Digital Banking

Scotiabank: Slow But Steady Wins The AI Fraud Race

The fact that fraud is on the rise is not new, nor is it surprising that banks are turning to artificial intelligence (AI) and machine learning to fight back. Banks are, however, revamping their approaches to these technologies on how they may be applied outside of their typical use cases, fending off cybercriminals who have a growing number of opportunities to access online banking platforms and customer data.

In the latest Digital Banking Tracker, PYMNTS looks at how banks are currently approaching their use of AI and machine learning in fraud protection and technology innovation.

Around The Digital Banking World

Competing in today’s digital banking space is not as simple as opening a fully digital bank, as U.K. institution Barclays found. The bank has shuttered plans to open such a service in the U.S., stating that the project was proving too costly. Barclays will instead keep up its co-branded card efforts in the country at this time, but may revisit the project in the future.

Fully digital banks themselves have their own challenges to meet, such as keeping customers satisfied in the event of a potential breach without the resources of a legacy bank. Digital bank Chime suffered a service outage that left customers unable to access their accounts, leading to frustration expressed online by those customers. This is the third such outage the bank has suffered since July.

Financial institutions (FIs) are also fending off fraud from false banking apps, a method that has seen a 63 percent rise since the last six months of 2018. Banks need to be on the lookout for account takeover fraud as well, which is becoming one of the larger challenges for the financial industry in the fight against cybercriminals.

For more on these and other stories, visit the Tracker’s News and Trends section.

How Scotiabank Manages Talent And Fraud Protection

Protecting customer data takes more than FIs having access to the latest technologies. Fraud strategies need to be mobile and innovative, which takes an innovative team. However, recruiting expert talent can be competitive, said Rania Llewellyn, executive vice president of global business payments for Scotiabank.

To learn more about Scotiabank’s three-pronged approach to the challenges of AI innovation and talent management, visit the Tracker’s feature story.

How AI And Machine Learning Data Models Can Help Banks Visualize Fraud

Banks are experimenting with a host of new technologies designed to stop cybercriminals from accessing online banking data. One of the more intriguing ways FIs are now making use of both AI and machine learning is by applying the technologies to data modeling, which provides analysts with a more detailed and understandable visualization of patterns and trends. This can help them isolate illegitimate customers from legitimate customers by providing a closer look at their behavior.

To learn more about how data visualization can help banks better protect against fraudsters, visit the Tracker’s Deep Dive.

About The Tracker

The Digital Banking Tracker, a Feedzai collaboration, brings the latest news, research and expert commentary from the FinTech and consumer banking space. It also includes a provider directory featuring the rankings of more than 250 companies serving or powering the digital banking sector.

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Our data and analytics team has developed a number of creative methodologies and frameworks that measure and benchmark the innovation that’s reshaping the payments and commerce ecosystem. In the December 2019 Mobile Card App Adoption Study, PYMNTS surveyed 2,000 U.S. consumers for a reveal of the four most compelling features apps must have to engage users and drive greater adoption.

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