The fraud landscape is evolving dramatically and rapidly thanks to new tactics, new scale, and new technology –– all of which present new challenges for both companies and consumers. Add to that, the rapid adoption of generative AI is making it increasingly difficult to discern genuine content from fraudulent schemes. As businesses expand their digital presence to cater to the changing consumer behavior, the threat of online fraud looms larger than ever before. Actively working to counter these threats is Sift, an established leader in digital trust & safety. The fraud prevention company works with companies from digital disruptors to Fortune 500s, helping them dynamically prevent fraud and abuse through industry-leading technology and expertise.
In this Q&A session with Kris Nagel, CEO of Sift, we will explore the impact of generative AI on the world of fraud and discuss the steps that companies and consumers can take to protect themselves from fraud, and from falling victim to scams.
Gary Drenik: What are some of the most common types of fraud across online products and services?
Kris Nagel: With more consumer activity happening online, nearly every company has a digital presence – according to a recent Prosper Insights & Analytics survey, more than 50% of Gen-Zers, Millennials, and Gen-Xers make their purchases on smartphones. This massive transformation in consumer behavior away from brick-and-mortar stores and physical transactions means that every business has now come face-to-face with online fraud. One of the most common types of fraud experienced by businesses online is account takeovers (ATO), where fraudsters gain unauthorized access to users’ accounts with stolen login credentials. Another common type of digital threat is payment fraud involving unauthorized transactions, illegitimate chargebacks, and the use of stolen financial information. Then there are phishing scams, where fraudsters pose as legitimate organizations or people to deceive users into revealing personal or financial details; identity theft, where personal information is stolen and misused; and fake reviews and spam, aimed at deceiving users about non-existent products or generating traffic to fake websites.
But among these common fraud tactics, ATO attacks have remained one of the fastest growing and most insidious types of threats affecting both businesses and consumers. Sift’s most recent data found that account takeover attempts jumped 354% year-over-year in Q2 2023, with certain industries hit particularly hard, like a 808% spike for fintech and 485% rise for food and beverage.
Drenik: How has fraud changed due to generative AI?
Nagel: Generative AI has ushered in a new era of fraud tactics, marked by increased sophistication and adaptability. Fraudsters can now employ AI-generated content, such as text, images, and profiles, to craft sophisticated and believable scams. In fact, a recent survey by Sift found that 68% of consumers noticed an increase in the frequency of spam and scams since November 2022, around when generative AI tools began scaling in the market, and 49% say it’s become harder to identify scams in that same timeframe.
This new AI technology makes it increasingly challenging for people to distinguish genuine content from fraud. Typically, one easy way to identify scams has been to look for text that is riddled with grammatical or spelling errors. With generative AI now capable of producing more sophisticated and natural-sounding written text (or even audio), these types of scams can appear much more convincing. Fraudsters who can manipulate audio and video to sound or look like any real person, even family members or celebrities, will make it even harder for the average consumer to recognize they’re being scammed.
The scale of fraud has also expanded with automation – fraudsters can now easily execute large-scale attacks efficiently across multiple channels at once using scripted bots to do so quickly and easily. The other trend we’re seeing is the democratization of fraud. Open forums like Telegram are lowering the barrier to entry to committing fraud, and our team has seen a proliferation of fraud groups that now offer bot attacks as a service, including one that tricks consumers into providing one-time passcodes for their online accounts. And fraudsters are making these tools easily accessible and available to others for a relatively small fee.
Drenik: How can companies prevent fraud from hurting their businesses?
Nagel: Automation, AI, and the ease with which fraudsters can sell and share tactics and collaborate are trends that all businesses should be aware of and respond to. The most effective way to respond to these fraud threats is to leverage advanced analytics and AI itself, specifically machine learning. With enhanced fraud detection capabilities, companies can enable better customer experiences and proactively combat evolving fraudulent activities. It’s important to note, however, that these fraud efforts need to be scalable –– it would be nearly impossible for most businesses to build the technology and solely tools in-house to effectively fight fraud.
Sift’s Digital Trust & Safety platform is built to give companies the most holistic solution to manage a wide variety of fraud types. We pride ourselves on the level of control and transparency we offer businesses, as well as the size and diversity of our global network. We work with over 34,000 sites and apps across a wide range of industries and process over 1 trillion events annually. Our massive global data network and broad customer base means we’re able to help companies manage a wide variety of fraud types. Sift offers customers global machine learning models that are fueled by our shared intelligence data network, as well as custom models that are tailored to specific business needs, so companies can enable proactive decisions that stop fraud before it happens.
Drenik: Sift’s platform uses machine learning. Why is it important to fight AI-driven fraud with AI?
Nagel: The reality is that leveraging AI is necessary to match the speed, scale, and complexity of fraudulent activities. Our company was an early pioneer when it came to AI-powered, machine learning-enabled fraud prevention, allowing us to sift through massive amounts of data quickly and efficiently. As fraud techniques get more sophisticated, AI becomes essential in uncovering the complex patterns that traditional rule-based fraud solutions often miss. Those who rely solely on manual reviews are basically playing catch-up with tech-savvy fraudsters. Businesses that embrace comprehensive machine learning tools and strategies experience a 40% improvement in fraud detection accuracy, effectively identifying and stopping fraudsters before they can cause harm. Taking a proactive approach to preventing fraud is imperative for businesses that want to protect their revenue and stay competitive in the digital space.
Drenik: Your recent industry report makes it clear that fraud is becoming more common. How can our readers better identify and protect themselves against scams?
Nagel: It’s important to note that companies are the first line of defense against fraud. Almost a quarter of consumers (24%) surveyed by Sift believe that the business where a fraudulent purchase was made should be held responsible. Companies can do their part to make sure that they have the tools, teams, and technology in place to prevent payment fraud, account takeovers, and spam and scams on their sites. Likewise, they should educate their customers, so they know how to stay safe and identify the warning signs of fraud.
With that being said, there are steps that consumers should take to safeguard themselves online. First, be cautious when sharing personal information and financial details. Verify the authenticity of websites and emails before clicking on links or providing any sensitive information. Never provide your social security number or bank account information before verifying that an app or site is legitimate.
Second, create and use strong, unique passwords for different accounts. If you don’t, a fraudster may be able to access multiple accounts with a single password. I highly recommend using a password manager for all online accounts. They can create customs, secure passwords for each site, and remove the headache of having to keep track of them all. And whenever possible, enable multi-factor authentication to add an extra layer of security.
Lastly, foster a healthy skepticism towards online offers that seem too good to be true and be wary of unexpected requests for money or personal information. This can significantly reduce the risk of falling victim to scams.
Drenik: Thank you, Kris, for breaking down the complexities of the evolving fraud economy and sharing your insights into how technology is poised to contribute to the fraud landscape. I look forward to seeing how tech companies continue to work against fraudsters to protect their bottom line, and how these developments continue to impact consumers.
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