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communick@academy.garden

[P] Fraud Detection | e-commerce (alien.top)

submitted 10 months ago by common_happen143@alien.top to c/machinelearning@academy.garden

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I am building a system to separate fraudulent transactions, these will be then manually verified, helping me in turn build a labelled dataset over time.

For now I have transaction data and customer behavior Information.

I intend to do this like this:The possible fraud cases include:- Abuse of all cashbacks and discounts ( Coupons / Vouchers / Auto Refund)- Retailing

- Acquiring sensitive SKUs

Since I don't really have labelled data, I am going with the unsupervised learning approach (isolation forest).I plan on having 3 modules : Users, SKUs, Localities For the last 2 I am suffering with setting meaningful thresholds, I standardized slope of sales trend and intercept, then divided them to get a compound variable which I am using to compare. Please share thoughts and or Resources.

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[–] flamboyantkoala@programming.dev 1 points 10 months ago

This seems like it’ll be a really long journey without labeled data. Do you have an idea of how much fraud is in your sample set?