公开(公告)号：US20240161115A1

公开(公告)日：2024-05-16

申请号：US17985732

申请日：2022-11-11

Applicant: Stripe, Inc.

Inventor： Ryan Drapeau ,  Logan Howard ,  Seth Hendrickson ,  Isaac Madwed

IPC: G06Q20/40

CPC classification number: G06Q20/4016

Abstract: A method and system for detecting a fraudulent payment are described herein. The method can include detecting, at a server computer system, a request to perform a transaction between a merchant system and a customer of the merchant system, and in response to the detecting, determining, in real time one or more real time features corresponding to the transaction. The method may also include determining, by the server computer system, one or more batch features that correspond to one or more attributes associated with the transaction. The method may also include determining, by the server computer system, whether the payment is potentially fraudulent based on utilizing a model that includes inputs corresponding to the combination of the one or more real time features and the one or more batch features, and in response to determining that the payment is potentially fraudulent, performing, a remediation action associated with the transaction.

公开(公告)号：US20240095741A1

公开(公告)日：2024-03-21

申请号：US17947036

申请日：2022-09-16

Applicant: Stripe, Inc.

Inventor： Emmanuel Ameisen ,  Faye Ouyang ,  Seth Hendrickson ,  Andrew Birck

IPC: G06Q20/40

CPC classification number: G06Q20/4016

Abstract: A method and apparatus for machine learning model based fraud detection of transactions are described. The method may include determining, by a fraud detection system, a first block rate of a first fraud detection machine learning model (MLM) that scores transactions of a server computer system, wherein the fraud detection system blocks a transaction when a score generated for the transaction by the first fraud detection MLM does not satisfy a first threshold value. The method may also include accessing, by the fraud detection system, a second fraud detection MLM to be used by the fraud detection system for blocking future transactions. Furthermore, the method may include determining, by the fraud detection system, a second threshold value using a set of prior transactions input into the second fraud detection MLM that results in a second block rate of the second fraud detection MLM within a predetermined margin of the first threshold. The method may also include deploying, by the server computer system, the second fraud detection MLM using the second threshold value for performing fraud detection of at least one new transaction processed by the server computer system.