Buy Now Pay Never — How to fight fraud in real-time with limited data

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Presented by

Faraz Rana - part of founding team at Bread, Joe Lemonnier - Product Marketing & James Brodhurst - Consultant Resistant AI

About this talk

Picture this: someone is asking for a loan. You don’t know who they are or their credit-worthiness. And you have seconds to make a call. What do you do? Was the last default just a missed payment, or was there no intention to pay in the first place? How do you tell the difference between fraud and credit risk? Risk departments in BNPLs are working at the cutting edge of fraud detection to protect some of the fastest growth ever seen in finance from a swarm of fake, synthetic, and stolen identities, and even from friendly fraud. Join us to hear from their battle-tested knowledge: - Why BNPL services make such attractive fraud targets and why they’re a sign of things to come for the rest of finance - How risk teams in BNPLs make calls with limited data and are key to long term growth - How AI is empowering them to distinguish fraud from credit risk

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Explore the latest threats posed by increasingly sophisticated criminals using automation to commit fraud and financial crime at an unprecedented scale, develop an understanding of the mindset of a cybercriminal to anticipate their moves, and learn how to best leverage AI, automation, and human insight to fight back. At Resistant AI, we’ve been using machine learning to hunt cybercriminals for over 15 years, and we’ve followed them into the field of financial crime. We’ve developed state of the art machine-learning techniques we call Real-time Identity Forensics to make the AI and automation systems you rely upon resilient to manipulation and attack. By analyzing everything from submitted documents to ongoing customer behaviors, we uncover and prevent document forgery, serial fraud, synthetic identities, account takeovers, money laundering, and as yet unknown financial threats operating at scale. And we want to arm you with the knowledge you need to fight off this new breed of financial criminals.