Fighting Financial Fraud with Targeted Friction

David from the Trust team walks us through how Airbnb battles chargebacks while minimizing impact to good guests.

David Press
Feb 6, 2018 · 9 min read
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The piano in our “Vienna” meeting room in San Francisco has an easter egg. Move the right book, and it will play for you!
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Figure 1: Schematic diagram of Good user dropout and Fraudster dropout experiments.
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Figure 2: Example ROC curve of a ML model predicting P(fraud)
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Figure 3(a): Blocking events, a friction with F=1 and G=1. Figure 3(b): Applying a friction with F=0.95 and G=0.1


Airbnb Engineering & Data Science

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