PATENT CLAIM ANALYSIS

Application Number: 15944693
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2019-09
Patent Classification: ["705", "044000"]

Abstract:
Methods, systems, and computer program products are provided for using pre-purchase scoring to efficiently detect fraud on an e-commerce platform. In particular, high dimension pre-purchase information may be consolidated into one or more scores to be carried over and applied to a real time machine learning model at the purchase stage. More specifically, a large amount of information is available, for example, when a user initially connects to the e-commerce platform, creates an account thereon, subsequently logs in using that account, or adds a payment instrument to their account. Such information is applied to a machine learning model that consolidates the information into a score to be carried over, and used further at the purchase stage.

Claim (Index 1):
A fraud detection system, comprising:\n one or more processors; and one or more memory devices accessible to the one or more processors, the one or more memory devices storing software components for execution by the one or more processors, the software components including:\n a data collection component configured to collect a plurality of usage attributes associated with a plurality of user actions conducted via a user account; \n a fraud risk score generation component configured to generate and store a first fraud risk score based at least in part on the plurality of usage attributes; \n the fraud risk score generation component further configured to, during a second user action conducted via the user account, retrieve the first fraud risk score, and generate a second fraud risk score based at least in part on the first fraud risk score; and \n a fraud detection component configured to determine if a transaction associated with the user account is fraudulent based at least on the second fraud risk score.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 91.0
- Lexical Diversity: 1.71053
- Patent Class: 705.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13304191', '14640701', '14479718', '15231425', '09782681']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1151477083212643
- 35 USC 102 Novelty (BERT): 0.492643824745509
- Combined Prediction Score: 0.1528973199636888
- Mean Citation Score: 225.372926
- Max Citation Score: 242.5779
- Similarity Product: 178.23391746779683

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test