It’s no secret that the past year has fundamentally changed how businesses operate. Facing a global health crisis, companies and consumers alike had to adjust and adapt to the accelerated shift to digital and the identity and fraud risk it brought.
We saw that shift to digital reflected in recent findings from Experian’s Global ID & Fraud Report, which found that the percentage of consumers over age 40 who reported using online banking increased from 33% pre-Covid to 38% in January 2021. Additionally, at the height of the COVID-19 pandemic, 64% of global consumers said they used mobile wallets, an over 10% increase from before the pandemic.
But as more consumers shifted to digital in 2020, so did fraudsters. According to the 2021 Identity Fraud Study by Javelin Strategy & Research, identity fraud cost Americans a total of about $56 billion last year, with about 49 million consumers falling victim. And during a year when leveraging government assistance programs were critical for many consumers, even they were not safe from fraud. Unemployment fraud in the U.S. reached dramatic levels during the pandemic, with the Labor Department inspector general’s office estimating more than $63 billion has been paid out improperly through fraud or errors since March 2020.
As businesses continue to navigate the current economic environment, it’s critical they also strategize for the future to position themselves for success once the environment improves. This means implementing robust fraud prevention strategies and tools that accurately separate fraud types to treat them correctly and address risk. The first step in this process is building a solid understanding of the different types of fraud so businesses can apply the correct solutions for the most effective response.
Identifying and Understanding the Types of Fraud
It is critical that businesses accurately identify and address individual fraud types, especially now that so much of everyday life has become digital. In general, there are three main types of fraud they should know: first-party fraud, third-party fraud, and synthetic identity fraud.
First-party fraud occurs when an individual uses their own identity to commit fraud. In these cases, an individual promises future payments in exchange for goods or services upfront but plans not to repay. Often, the individual will have a solid period of building a favorable credit profile and then take advantage of their positive standing to make a substantial financial commitment, such as taking out a large loan with no intention of paying it back. First-party fraud can be challenging to address because the person who owns the identity also commits the fraudulent activity. This means you cannot rely on the identity owner to confirm if the activity is legitimate or not because they are also the perpetrator.
Third-party fraud occurs when an outside entity impersonates or takes control of another individual’s identity. This is commonly referred to as identity theft. This type of fraud has been primarily fueled by the rapid digital transformation of the past year. And with the increasing amount of personally identifiable information available online, fraudsters can commit identity theft easier than ever before. However, third-party fraud tends to be easier to address, as the victim usually is willing to resolve the issue by accurately confirming whether or not the activity was fraudulent.
Lastly, synthetic identity fraud is one of the fastest-growing types of fraud businesses should be prepared to tackle. To create synthetic identities, fraudsters usually use a combination of real and fake information, such as names and social security numbers, to create “Frankenstein IDs,” which are then used to obtain credit. For synthetic identity fraud, there is no identity theft victim like there is in other types of fraud, so there’s no one person to collect losses against, which makes the impact much larger to organizations.
Leveraging Data and Analytics to Streamline Fraud Solutions
It is commonly believed that a multi-layered solution is the best approach to fraud tools, but only when the approach is utilized correctly. Many times, fraud solutions are built on top of one another, creating a multi-layered approach that is too broad, too interdependent and inefficient. Because of this, accuracy and efficiency are sacrificed in favor of casting a wider net. This way of addressing fraud often requires manual review to determine the type of fraud and the necessary next steps, significantly slowing down the response time.
Now more than ever, businesses need a solution that leverages highly predictive data and analytics that detect and distinguish types of fraud and identify the appropriate next steps to take action for each type. Solutions that effectively verify identities with the power of industry-leading data sources and advanced analytics can help distinguish first-party, third-party, and synthetic identity fraud risk independently to determine the next best action to take to address those threats.
Fraud prevention tools can help protect the entire customer journey against fraud while creating a seamless experience for true customers. By having an orderly, organized way to categorize risk and different paths for addressing each one, businesses can improve fraud detection while maximizing efficiency and eliminating redundancy across fraud prevention teams, ultimately reducing fraud losses.
As fraudsters continue to adapt and evolve with the new environment, businesses must do the same to combat them. Leveraging data and advanced analytics is critical for predicting different types of fraud and the next best action to address it. In doing so, businesses can stay agile in changing economic conditions, detect fraud more efficiently, and protect their customers and themselves from fraud risk.