18410871. METHODS AND ARRANGEMENTS TO DISTRIBUTE A FRAUD DETECTION MODEL simplified abstract (Capital One Services, LLC)
Contents
METHODS AND ARRANGEMENTS TO DISTRIBUTE A FRAUD DETECTION MODEL
Organization Name
Inventor(s)
Austin Grant Walters of Savoy IL (US)
Jeremy Edward Goodsitt of Champaign IL (US)
Fardin Abdi Taghi Abad of Champaign IL (US)
Reza Farivar of Champaign IL (US)
METHODS AND ARRANGEMENTS TO DISTRIBUTE A FRAUD DETECTION MODEL - A simplified explanation of the abstract
This abstract first appeared for US patent application 18410871 titled 'METHODS AND ARRANGEMENTS TO DISTRIBUTE A FRAUD DETECTION MODEL
The abstract of the patent application describes a method to detect fraudulent transactions by associating a customer identification with a model and clustering customers based on their characteristics. The model then transmits transaction data to customer devices and communicates modified transaction data to multiple customers associated with a specific cluster.
- Logic assigns a customer identification to a model to detect fraudulent transactions.
- Characteristics of the first customer are used to determine clusters to associate with the customer.
- Cluster identifications are associated with the first customer, each identifying a group of customers.
- The model transmits transaction data to customer devices associated with the first customer.
- Modified transaction data is communicated to multiple customers associated with a specific cluster.
Potential Applications: - Fraud detection in financial transactions - Customer segmentation for targeted marketing strategies
Problems Solved: - Detection of fraudulent transactions - Efficient communication of modified transaction data to multiple customers
Benefits: - Improved fraud detection capabilities - Enhanced customer segmentation for marketing purposes
Commercial Applications: Title: Fraud Detection and Customer Segmentation Technology This technology can be utilized by financial institutions, e-commerce platforms, and other businesses to enhance security measures and improve customer targeting strategies.
Questions about the technology: 1. How does this technology improve fraud detection in financial transactions? - This technology utilizes customer clustering and model associations to detect fraudulent transactions more effectively. 2. What are the potential benefits of using this technology for customer segmentation? - The technology allows businesses to target specific customer groups more accurately for marketing purposes.
Original Abstract Submitted
Logic may assign a customer identification to a model to associate a first customer with the model to detect fraudulent transactions. Logic may determine one or more clusters to associate with the first customer based on characteristics associated with the first customer. Logic may associate one or more cluster identifications with the first customer. Each cluster identification may identify one cluster of the one or more clusters. Each cluster may identify a group of customers based on characteristics associated with the group of customers. Logic may cause the model to transmit to a customer device associated with the first customer. Logic may receive transaction data for a transaction for one customer of the group of customers associated with a first cluster. And logic may communicate modified transaction data to customer devices of more than one customer of the group of customers associated with the first cluster.
