ClearSale’s fraud prevention methodology is based on best practices, industry intelligence, and fraud experience across industries, markets and order types. If a fraud scheme has been attempted, we’ve seen it and have learned how to recognize it.
Our statistical model uses over 70 constructed variables with more than 300 possible fraud categories and scores. This model covers our entire database of historical orders and has a level of rigor that has scored higher on the KS test than credit models. It also allows us to automatically approve very large numbers of orders.
When onboarding a new client, we gather data from past transactions to build fraud scoring and automatic approval thresholds for that client. At a minimum, we gather the first six and last four digits of credit card numbers, IP addresses, device fingerprints, product info, and price.
In addition, as ClearSale evaluates more orders from each client, it helps further validate or update the company’s fraud score – resulting in even more approvals.
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