Analyst Report
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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- Article ТОП-5 схем мошенничества по предоплаченной карте
- E-Book 5 Steps to a Unified Enterprise Customer Decisioning Strategy
- E-Book Your journey to a GenAI future: A strategic path to success in banking
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- Аналитический отчет Chartis RiskTech Quadrant for Watchlist and Adverse Media Monitoring 2024
- E-Book On the Road to Accelerating Claims Automation
- Article Проактивное обнаружение - новый подход к борьбе с террором
- Аналитический отчет SAS is a Leader in The Forrester Wave™: AI Decisioning Platforms, Q2 2023.
- Article Strengthen your payment fraud defenses with stronger authentication
- Технический документ What Lies Beneath
- Article Fraud detection and machine learning: What you need to know
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- Аналитический отчет Chartis RiskTech Quadrant for Trade-Based AML Solutions 2022
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- E-Book Protecting the Payments
- Технический документ Effective fraud analytics: 10 steps to detect and prevent insurance fraud
- E-Book Faces of Fraud
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- Технический документ Managing Fraud Risk in the Digital Age
- Технический документ Enforcing Tax Compliance in a Turbulent World
- Аналитический отчет Matrix: Leading Fraud & AML Machine Learning Platforms
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- Технический документ Machine Learning Use Cases in Financial Crimes
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- Article Analytics for prescription drug monitoring: How to better identify opioid abuse
- Технический документ Data and Analytics to Combat the Opioid Epidemic
- Технический документ Leveraging Analytics to Combat Digital Fraud in Financial Organizations
- Технический документ Proactive anti-financial crime strategies to improve compliance and reduce risk
- Технический документ Achieving program integrity for health care cost containment
- Технический документ Government Procurement Offices
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- Технический документ 2021 State of Insurance Fraud Technology Study
- Технический документ Detect and prevent digital banking fraud
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- Технический документ Banking in 2035: global banking survey report
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- E-Book The Future of Energy & Utilities: Transform Through Innovation
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- Customer Story Advanced analytics can detect and prevent insurance fraud before losses occur | SAS
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- Customer Story Бразилия борется со страховым мошенничеством с помощью ИИ и аналитики.
- Вебинар Современная антифрод система: что выбрать и как внедрить?
- Article Online fraud: Increased threats in a real-time world
- Article Detecting health care claims fraud
- Вебинар Найти иголку в стоге сена: разрушаем стереотипы о сложности выявления внутреннего мошенничества
- Article Доверяй, но проверяй: как бороться с внутренним мошенничеством в ритейле
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- Вебинар Основные тренды 2020 года в ПОД/ФТ
- Вебинар Новый всплеск страхового мошенничества после COVID-19
- Customer Story Thai bank safeguards customers while managing fraud detection in real time
- Аналитический отчет How Data Science Teams Leverage Machine Learning and Other Advanced Analytics
- Article Как ИИ и углубленная аналитика влияют на отрасль финансовых услуг
- Customer Story Preventing crime and ensuring compliance at 120 Nordic banks
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- Research Containing health care costs: Analytics paves the way to payment integrity
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