When card issuers first started using automated business rules software to counter debit and credit card fraud, the limits on that technology were quickly evident: Customers reported frustrating payment rejections on dream vacations or critical business trips. Visa works with its clients to improve customer experience by providing cutting-edge fraud risk tools and consulting services that make its strategies more effective. Through this approach, Visa enhances customer experience and minimizes invalid transaction declines.
The company's global network connects thousands of financial institutions with millions of merchants and cardholders every day. It has been a pioneer in cashless payments for more than 50 years. By using SAS® Analytics, Visa is supporting financial institutions to reduce fraud without upsetting customers with unnecessary payment rejections. Whenever it processes a transaction, Visa analyzes up to 500 unique variables in real time to assess the risk of that transaction. Using vast data sets, including global fraud hot spots and transactional patterns, the company can more accurately assess whether you’re buying escargot in Paris, or someone who stole your credit card is. “What that means is that if you are likely to travel we know it, and we tell your financial institution so you’re not declined at the point of sale,” says Nathan Falkenborg, Head of Visa Performance Solutions for North Asia. “We also will assist your bank in developing the right strategies for using the Visa tools and scoring systems,” he adds. Visa estimates that Big Data analytics works; state-of-the-art models and scoring systems have the potential to prevent an incremental $2 billion of fraudulent payment volume annually.
A globally recognized name, Visa facilitates electronic funds transfer through branded products that are issued by its thousands of financial institution partners. The company processed 64.9 billion transactions in 2014, and $4.7 trillion in purchases were made with a Visa card in that same year.It has the computing capability to process 56,000 transaction messages per second, which is greater than four times the actual peak transaction rate to date. Visa doesn’t just process and compute— it is continually using analytics to share strategic and operational insights with its partner financial institutions and assist them in improving performance. This business goal is supported by a robust data management system. Visa also assists its clients in improving performance by developing and delivering deep analytical insight.“We understand patterns of behavior by performing clustering and segmentation at a granular level, and we provide this insight to our financial institution partners,” says Falkenborg. “It's an effective way to help our clients communicate better and deepen their understanding of the customer.”
As an example of marketing support, Visa has assisted clients globally in identifying segments of customers that should be offered a different Visa product. "Understanding the customer lifecycle is incredibly important, and Visa provides information to clients that help them take action and offer the right product to the right customer before a value proposition becomes stale", says Falkenborg.
How Can Using In-Memory Analytics Make a Difference?
In a recent proof-of-concept, Visa used a high- performance solution from SAS that relies on in-memory computing to power statistical and machine-learning algorithms and then present the information visually. In-memory analytics reduces the need to move data and perform more model iterations, making it much faster and accurate.
Falkenborg describes the solution as like having the information memorized, versus having to get up and go to a filing cabinet to retrieve it. “In-memory analytics is just taking your brain and making it bigger. Everything is instantly accessible.”
Ultimately, solid analytics helps the company do more than just process payments. “We can deepen the client conversation and serve our clients even better with our incredible big data set and expertise in mining transaction data,” says Falkenborg. “We use our consulting and analytics capabilities to assist our clients in tackling business challenges and protect the payment ecosystem. And that’s what we do with high-performance analytics.”
“The challenge that we have, as with any company managing and using massive data sets, is how we use all necessary information to solve a business challenge—whether that is improving our fraud models, or assisting a client to more effectively communicate with its customers,” elaborates Falkenborg. “In-memory analytics enables us to be more nimble; with a 100* analytical system processing speed improvement, our data and decision scientists can iterate much faster.”
Fast and accurate predictive analytics allows Visa to better serve clients with tailored consulting services, helping them succeed in today’s fast- changing payments industry.
该公司的全球网络每天将成千上万的金融机构与数以百万级的商家和持卡人练习在一起。50多年来，它一直死无现金支付的先锋。通过使用 SAS Analytic, Visa 为金融机构减少欺诈行为提供支持，同时又不让顾客由于不必要的支付拒绝而恼怒。每当它处理一个交易时，Visa 就会实时分析 500 个不同的变量，以评估交易的风险。通过使用包括全球欺诈热点和交易模式在内的巨大数据集，该公司可以更准确地评估用户是在巴黎买了食用蜗牛，还是用户的信用卡被盗刷。“这意味着如果你在旅行，我们会知道，并且我们会告诉你的金融机构，这样你就不会在销售点被拒绝，”Nathan Falkenborg 说，他是 Visa 的北亚绩效解决方案主管。“我们也会协助你的银行制定正确的策略来使用 Visa 工具和评分系统，”他补充说。Visa 估计大数据分析起了作用，使用最先进的模型和评分系统有可能减少每年 20 亿美元的欺诈性支付额。
Visa 是一个全球认可的品牌，它通过数以千计的金融机构合作伙伴发行的品牌产品来促进电子资金的转移。该公司 2014 年处理了 649 亿笔交易，同时使用 Visa 卡消费额达到了4,7 万亿美元。创系统每秒能够处理 56000 个交易信息的计算能力，大于实际交易峰值的四倍。Visa 不只是负责处理和计算，它不断使用数据分析与金融机构合作伙伴分享战略和运营洞察，并帮助他们改善绩效。一个鲁棒的数据管理系统支撑着这个商业目标。Visa 同时通过发展和提供深度分析洞察帮助其客户改善绩效。“我们通过在轻度层面上进行聚类和细分来理解行为模式，并且为我们的金融机构合作 伙伴提供这种洞察，”Flkenborgs 说。“这是帮助我们的客户和顾客更好地交流，并且深入理解顾客 向的有效途径。”