Marketplace Risk NYC Recap: How Uber Is Building Trust Globally in the Age of AI

‍In every digital marketplace, trust and safety are fundamental. But at Uber, the stakes are unusually immediate. A digital interaction quickly becomes a real-world one, with a rider getting into a stranger’s car or a driver welcoming someone they’ve never met into their vehicle. The ability to establish who is on both sides of that interaction, and maintain confidence in that identity over time, is a critical part of keeping the marketplace safe.

I recently hosted a session at Marketplace Risk NYC with Manju Siddappa, Head of Engineering at Uber, where we explored what it takes to establish and maintain trust across a massive global platform. More to the point, we discussed how that challenge is changing as AI makes sophisticated deception increasingly accessible.

As we learned in our session, the traditional model of verifying someone once and assuming they can be trusted from that point forward is becoming impossible to defend.

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When digital trust has real-world consequences

Manju made it clear at the start of our conversation: at Uber, safety comes first.

Fraud prevention and trust are obviously critical, but Uber operates in an environment where digital interactions lead directly to physical ones. Riders need confidence that the person arriving is the driver they expect.Drivers need confidence in the person entering their vehicle. And Uber needs mechanisms for continually establishing that the people participating in its marketplace are who they claim to be.

That changes the role identity plays.

Identity verification cannot only be a gate someone passes through when creating an account. It has to contribute to an ongoing understanding of the person interacting with the platform.

AI is changing what platforms have to defend against

The urgency around that shift is growing because the tools available to attackers are improving rapidly. We discussed the increasing sophistication of document fraud, and Manju highlighted hyper-realistic deepfakes and forged identity documents. AI can dramatically reduce the effort required to create convincing fraudulent artifacts, while organized fraud rings can industrialize those techniques across large numbers of accounts where organizations are seeing more organized racketeering involving coordinated networks for colluding and account sharing in black markets.

The economics of deception are changing. Tasks that once required specialized skills, significant time, or substantial resources can increasingly be automated and scaled. As those barriers fall, marketplaces should expect attacks to become more sophisticated, persistent, and coordinated.

That makes a single identity check, even a strong one, just a part of the answer.

Trust has to follow the user

People don't interact with platforms once. They create accounts, return on new devices, change information, recover credentials, make transactions and take actions that may look very different over time. Risk changes, too.

A legitimate account can be compromised. A device can change hands. An identity can behave differently. New signals can emerge that alter what a platform knows about the person behind an interaction.

The goal, then, isn't to repeatedly force users through the same verification process. It's to create a persistent trust layer that can recognize known users, incorporate new signals and determine when additional verification is actually warranted.

For legitimate users, that can mean less visible verification, not more. Instead of asking people to continually prove who they are, platforms can build on the trust they've already established and introduce friction when something meaningfully changes.

What does the future of trust look like?

Toward the end of our conversation, Manju offered a compelling vision for where this could go over the next five years: trust becomes increasingly invisible to the user.

Today, we tend to think of identity verification as an event. Upload a document. Take a selfie. Enter a code. Complete a check. But the future may look much more dynamic.

We explored the potential for identity profiles informed by signals accumulated across interactions and, eventually, cross-industry consortiums. Instead of every platform starting from zero, trusted signals could help create a richer understanding of identity and risk across the digital ecosystem.

There are significant questions the industry will need to solve to make that vision work, including how signals are shared, how consent is managed, and how businesses establish confidence in the provenance and reliability of those signals.

It starts with the notion that trust can become something that is established, strengthened and continuously evaluated, not repeatedly recreated from scratch.

Identity is now the accelerator for marketplace growth

It was clear from both this session and discussions with other leaders at the conference that identity is moving deeper into the infrastructure of digital marketplaces.

As AI makes it easier to manufacture convincing identities and automate abuse, platforms will need more than stronger checkpoints. Platforms need ways to establish persistent relationships between people, devices, credentials and actions throughout the customer lifecycle.

The opportunity is to make strong identity largely invisible for legitimate participants while giving platforms the intelligence they need to recognize when something has changed and respond accordingly.

For global marketplaces like Uber, getting that balance right has enormous implications. It reduces fraud and abuse. It creates safer interactions. And it gives users greater confidence in the people and platforms they're interacting with.

And as our physical and digital worlds become even more intertwined, that ability to establish trust continuously, not just at the front door, will become increasingly fundamental to how marketplaces operate.