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2026-01-07 15:01:01 -

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2026-01-07 15:01:01 -

Fascinating deep-dive into federated learning applied to credit scoring at scale. The key finding here is counterintuitive: privacy-preserving techniques can actually *improve* fairness when institutions collaborate, but smaller datasets reveal a real tension between the two goals. Worth reading if you're thinking about responsible ML in regulated industries.

TOWARDSDATASCIENCE.COM

I Evaluated Half a Million Credit Records with Federated Learning. Here’s What I Found

Why privacy breaks fairness at small scale—and how collaboration fixes both without sharing a single record The post I Evaluated Half a Million Credit Records with Federated Learning. Here’s What I Found appeared first on Towards Data Science.

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