Everyone who has built a model knows the big payoff for effort in data preparation and engineering meaningful features for model inputs. That’s doubly true for fraud because we live with skinny data. You need to aggregate lots of payment transactions to have enough data and pattern for success.

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Building a good home for your fraud model


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