Fraud remains a top concern for financial institutions and merchants alike, with both being subject to rising losses in the past several years. Card not present (CNP) losses due to fraud have spiked in response to the EMV liability shift of October 2015. But while the fight against fraud seems daunting to even the most experienced institution or merchant, there is room for optimism: it doesn’t have to be won alone.
Global payments leader Worldpay is always on the lookout to mitigate fraud and the corresponding losses for all of its partners and customers. The company supports thousands of financial institutions and merchants with comprehensive fraud fighting tools and technology including those described below.
One of Worldpay’s newest cardholder authentication solutions, 3D Secure uses risk-based authentication to reduce friction and help minimize CNP losses. Cardholders don’t need a password, so they are usually not even aware of the authentication process. This results in a more streamlined checkout experience for cardholders, and more secure transactions for merchants and institutions.
Motion Code technology
Motion Code is to online and mobile transactions what EMV is to instore transactions— an extra layer of security. Motion Code cards feature a dynamic CVV/CVC that changes at regular intervals, so card data is useless if stolen. Since most CNP transactions require CVV, Motion Code cards are especially attractive for consumers that make a lot of online purchases.
Additionally, the Worldpay reporting dashboard makes it possible for financial institutions to see which cardholders are high CNP consumers, so they can target the Motion Code offering to those specific segments. This type of targeted marketing has yielded very positive results for a number of Worldpay’s customers.
Driven by the desire to focus on machine learning to fight fraud, Worldpay was one of the first US based payment processors to migrate to the SAS Enterprise Fraud Manager fraud technology platform. SAS’s machine learning capabilities coupled with Worldpay’s extensive data set and experienced fraud teams has allowed Worldpay to become even more effective at fighting fraud.
Machine learning is important for fraud development because it offers the capacity to process data faster than humans can, essentially learning on the fly. For example, machine learning makes it possible to detect the likelihood of a fraudulent transaction in real time, gathering information to determine new fraud trends as they materialize.
Utilizing machine learning and artificial intelligence allows Worldpay to be more proactive than reactive in the fight against fraud, with solutions that help reduce fraud losses to numbers well below the US average. By relying on machine learning to detect the bulk of the fraud, Worldpay also frees up its fraud teams to focus on emerging trends and product improvement.
In addition to the aforementioned solutions, Worldpay invests heavily in data research technology. This makes it possible to identify a breached merchant based on fraudulent chargebacks reported by cardholders.
Consider this example: Worldpay determined that fraud was trending away from a small number of very large, high profile breaches, to a very large number of smaller, lower profile breaches. The result was a rise in local and regional breaches, instead of national occurrences.
Worldpay has determined the three most important metrics for financial institutions to track: gross fraud loss, net fraud loss, and false positives.
Gross fraud loss is the loss due to the fraud that occurs across a financial institution’s entire portfolio. It represents the fraud that cardholders report, whether it’s recovered through the chargeback process or not.
Net fraud loss is the difference between gross fraud loss and the amount that a financial institution has recovered through the chargeback process. This includes anything an institution has had to write off as a loss, so it directly affects an institution’s profitability.
Finally, false positives refers to the number of times a good cardholder or transaction is declined at the point of sale because it’s falsely determined to be fraud. A high number of false positives has a negative impact on both an institution’s profitability and their cardholders’ experience.
Nobody likes to have their transaction declined at the point of sale. So ultimately, the goal is to strike an effective balance between managing fraud risk and offering a streamlined and friendly cardholder experience.
As for the future, Worldpay is not slowing down in its evolution of tools and technology to combat fraud. The company’s reach and scope gives it the ability to detect fraud trends in unique ways.
For example, whereas credit card fraud and debit card fraud are usually managed by different groups, at Worldpay, both credit and debit are centralized within one group.
This is an advantage because a fraud trend that affects debit cards first is likely going to migrate to credit cards at some point. With a view into both debit and credit portfolios, Worldpay can detect these trends and roll out solutions across both platforms.
There’s no certainty in the future of fraud— except that it will still exist. By leaning on the expertise of a company with the global reach and expertise like Worldpay, both financial institutions and merchants can rise above the tide of the most potentially damaging fraud scenarios.
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