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 16):
The computer-implemented method of  claim 15 , wherein the first and second machine learning models each comprise at least one of:\n a gradient boosting decision tree; an artificial neural network; or a deep neural network.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 91.0
- Lexical Diversity: 1.71053
- Patent Class: 705.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13304191', '14640701', '14479718', '15231425', '09782681']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1275139760255471
- 35 USC 102 Novelty (BERT): 0.498026757337104
- Combined Prediction Score: 0.1645652541567028
- Mean Citation Score: 225.372926
- Max Citation Score: 242.5779
- Similarity Product: 170.7847593905568

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