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January 6, 2021 - Claire Zhou

Application Fraud: Key Trends in 2021 and the Need for Multi-Layered Protection

For many financial institutions (FIs) using the “If it’s not broken, don’t fix it” approach to fraud, 2020 is the year it finally broke. With application fraud on the rise, it’s important for banks to understand that technology is both the catalyst for global fraud and an effective tool to help prevent it in the first place. 

FIs have been fairly quick to evolve their technology to cater to the front-end customer experience. However, out of the nearly $300 billion in technology spend in 2020 alone, very little of this has gone to improving back-end processes and manual fraud detection. 

Here are some of the most alarming trends in application fraud that underscore the need for better fraud prevention in 2021 and beyond.

First-Party Fraud Is Increasing in Size and Scope

First-party fraud is defined as any fraud committed against an FI by one of its own customers. According to a recent Aite Group report, first-party fraud has been on the rise since 2017 but has significantly accelerated in 2020 as a result of the pandemic. 

As economic conditions have slumped around the world, millions of workers are seeking alternative ways to improve their financial condition. Many may be more likely to serve as a money mule and open an account on behalf of a fraudster to illegally move money. 

These accounts are becoming easier to create with the help of synthetic identities. Many fraudsters are creating and nurturing synthetic identities to develop credit profiles, making them extremely difficult to detect.

illustration of secure documents

Personally Identifiable Information Is Cheap and Available

Personally identifiable information (PII) is the foundation of all identity fraud. Though the price for PII has remained relatively stable in the last few years, it also remains inexpensive and easy to obtain. Aite Group notes the going rate is $4-$10 per identity in the United States. Many fraud experts attribute this low cost to abundance: as more data breaches occur, more personal details become compromised. 

PII can be used to create synthetic identities and/or bypass traditional fraud detection tools, since some or all of the identifying information is valid.

Credit Card and DDA Application Fraud Span a Diverse Range

Widespread lockdowns, high unemployment, and sustained economic uncertainty have created disruptions to social and behavioral patterns, making it harder to separate fraud from honest transactions. The proliferation of fraud activities further complicates matters, where fraud related to credit cards and demand deposit accounts (DDAs) can take many forms.

Aite Group notes that DDA fraud activities include money mules, unemployment fraud, and deposit fraud, while synthetic identity incubation, first-party fraud, bust-out fraud, and credit repair schemes make up the majority of credit card fraud losses. 

The Need for a Multi-Layered Approach to Application Fraud

Each of these fraud trends and activities emits unique signals that require specialized fraud prevention tools to detect. Taking a one-size-fits-all approach, however, isn’t likely to result in high accuracy since each type of fraud can vary in size, scope, and signals.

DataVisor’s comprehensive platform takes a multi-layered approach to fraud by analyzing billions of data points and user activities in real-time at scale, giving FIs the power to lower their false positive rate and prevent known and unknown attacks before they can be carried out.

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about Claire Zhou
Claire is a Senior Product Marketing Manager at DataVisor with over 5 years of marketing experience in security and fin-tech. She is passionate about empowering enterprise customers with AI-based solutions. Her expertise spans data analytics, cybersecurity, and fraud prevention. Claire has an MBA from UCLA.
about Claire Zhou
Claire is a Senior Product Marketing Manager at DataVisor with over 5 years of marketing experience in security and fin-tech. She is passionate about empowering enterprise customers with AI-based solutions. Her expertise spans data analytics, cybersecurity, and fraud prevention. Claire has an MBA from UCLA.