Product design question

Using AI/ML, how can Amazon detect and prevent fraud done by retailers listed on Amazon e-commerce website

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What this question tests

AI and technical product thinking: can you design a fraud detection system with the right data, model approach, and precision recall trade off.

How to approach it

  1. Define fraud types to target, assume fake listings and stolen inventory resale by third party sellers.
  2. Identify signals: seller account age, sudden inventory spikes, price far below market, return rate, and payment method patterns.
  3. Propose an approach: a supervised model trained on confirmed fraud cases, combined with rule based flags for known patterns while the model matures.
  4. Discuss the precision recall trade off explicitly, since flagging legitimate sellers as fraud damages trust and revenue.
  5. Design the response flow: low confidence flags go to human review, high confidence triggers automatic listing suspension.
  6. Define success as fraud caught before customer harm and false positive rate on legitimate sellers.

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