SAS IS A LEADER
The Forrester Wave™: Enterprise Fraud Management, Q3 2021
SAS is the only vendor in the evaluation to earn a 5 out of 5 score in the model explainability and governance criterion.
Managing supervised and unsupervised machine learning risk scoring algorithms is intuitive and offers robust model explainability. Visual tools allow for creating and managing entity (customer) segments for risk scoring models. In investigators’ queue management, case routing prioritization is flexible and configurable.
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Технический документ
Payments Without BordersMitigating fraud risks in cashless payments by holistically understanding your customers across all channels.
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Технический документ
Field Experience in Embedded AnalyticsInternational Institute for Analytics summarizes key questions and answers about financial fraud in the digital age.
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Article
Мобильные платежи, смурфы и новые угрозыИнновации охватили весь мир – даже где-нибудь в глухой кенийской деревне мобильный телефон служит местному жителю виртуальным кошельком. Но почему эта новая технология может стать потенциальным препятствием в борьбе с отмыванием доходов?
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Customer Story
Fast analytical defenseDeutsche Kreditbank AG combats fraud and money laundering with SAS.
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E-Book
Fight money laundering with these 5 game changers from SASEffectively battling dynamic financial crime threats requires new capabilities for AML defense – such as artificial intelligence, machine learning, intelligent automation and advanced visualization.
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Технический документ
Detect and prevent digital banking fraudDiscover how banks can fight identity-based fraud attacks using proven analytical methods to detect the fraudsters while expediting service for legitimate customers.
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Технический документ
Enhancing AML Efficiency and EffectivenessCelent discusses how banks are adopting artificial intelligence, machine learning and robotic process automation, including the benefits and key lessons learned. The paper explores considerations for AI adoption and future benefits for the AML industry.
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Технический документ
Fighting Money Laundering with Intelligent AutomationThe world of money laundering and other financial crimes is changing rapidly. This International Institute for Analytics research brief shows how fraudsters and money launderers keep getting more sophisticated.
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Технический документ
How AI and Machine Learning Are Redefining Anti-Money LaunderingMachine learning can play a big role in the defense against money laundering, either to automate tasks that formerly required human intervention, such as managing the data to train models, or detect more financial crimes risk that rules and more basic analytic techniques might miss.
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Технический документ
Managing Fraud Risk in the Digital Age The rise of mobile and online transactions introduces new fraud risks. Retailers and payment processors must adapt their anti-fraud defenses, augmenting them with stronger, analytics-driven authentication, proactive detection and mitigation tools.
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Технический документ
Rethinking customer due diligenceHelp evaluate your organization's CDD processes and technology relative to current industry risks and regulatory requirements.
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Технический документ
The Escalation of Digital FraudThis Javelin Research report is based on 120 independent interviews of payment and security executives in 20 countries and delivers a clear picture of how digital fraud has changed the global operating environment for financial institutions.
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Технический документ
What is next-generation AML? The fight against financial crime fortified with robotics, semantic analysis and artificial intelligence
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Customer Story
Preventing crime and ensuring compliance at 120 Nordic banksSDC enables small and medium financial institutions in four Nordic countries to stay compliant.
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Article
Личные данные – лучший подарок мошенникам на зимние праздникиВ период праздников у нас слишком много хлопот и безумный ритм жизни. Мошенники пользуются нашим положением, поэтому в это время как никогда важно защитить себя от кражи личных данных.
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Технический документ
Balancing Fraud Detection and the Customer Experience Customers of a digital business create an intricate online footprint as they transact online. Businesses that capture and truly understand a complete identity based on online and offline attributes can seamlessly authenticate good customers and reliably spot the fraudulent or hijacked identities – in real time.
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Технический документ
Using Digital Identity To Unleash Organizational DataCustomer experience focuses on speed and ease of access, lowering friction where possible. However, this approach has the potential to open up an organization to fraudulent attacks.
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Технический документ
Advanced Analytics For Dissolving Data SilosThe growing need for data storage has heightened the proliferation of data silos. Readers will learn how organizations can apply machine learning and artificial intelligence to battle fraud, confirm customer identities and build data systems to avoid potential silos.
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Технический документ
Developing Trust: Uniting Fraud and Consumer Experience Through Digital IdentityFraud and CX used to have a contentious relationship. But with strong foundational digital identity infrastructure, fraud efforts can provide greater insight into the user to enable CX teams to build improved services and offerings.