Chartis RiskTech Quadrant® for AI Governance Solutions recognizes six areas of strength:
- Model Coverage: SAS Viya supports a broad range of model types, including traditional ML, GenAI, LLMs and agentic systems.
- Governance: SAS helps firms mitigate AI and model risks, enabling automated enforcement of AI risk frameworks and regulations.
- Data Management: SAS capabilities emphasize data privacy and protection, visibility and benchmarking/mapping, while Viya's unified platform handles structured/unstructured data with audit trails.
- Model Management: SAS MRM expertise is a foundational pillar of its AI governance strategy, underpinning a forward-thinking approach to AI model risk at all stages of use and implementation.
- Visualization: SAS Viya provides visibility of the entire ecosystem via auditable reports, traceability dashboards and explainability tools designed to detail agentic AI decision-making.
- Workflow: The SAS platform supports unified workflows to help manage AI models, with a focus on automating governance tasks.
The RiskTech Quadrant for AI governance solutions is included in the Chartis report “Governance, Resilience and Compliance Solutions, 2025 – Digital Resilience: Quadrant Update."
The SAS Viya platform includes leading governance capabilities that extend classic machine learning model risk management, explainability, bias detection, privacy protection and end-to-end monitoring to the broader enterprise AI environment. By combining these capabilities with its deep expertise in regulated industries, SAS is in a position to demonstrate AI as a growth strategy for clients and prospects.” Michael Versace Chartis
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客戶案例
Intelligent, real-time fraud decisions in 50 milliseconds -
網路研討會
The Sector Series | Game Changing AI Technology for Governments: Computer Vision -
分析報告
The Forrester Wave™: Real-Time Interaction Management, Q4 2025 -
分析報告
Datos Matrix: Fraud and AML Case Management, 2025 -
網路研討會
Credit Risk Decisioning Using Intelligent Decisioning on SAS® Viya® -
電子書
Decisions you can trust: A strategic guide to trustworthy data and AI decision making -
白皮書
Building a foundation for innovation: Five steps to keep your AML program efficient and effective -
白皮書
Explainable Artificial Intelligence for Anti-Money Laundering -
白皮書
How AI and Machine Learning Are Redefining Anti-Money Laundering -
分析報告
The Forrester Wave™: Anti-Money Laundering Solutions, Q2 2025 -
白皮書
Rethinking risk: Smarter models, better decisions -
分析報告
Chartis RiskTech Quadrant for AML Transaction Monitoring Solutions, 2024 -
電子書
5 Steps to a Unified Enterprise Customer Decisioning Strategy -
分析報告
IDC MarketScape：2024 年全球決策情報 -
客戶案例
European Banking-as-a-Service leader strengthens its AML/CFT and fraud surveillance system with SAS -
客戶案例
Jakarta Smart City uses IoT analytics to better serve residents -
文章
4 strategies that will change your approach to fraud detection -
分析報告
SAS 在 Forrester Wave™ 2023 年第二季度 AI 決策平台報告中被評為領導者。 -
客戶案例
Combating financial crime and terrorism financing with real-time sanctions screening -
白皮書
Proactive anti-financial crime strategies to improve compliance and reduce risk -
客戶案例
Modern, real-time marketing increases customer loyalty and revenue for property management company and its retail tenants -
客戶案例
Stopping payment fraud in real time -
客戶案例
Finland’s top retail bank applies AI to improve customer service and credit scoring -
客戶案例
Real-time analytics helps telecom provider adapt to changing customer needs during global pandemic and beyond -
客戶案例
Fighting financial crime through a global anti-money laundering platform -
客戶案例
Complex telco product portfolio, maximum agility thanks to intelligent decisioning -
文章
Managing fraud risk: 10 trends you need to watch -
客戶案例
A risk-based approach to combat money laundering in Israel -
白皮書
AI Is at the Forefront of Reducing Money Laundering and Combating the Financing of Terrorism -
客戶案例
Preventing crime and ensuring compliance at 120 Nordic banks -
客戶案例
洗錢防制 -
文章
Mobile payments, smurfs and emerging threats -
文章
Rethink customer due diligence -
網路研討會
ESP Project Containers – How to Enhance ESP Models Deployment and Operationalization -
網路研討會
Real-Time Agent Assist and Next-Gen Strategy for Financial Services -
網路研討會
Orchestrating Your Multi-Wave Campaigns Through Scheduled Journeys -
網路研討會 Reinforcing Compliance Programs: Future-Proofing with SAS
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網路研討會
2022 Trends in Digital Fraud: ATOs, Scams and Solutions -
網路研討會
Shell game shutdown: Redefining trade transaction monitoring with automation and analytics -
網路研討會
Journey to AML Modernization -
網路研討會
Generative AI Meets AML: Elevating Compliance Standards in Banking -
網路研討會
Real-Time Watchlist Screening: Unlocking Efficiency and Compliance With SAS and Neterium -
網路研討會
Not All Heroes Wear Capes: How AI and Data Help Stop Money Laundering in the Opioid Crisis -
網路研討會
The Sector Series | Game Changing AI Technology for Governments: An Introduction to Artificial and Generative Intelligence for Public Sector Leaders -
網路研討會
Empowering Government Efficiency with SAS Managed Cloud Services on Microsoft Azure Government -
網路研討會
The Sector Series | Game Changing AI Technology for Governments: Machine Learning -
白皮書
Intelligent Decision Automation for Telecommunications in the Digital Age -
電子書
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FAQs
What is the Chartis RiskTech Quadrant® for AI governance solutions report?
It’s an independent analysis that evaluates AI governance solutions, highlighting vendor strengths and market trends.
Why is SAS recognized as a leader?
In this Chartis evaluation, SAS’ Category Leader placement reflects how it has developed MRM capabilities for generative AI (GenAI) with real-time anomaly detection – a vital feature as AI tools become more deeply embedded across the business.
How can SAS help my organization with AI governance solutions?
SAS ensures AI remains safe, trustworthy, and compliant with regulations, mitigating risks such as bias and misuse. Effective AI governance balances innovation with ethical responsibility.
What does "AI governance" mean?
It refers to the framework of policies, procedures, and ethical standards that govern and oversee the development, deployment, and operation of trustworthy AI systems.