Chatbot LLM for Payment Card Benefit Confirmation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Consumers often lack awareness of the benefits associated with their payment cards and the specific merchants that offer these benefits, leading to underutilization of available rewards and discounts.
Innovation Solution
An apparatus and method utilizing a large language model (LLM) integrated with a chatbot within a software application, which stores credit card documentation and converses with users to identify benefits, generate confirmation letters, and send electronic messages with attached letters to user devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If credit card companies provide extensive benefits and partnerships with merchants, then cardholder value increases, but cardholder awareness and understanding of these benefits decreases
Solution Approach 1:
The patent introduces a chatbot as an intermediary between the credit card company and cardholders. The chatbot retrieves benefit information from the credit card documentation data store and presents it to cardholders in an accessible format, bridging the gap between extensive benefits and cardholder awareness.
Solution Approach 2:
The system enables cardholders to self-serve by allowing them to query the chatbot about their benefits, merchants, and rewards. Cardholders can independently obtain information about their card benefits without needing to contact customer service or search through documentation.
2Measurement precision
If detailed credit card documentation is maintained, then accuracy of benefit information increases, but accessibility and user understanding decreases
Solution Approach 1:
The chatbot serves as an intermediary that queries the detailed credit card documentation data store and translates complex information into user-friendly responses. This maintains the accuracy of the source documentation while improving accessibility for cardholders.
Solution Approach 2:
The system changes the parameter of information presentation from detailed technical documentation to conversational, natural language responses. The underlying data remains accurate and detailed, but the delivery format is optimized for user comprehension.
3Device complexity
If manual processes are used for providing benefit information, then system complexity remains low, but user service efficiency decreases
Solution Approach 1:
The chatbot enables automated self-service for cardholders, allowing them to independently query benefit information without manual intervention. This dramatically improves service efficiency while the system complexity remains manageable through the use of established LLM technology.
Solution Approach 2:
The patent replaces manual customer service processes with an automated chatbot system based on large language models. This substitution of mechanical human processes with automated AI processes improves productivity while keeping system complexity relatively low.
Data Source
AI summary
An example operation may include one or more of storing a data store of credit card documentation, conversing with a user via a chatbot within a chat window of a software application, wherein the conversing comprises receiving natural language inputs with requests for information about a payment card, identifying a benefit obtained by the user based on the conversation, executing a large language model (LLM) on the identified benefit and the data store of the credit card documentation to generate a letter of confirmation, and generating an electronic message with the letter of confirmation attached, and transmitting the electronic message to a user device.