18432293. PREEMPTIVE TRANSACTION ANALYSIS simplified abstract (Capital One Services, LLC)
Contents
PREEMPTIVE TRANSACTION ANALYSIS
Organization Name
Inventor(s)
Michael Mossoba of Great Falls VA (US)
Joshua Edwards of Philadelphia PA (US)
Abdelkadar M’Hamed Benkreira of Washington DC (US)
PREEMPTIVE TRANSACTION ANALYSIS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18432293 titled 'PREEMPTIVE TRANSACTION ANALYSIS
Simplified Explanation: The patent application describes a method for predicting a user's likelihood of purchasing a product based on their online activity data, generating an annotation indicating a potential transaction, and performing fraud analysis on the transaction.
- The method involves receiving and analyzing activity data related to a specific product type.
- It predicts the user's interest in purchasing a product of that type.
- An annotation is generated to indicate a potential transaction for the predicted purchase.
- The annotation is stored in the user's account profile.
- If a transaction occurs, fraud analysis is performed based on the annotation.
Potential Applications: This technology could be used in e-commerce platforms to improve targeted marketing strategies and enhance fraud detection mechanisms.
Problems Solved: 1. Predicting user purchase behavior based on online activity. 2. Enhancing fraud detection in online transactions.
Benefits: 1. Improved user experience through personalized product recommendations. 2. Enhanced security measures for online transactions.
Commercial Applications: Predictive analytics for e-commerce platforms: Enhancing user experience and security in online transactions.
Prior Art: No specific prior art information provided in the abstract.
Frequently Updated Research: No information on frequently updated research relevant to this technology.
Questions about Predictive Purchase Technology: Question 1: How does the method differentiate between genuine user transactions and fraudulent ones? Answer: The method uses the generated annotation to perform fraud analysis on the transaction, which helps distinguish between legitimate and potentially fraudulent activities.
Question 2: Can this technology be applied to different product types beyond the one mentioned in the abstract? Answer: Yes, the method can be adapted to analyze activity data related to various product types, allowing for broader applications in different industries.
Original Abstract Submitted
A method may include receiving activity data associated with a user, wherein the activity data relates to online activity involving a product type, identifying the product type associated with the activity data, and predicting, based on the activity data, that the user is likely to purchase a product of the product type. The method may include generating, based on predicting that the user is likely interested in purchasing the product of the product type, an annotation to indicate that a potential transaction to purchase the product is forthcoming, and storing the annotation in a profile associated with an account of the user. The method may include detecting a transaction to purchase the product, wherein the transaction involves a payment from the account, and performing an action associated with a fraud analysis of the transaction based on the annotation.
