欺诈、反洗钱和安全情报资源
了解 SAS 如何帮助您阻止不良行为者。
聚焦：分析师亮点
投资打击欺诈？了解 SAS 为何是领导者。
SAS是2022年基于贸易的反洗钱解决方案Chartis RiskTech Quadrant的类别领导者
"SAS解决方案以结合数据提取，数据融合，文档和事务分析，KYC / AML分析和工作流程管理而闻名。特别是，贸易文件分析的集成 - 从图像中提取文本并执行各种贸易欺诈和AML风险指标检查 - 脱颖而出。
SAS在Matrix：领先的欺诈和AML机器学习平台中被评为同类最佳
SAS提供了一个有凝聚力、开放、弹性和可扩展的平台，支持高性能的高级分析、机器学习模型开发和部署，以及跨各种欺诈和AML用例的实时决策。
— Trace Fooshée，战略顾问，Charles Subrt，Datos Insights 欺诈与反洗钱实践总监
SAS是Forrester浪潮™的领导者：企业欺诈管理，2021年第三季度
自2013年报告发布以来，SAS是唯一一家保持其领导者地位的供应商，也是2021年评估中唯一一家在模型可解释性和治理标准中获得5分（满分5分）的供应商。
SAS 是 RiskTech100 五强公司和金融犯罪 – 基于贸易的反洗钱类别获奖者
SAS连续16年被评为RiskTech100五大领导者，这是无与伦比的，反映了深厚的行业专业知识和解决方案，帮助客户适应不断变化的风险。
— Sidhartha Dash，Chartis 研究总监
SAS 是 2021 年 Chartis RiskTech Quadrant for Enterprise Fraud Solutions 的品类领导者
"SAS提供的架构最适合组织正在处理的欺诈类型 - 例如实时支付和/或卡欺诈，应用程序欺诈和存款监控。
— Phil Mackenzie，Chartis 高级研究专家
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白皮书
Building a foundation for innovation: Five steps to keep your AML program efficient and effectiveWhite paper
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白皮书
Explainable Artificial Intelligence for Anti-Money LaunderingAn automated AML system should catch suspicious activity and be able to explain why it did so in a way that’s satisfactory to regulators. While machine learning techniques promise significant innovations for anti-money laundering efforts, they’re contained in "black boxes." This is hard to justify to regulators, and many financial institutions hesitate to invest in the technology for their AML programs. This paper takes a deep dive into how you can use explainable artificial intelligence (XAI) techniques to overcome this obstacle.
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白皮书
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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电子书
Public procurement integrity at riskFraud, waste and abuse (FWA) take many forms, from duplicate invoices, ghost vendors and fake invoices to overbilling billing for goods. This e-book explores the procure-to-pay lifecycle, obstacles to spotting FWA, how to strengthen government procurement, hat's possible in the real world and how a data and AI-driven approach leads to greater productivity.
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电子书
5 Steps to a Unified Enterprise Customer Decisioning StrategyIn an era of unprecedented technology-driven disruption, banks are facing a dual challenge: Meeting rising customer expectations while navigating increasingly complex regulatory demands.
To remain competitive, banks must not only innovate but also streamline operations and foster greater collaboration across departments, breaking down traditional silos and working toward innovation.
How can banks simplify their operations, future-proof their services, and drive growth? Enterprise customer decisioning is the answer. This ebook describes five important steps to making better decisions faster with enterprise customer decisioning.
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电子书
Your journey to a GenAI future: A strategic path to success in bankingAs generative AI (GenAI) stands on the brink of revolutionizing how the world does business, the banking industry is starting to capitalize on it. Data is at the center of everything in banking. GenAI offers the potential to generate more value from this data by enabling new efficiencies and unlocking untapped value – and many banks are already reaping the benefits. From enhancing the customer experience to thoroughly transforming fraud detection, risk and compliance management and more, banks are beginning to realize the productivity and efficiency gains GenAI offers. The pressing questions for banking leaders now are how and where they can use GenAI most effectively going forward, and how to ensure it is fully adopted and scaled.
Our research findings are based on a new survey of 1,600 organizations across the globe from a wide range of industries. To better understand the banking industry perspective on GenAI, we examined responses from 243 senior leaders in the banking sector who are responsible for making decisions on GenAI strategy or data analytics.
This report reveals:
● How banks are implementing GenAI compared to other sectors.
● Which areas banks are seeing benefits in, and where banks feel less confident.
● How the banking sector’s investment in GenAI stacks up against other sectors, and where it is being spent.
● How banking firms can proactively prepare for the challenges of implementing GenAI to ensure a strong ROI.
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电子书
On the Road to Accelerating Claims AutomationMore than ever, insurance companies need to provide customers with seamless interactions that save them time, minimize hassle, and make them feel seen, understood, and cared for. Many are also exploring the use of AI for claims prevention – for example, by creating new risk mitigation services. All of this requires investment in digital technologies that work together to enable intuitive, Amazon-like customer experiences. This ebook explores how insurers can make the leap to digitally transformed, intelligent claims processes that customers love and increase operational efficiency and reduce costs.
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客户案例
Revolutionizing fraud detection at TechcombankAward-winning Vietnamese bank slashes time needed for fraud detection to mere seconds using a SAS enterprise fraud solution.
