Page 36 - Security Today, September 2020

Democratizing Access Leveraging the power of shared intelligence
By Damon Madden
The COVID-19 pandemic has put financial institutions undermorepressuretostay on top of fraudulent activ- ity—as opportunists are looking for any weakness in a system that can be exploited. Moreover, as consumers turn to eCommerce and digital payments while social distancing, there’s no avoiding the increased levels of associated risk for financial institutions.
As organizations prepare for more commerce to be conducted online during the pandemic, sometimes through quickly transplanted or repositioned business mod- els, payment fraud will proliferate. In fact, research from ACI Worldwide has revealed that merchants have experienced significant increases in COVID-19 related phishing activities and friendly fraud, with non- fraud chargebacks up 25 percent in May this year. While overall fraud attempt rates fell from March (5.3%) to May (3.4%), the research shows that the average ticket price
of attempted fraud increased by $18 year- over-year.Thisindicatesthatfraudstersare gettingmorebullishandconfidentintheir pandemic-related methods.
For financial institutions, getting the balance right between identifying genu- ine payments and creating a frictionless customer experience is key. And, machine learning has emerged as an essential tool for detecting fraudulent payments among the many thousands or millions of genu- ine ones made every day.
THE DOUBLE-EDGED SWORD OF DIGITAL PAYMENTS
Digital payments offer many benefits including better, faster experiences for cus- tomers. However, when payments happen in real-time, the window for fraud detection is reduced to milliseconds and the likelihood of recovering fraudulent payments is far lower than with traditional methods. Essentially, as payments get faster so too does fraud — and when the money is gone, it’s gone.
Further, as the volume and vari- ety of digital payments surges so too does the volume and variety of data generated by those payments. Geo- location information, behavioral clues and biometrics provide a wealth of in- telligence for financial institutions — but only if they can make sense of the del- uge.
As such, machine learning plays a key role enabling financial institutions to oper- ate at the speed and scale required to au- thenticate genuine payments, catch fraud as it happens, reduce the volume of false positives, and improve the time it takes to react when they do occur. With machine learning, financial institutions can flag ac- tivity that deviates from the norm but isn’t necessarily suspicious. For example, when a customer logs in using a different device, it’s less likely to be unauthorized access and more likely that they’ve upgraded their phone – nevertheless, it needs verifying.
To avoid overwhelming already
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MACHINE LEARNING
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