SAS is a Leader in The Forrester Wave™: Enterprise Fraud Management, Q2 2024
As noted in the Forrester evaluation, "SAS provides a broad selection of out-of-the-box EFM machine learning models. The vendor's EFM vision and product roadmap are first-rate and include not only transaction monitoring but also cyber (online) fraud management."
SAS’s productized, out-of-the-box supervised and unsupervised machine learning models for banking transaction monitoring are ahead of the competition and require less effort to train than those of competitors. Analyst investigation screens are intuitive and customizable. Reporting is versatile, visually pleasing, and easy to configure."
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電子書
Seven trends shaping the future of tax -
電子書
Public procurement integrity at risk -
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 -
電子書
Your journey to a GenAI future: A strategic path to success in banking -
分析報告
Chartis RiskTech Quadrant for Watchlist and Adverse Media Monitoring 2024 -
電子書
On the Road to Accelerating Claims Automation -
分析報告
SAS is a Leader in The Forrester Wave™: AI Decisioning Platforms, Q2 2023. -
白皮書
What Lies Beneath -
白皮書
Generative AI in Health Care: Opportunities and Cautions -
文章
6 ways big data analytics can improve insurance claims data processing -
文章
Containing health care costs: Analytics paves the way to payment integrity -
文章
Know your blind spots in tax fraud prevention -
文章
Putting an end to pay and chase -
分析報告
Chartis RiskTech Quadrant for Trade-Based AML Solutions 2022 -
分析報告
Chartis RiskTech100 2024 -
分析報告
SAS is a Leader in The Forrester Wave™: Anti-Money Laundering Solutions, Q3 2022 -
客戶案例
Fighting loan application fraud with cutting-edge analytics -
客戶案例
European Banking-as-a-Service leader strengthens its AML/CFT and fraud surveillance system with SAS -
客戶案例
Combating financial crime and terrorism financing with real-time sanctions screening -
客戶案例
Stopping payment fraud in real time -
電子書
Protecting the Payments -
白皮書
Effective fraud analytics: 10 steps to detect and prevent insurance fraud -
電子書
Faces of Fraud -
白皮書
Protect the Integrity of the Procurement Function -
文章
When it matters: Safeguarding your organization from the inside -
分析報告
IDC MarketScape: Worldwide Responsible Artificial Intelligence for Integrated Financial Crime Management Platforms 2022 Vendor Assessment -
白皮書
Using Modern Analytics to Save Government Programs Millions -
文章
5 steps to sustainable GDPR compliance -
分析報告
Chartis RiskTech Quadrant for Enterprise Fraud Solutions, 2023: Vendor Analysis -
白皮書
Managing Fraud Risk in the Digital Age -
白皮書
Enforcing Tax Compliance in a Turbulent World -
文章
Continuous monitoring: Stop procurement fraud, waste and abuse now -
分析報告
Matrix: Leading Fraud & AML Machine Learning Platforms -
分析報告
Matrix: Payment Integrity In Healthcare -
白皮書
Machine Learning Use Cases in Financial Crimes -
白皮書
Keeping Fraud Detection Software Aligned With the Latest Threats -
文章
Analytics: A must-have tool for leading the fight on prescription and illicit drug addiction -
文章
4 strategies that will change your approach to fraud detection -
文章
Unemployment fraud meets analytics: Battle lines are clearly drawn -
客戶案例
Advanced analytics and machine learning help Poste Italiane identify and stop fraud in real time while enhancing customer experience -
白皮書
Fighting Insurance Application Fraud -
文章
Analytics for prescription drug monitoring: How to better identify opioid abuse -
白皮書
Data and Analytics to Combat the Opioid Epidemic -
文章
Online fraud: Increased threats in a real-time world -
白皮書
Leveraging Analytics to Combat Digital Fraud in Financial Organizations -
白皮書
Proactive anti-financial crime strategies to improve compliance and reduce risk -
白皮書
Achieving program integrity for health care cost containment -
文章
How to prevent procurement fraud -
白皮書
Government Procurement Offices -
白皮書
Fraud in Communications -
客戶案例
A risk-based approach to combat money laundering in Israel -
白皮書
Rethinking customer due diligence -
白皮書
2021 State of Insurance Fraud Technology Study -
白皮書
Detect and prevent digital banking fraud -
文章
Detect and prevent banking application fraud -
白皮書
Next-generation AML -
文章
Are you covering who you think you’re covering? -
分析報告
Celent: Insurance Fraud Detection Solutions: Health Insurance, 2022 Edition -
分析報告
Celent Insurance Fraud Detection Solutions: Property and Casualty Insurance, 2022 Edition -
白皮書
Banking in 2035: global banking survey report -
文章
Top prepaid card fraud scams -
文章
Improve child welfare through analytics -
白皮書
Procurement integrity powered by continuous monitoring -
白皮書
Banking in 2035: three possible futures -
白皮書
AML Modernization -
電子書
The Future of Energy & Utilities: Transform Through Innovation -
白皮書
Data-Driven Performance -
白皮書
Fighting the Rising Tide of Medicaid Fraud -
白皮書
Fraudsters love digital -
白皮書
Data, analytics and machine learning: The new frontier of fraud prevention -
白皮書
Anti-Fraud Technology -
白皮書
Value and Opportunity: An Executive Guide to Procurement Integrity -
電子書
Fight money laundering with these 5 next-gen game changers from SAS -
電子書
High velocity decisions. Trusted outcomes. -
白皮書
Top Trends: Why Tax Administrators Are Adopting New Data and Analytics Strategies -
白皮書
Payments Without Borders -
白皮書
The Escalation of Digital Fraud -
白皮書
Safer communities, trusted law enforcement -
白皮書
How Public Sector Agencies Can Use Analytics to Lead Through Crisis -
白皮書
How AI and Machine Learning Are Redefining Anti-Money Laundering -
白皮書
Managing the Intelligence Life Cycle -
白皮書
Balancing Fraud Detection and the Customer Experience -
白皮書
AI Is at the Forefront of Reducing Money Laundering and Combating the Financing of Terrorism -
白皮書
Detect and Prevent Identity Theft -
文章
Payment fraud evolves fast – can we stay ahead? -
文章
疫情期間網路交易大增，全面防護金融詐欺犯罪 -
客戶案例
Managing mergers and analytics: Ensuring reliable energy by eliminating risk -
文章
The best gift you can give to thieves this holiday season? Your identity. -
文章
Shut the front door on insurance application fraud! -
文章
Online payment fraud stops here -
文章
Strengthen your payment fraud defenses with stronger authentication -
文章
Fraud detection and machine learning: What you need to know -
文章
Health care cost containment through big data analytics -
文章
Managing fraud risk: 10 trends you need to watch -
客戶案例
Turkish insurer achieves real-time fraud detection -
客戶案例
Preventing payment card fraud one transaction at a time -
客戶案例
Advanced analytics can detect and prevent insurance fraud before losses occur -
客戶案例
Fighting financial crime through a global anti-money laundering platform -
客戶案例 fluvius uses sas procurement cockpit
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文章
Taking pre-emptive action to stem the tide of VAT fraud losses -
文章
Mobile payments, smurfs and emerging threats -
文章
Stop contract and procurement fraud -
文章
Medicaid and benefit fraud in 2018 and beyond -
文章
Applying technology to ensure voter integrity in elections -
文章
Rethink customer due diligence -
文章
Detecting health care claims fraud -
文章
How to uncover common point of purchase -
客戶案例
泰國銀行在即時管理詐欺偵測的同時也保護客戶 -
文章
Uncover hidden financial crime risk -
文章
How AI and advanced analytics are impacting the financial services industry -
文章
What do drones, AI and proactive policing have in common? -
客戶案例
洗錢防制 -
客戶案例
Fast analytical defense -
客戶案例
Preventing crime and ensuring compliance at 120 Nordic banks -
文章
Proactive detection – A new approach to counter terror
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