As financial institutions shift their focus from business continuity back to growth in a post-pandemic world, they must firm up defenses even further in order to keep fraudsters at bay.
According to the 2021 Identity Fraud Study by Javelin Strategy & Research report, identity fraud cost U.S residents a total of about $56 billion in 2020 alone. And recent research from TransUnion found that financial services fraudsters have ramped up their efforts in 2021. When comparing the last four months of 2020 to the first four months of 2021, the percentage of suspected digital fraud attempts increased 109% in the U.S and 149% across the globe.
The Reasons Behind the Rise in Fraud
What’s behind the surge in fraudulent activity? Changing consumer behavior resulting from pandemic lockdowns, for one. Since the start of the pandemic, 93 million people in the U.S. have signed up for online services that were once carried out in person, and 75% of them plan to continue using these services moving forward. The move to online and mobile commerce by consumers with less digital experience, such as senior citizens, has provided an open door to fraudsters, and they’re wasting no time in seizing the opportunity. Additionally, consumer stress and fear can lead to riskier transaction behaviors for all consumers, which creates opportunities for malware infection on devices and theft of personal identification information.
Remote work has also played a role. It impacted employee behaviors and exposed gaps in processes and systems that created security risks. Many organizations were not prepared for this shift and may not have had protected technology resources, such as a virtual private network (VPN), that can encrypt the information going through the Internet.
New Approaches to Fighting Fraud
Fortunately, a massive transformation is occurring across digital and mobile channels in how financial services organizations engage with their customers and use artificial intelligence. They are accelerating digital transformation initiatives to improve the efficiency and effectiveness of existing anti-fraud teams, as well as implementing new ways to fight off fraudsters.
American Express, for example, has employed a machine learning model that uses various inputs which are pattern-matched against evolving algorithms in real time to flag transactions that have a high probability of being fraudulent. According to estimates by the company, the fraud detection machine learning approach has identified $2 million in potential annual incremental fraud incidents. Mastercard leverages Dell EMC to fight fraud, using their data analytics and artificial intelligence. Its fraud detection machine learning system looks for established fraud patterns to identify emerging fraud patterns in real time.
With more sensitive personal data online as a result of widespread consumer adoption of all things digital and mobile, fraudsters have the power to perpetrate more digital fraud. As a result, financial services organizations are doubling down on their efforts to stay one step ahead. According to a new report offered by Research Dive, the global fraud detection & prevention market is predicted to generate a revenue of $145.7 billion by 2026, from a market size of $18.8 billion in 2018.
How Fraudsters are Fighting Back
Fraudsters, however, are also leveraging artificial intelligence to break traditional security solutions including passwords, captcha, or even biometric authentication with the use of deepfake technology. Deepfakes are videos or images created using AI-powered software to show people saying and doing things that they didn’t say or do.
Synthetic identity fraud is a sophisticated form of online fraud that is also hard to identify. Fraudsters create identities using information from multiple people to create a “person” who doesn’t exist, then use this identity to apply for credit card accounts or complete other transactions that help build a credit score for non-existent customers.
Infrastructure Requirements for Fighting Fraud
A best-in-class fraud fighting strategy that leverages artificial intelligence and other innovative technologies requires an equally best-in-class infrastructure to support it. We wrote in a previous blog post about how these types of applications use more power per rack than average applications because they require much higher processor utilization and rely on faster-running processors. This also increases the demand for cooling, which further increases the need for power.
Panduit provides financial services organizations with sustainability-focused infrastructures that are also robust, agile and can scale on demand.
Visit our website to learn more about our solutions for financial institutions and download our e-book to find out the three key trends driving financial services IT transformation.
