to configure detection rules and run investigations themselves without engineering support.

Pricing

Enterprise pricing quoted per customer based on data volume and modules; no self-serve signup or published rates.

Pricing has not been verified yet — see the vendor's site.

Features

  • No-code rules engine for velocity and behavioral checks
  • Case management with alert-to-SAR workflow automation
  • Graph/link analysis connecting entities across data points
  • Device risk scoring (rooted devices, VPNs, tampered browsers)
  • Sanctions and watchlist screening with fuzzy matching
  • Direct integration with existing data warehouses (Snowflake, BigQuery, Databricks)
  • Automated evidence collection and narrative drafting
  • Regulatory filing automation (SAR, STR, CTR, 314(a), goAML)

Integrations

Profile last reviewed September 21, 2026

Alternatives

Sift ML fraud-scoring platform that leans on a cross-customer consortium network plus device and behavioral signals. Sardine Fraud and AML platform leaning on behavioral biometrics, device intelligence and payment/on-chain risk signals. NICE Actimize Enterprise AML transaction-monitoring and fraud suite with heavy case-management and regulatory-filing workflows for banks. Alloy Identity risk orchestration platform that routes onboarding decisions across 270+ KYC/KYB and fraud data providers.

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Terms to know

Anomaly detection Identifying data points or patterns that deviate significantly from expected or normal behavior. Data quality The degree to which data is accurate, complete, consistent and fit for the purpose it is being used for. Data governance The policies, roles and processes that determine how data is defined, owned, accessed and kept compliant. Data warehouse A centralized, structured database optimized for fast historical reporting rather than day-to-day transactions. Risk scoring Assigning a numeric score to a customer, transaction, or entity that estimates the likelihood of a specific negative outcome. Transaction monitoring Ongoing, largely automated screening of financial transactions to flag activity that may indicate fraud or laundering.

Related guides

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