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SAS Institute

Analytics-led AML monitoring, CDD and investigations on SAS's cloud-native platform

Overview

SAS Anti-Money Laundering is sold by SAS Institute, the analytics company founded by Jim Goodnight and John Sall and headquartered in Cary, North Carolina, which describes more than 50 years of analytics development[8]. The product covers transaction monitoring, AI and machine learning, customer due diligence, entity resolution, investigation management and regulatory reporting[7].

Out-of-the-box scenarios and network analytics target threats including virtual currencies, human trafficking, trade-based money laundering and drug trafficking. Integrated CDD and enhanced due diligence support what SAS calls perpetual KYC, triggered by demographic or behavioural changes, and network analytics help identify ultimate beneficial owners. Entity resolution deduplicates customer records and builds relationship networks in real time rather than in overnight batches, and low-code tools let compliance teams write scenarios, configure screens and build workflows without developers[7]. SAS stresses explainability: the system shows why activity was flagged so that auditors and model-governance staff can follow the logic. Named customers include Bangkok Bank, Landsbankinn and a Nordic group of 120 banks[7]. Prices are not published, and buyers typically need in-house analytics skills to exploit the modelling tools fully.

SAS Institute features

  • Scenario library covering trade-based laundering and trafficking typologies
  • Perpetual KYC with CDD/EDD triggers
  • Real-time entity resolution and network analytics
  • Low-code scenario authoring and workflow design
  • Investigation management and regulatory reporting
  • Explanations of why activity was flagged
  • Real-time fraud decisioning
  • Machine learning and predictive analytics

SAS Institute pricing

Quote-based ("Request Pricing"). SAS offers a free trial of its Viya platform, but not a published price for the AML product.

SAS Institute strengths and limitations

Strengths

  • Strong analytics, modelling and explainability tooling
  • Low-code configuration for compliance teams
  • Entity resolution and UBO network analysis built in
  • Strong modelling and analytics depth
  • Supports custom models
  • Integrated with wider SAS analytics

Limitations

  • No published pricing
  • Benefits depend on in-house analytics expertise
  • Product page does not detail deployment options beyond a cloud-native architecture
  • Requires analytics expertise to exploit fully
  • Less turnkey than consortium-model vendors
  • Only a rounded revenue figure is published

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