The impact of COVID-19 has been felt across the full breadth of the global economy, causing an estimated 3% contraction in the global economy, according to the IMF. While industries such as travel, hospitality, and higher education will face a fundamentally different landscape in a post-COVID environment, the digital identity sector has seen acceleration for trends that were beginning to take shape in 2019.
While she’s not necessarily my favorite performing artist, Taylor Swift’s dominance of the music industry over the past decade is indisputable. She has managed to stay on top of the charts with a deft reading of the cultural tradewinds. The recent midnight surprise “drop” of her latest album Folklore is indicative of the increasing importance of “virality” to the global economy in both the pre- and post-COVID eras.
As consumer attention spans decrease amid a sea of devices, websites, and streaming platforms vying for eyeballs, viral marketing has become a critical tool for reaching mass audiences. The use of algorithms to curate user feeds across platforms underscores the importance of achieving a critical audience mass rapidly, with the velocity of trending content increasing once it starts to build momentum.
The criticality of achieving a rapid audience for your content remains true for all disseminators, regardless of their intention. From brands to nation-states and content marketing managers to cybercriminals, rapid propagation is key to the success of your messages.
This ever-increasing dependence on audience scale for the generation of revenue is, in many ways, a double-edged sword. Reducing user friction is critical to driving user engagement and opens the door for multiple types of fraud. How do we know the audience that our content is reaching is authentic? OWI’s core thesis illustrates this directly. It places digital identity at the intersection of marketing, payments & the data economy, and cybersecurity.
When eyeballs equal dollars, there is direct economic motivation to generate fake user accounts and drive inauthentic traffic from real users’ accounts. According to the latest industry data released by White Ops, fraud attempts account for an estimated 20-35% of all online ad impressions generated in a given year. Monetizing this traffic can be accomplished in several ways. First, indirectly, unscrupulous website owners spin up bot networks to generate false traffic across their websites and create profitable false impressions paid for by advertisers. Another is by vendors who directly operate bot networks and sell the false impressions themselves. One such vendor, Devumi, is alleged to have had over 200,000 customers, including reality television stars, professional athletes, comedians, TED speakers, pastors, and models, paying for faked social media impressions and “likes.”
To combat increasingly sophisticated vendor solutions dedicated to identifying and neutralizing false advertising and impressions, fraudsters’ methods for creating and utilizing fraudulent accounts continue to evolve. Unfortunately, these methods are also an ideal conduit for perpetuating a full gamut of digital identity fraud from the creation of synthetic identities to money laundering and account takeover.
Today there is no “silver bullet” to defend against the threats mentioned above. But making any progress towards the adoption of digital identity standards will help destroy the economic model that underpins the fraud ecosystem. For too long, the dominant thinking across industry verticals has remained that user friction and high levels of identity assurance must remain mutually exclusive. For social media platforms such as Facebook, Twitter, and TikTok, the insertion of steps within the account creation process to ensure that a valid physical person is involved will lead to higher user drop-off rates and, therefore, slower platform growth. This no longer has to be the case.
In the near-term, mobile telecommunications data, user-entity and behavioral analytics, and networked fraud detection platforms offer product managers the tools to pick up on risk signals. This can ultimately identify fraudulent user accounts and provides a high degree of accuracy and no added user friction. While no solution can, or should, claim to be 100% accurate, these technologies continue to increase the time, cost, and effort associated with fraudulent accounts.
This escalation of the cost of creating fraudulent accounts is critical. This is because shifting the fraud equation is the fundamental equation to keep in mind. Eliminating all fraudulent accounts is an admirable goal, but perhaps unattainable. Making it more expensive to create a fraudulent account than the profit generated by a fraudulent account is both achievable. It will go the farthest towards meeting the goals of trust and growth teams alike.
This equation holds across the broader digital identity landscape and remains applicable across payments, cybersecurity, and marketing. Fraudsters have budgets and investors the same as legitimate enterprises. Working to make the cost of successfully perpetuating fraud high enough to make large-scale operations, unsustainable offers the best chance of mitigating risks. The challenge is now, how can businesses do that without fundamentally compromising the experience of your authentic users and compromising growth?