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Google, Twitter, Lime, Getaround, Spotify… What do these businesses have in common? All of them are hiring in Trust & Safety.
Tech is experiencing a revolution in its approach to risk and revenue. The conventional approach to fraud-fighting is to invest almost exclusively in fraud and risk teams that operate independently from product teams, finance, marketing, and so on. But innovators across all verticals are switching from this legacy approach to a Digital Trust & Safety approach: integrating risk and revenue decisions, which are guided by machine learning technology and cross-functional collaboration.
Going from a legacy approach to Digital Trust & Safety involves a fundamental change in mindset, processes, and technology. So why are companies making such a seemingly invasive change? Here are three key reasons.
Companies that invest in Trust & Safety teams understand that trust underpins their entire business model. For many businesses, their app or platform connects strangers who provide a service or even enter a customer’s home. If customers don’t trust the company, they’re not letting anybody through their door.
On-demand carpooling service Scoop describes it this way: “Building a community of carpoolers relies on trust. From working with product and eng teams, to partnering with sales, we take a systematic and human approach to our trust and safety work.” Scoop customers trust that their carpool will get them to work on time; Scoop trusts that its customers will use the app safely and respectfully. When customers’ safety and comfort are on the line, Scoop can’t afford to release a product first and worry about fraud later. Fraud and product teams must collaborate throughout the product lifecycle.
Scoop isn’t the only company using a Digital Trust & Safety approach to foster trust. Smart-mobility provider Lime has a similar model. Their Digital Trust & Safety professionals are “responsible for building and scaling a global organization tasked with enhancing trust within the Lime community and ensuring the safety of Lime’s users.” Lime calls out an important aspect of the Digital Trust & Safety approach. Unlike the legacy model, Digital Trust & Safety scales with your business. It’s the only approach that empowers businesses to explore new revenue opportunities without worrying about risk.
Cross-functional collaboration is at the heart of Digital Trust & Safety. Risk and fraud teams work with product, marketing, finance, operations, and others to set goals that encompass risk mitigation and revenue growth. Trust & safety teams are stakeholders in growth and product decisions: while legacy fraud prevention supports launches, Digital Trust & Safety enables launches.
Twitter, for example, looks for Trust & Safety professionals who can “work effectively with people at all levels in an organization.” Their Trust & Safety managers “work across three sub teams to scope out and track projects.” Twitter’s forward-thinking approach to fraud-fighting has enabled the company to grow despite challenges such as content fraud and account takeover.
Similarly, peer-to-peer carsharing service Getaround relies on its Trust & Safety team to “create positive customer experiences” by fostering conversations between “Customer Happiness, Claims, and Product/Engineering.” These conversations help companies like Getaround understand how fraud is impacting the company’s bottom line, how to work with customer service to see how user complaints are tied to fraud, and much more.
Fraudsters have started incorporating sophisticated tools into their strategies, so rules-based methods for fighting fraud are coming up short. In particular, bots and machine learning can ramp up the volume of attacks against your business nearly instantaneously, and rules simply cannot compete.
By contrast, the Digital Trust & Safety approach is underpinned by machine learning technology that adapts to fraudsters’ behavior. The legacy, rules-based approach tries to apply a one-size-fits-all model to your customers, often forcing even honest customers to prove their identity before making a transaction. But Digital Trust & Safety allows businesses to customize user experiences based on a customer’s history and behavior. Fraudsters experience friction; good users don’t.
Companies like Google are turning to machine learning to fight new and surprising kinds of fraud. They’re hiring Trust & Safety professionals to make sure this technology is baked into their processes from the ground up. In order to “gain and retain [their users’] trust,” Google hires Trust & Safety teams with “technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse.” Like other industry giants, Google relies on machine learning — and risk teams with a robust technical vocabulary and experience — to stay ahead of the game.
Is your business ready to make the jump to Digital Trust & Safety? Download our ebook to get started!
Roxanna "Evan" Ramzipoor was a Content Marketing Manager at Sift.
Stop fraud, break down data silos, and lower friction with Sift.