RFP Message Decomposition for Real-Time Targeted Recommendations
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Solution Overview
Problem
Existing real-time payment (RTP) technologies lack the ability to provide targeted recommendations and incentives to customers in real-time based on decomposed structured messaging data, limiting the effectiveness of data exchange and interoperability between financial institutions.
Innovation Solution
A computing system intercepts and decomposes ISO-20022-compliant Request for Payment (RFP) messages to extract customer and relationship data, identifies targeted incentives, and provisions real-time notifications and offers through a digital interface, enabling simultaneous presentation and acceptance/rejection of offers with the payment request.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If real-time payment messaging is used, then payment speed and accessibility are improved, but the ability to provide targeted recommendations and incentives is lost
Solution Approach 1:
The patent segments the payment messaging system into distinct functional components: a messaging layer for real-time payment notifications and a separate analytics layer for extracting customer insights. This segmentation allows the system to maintain real-time payment capabilities while adding targeted recommendation functionality through decomposed message data analysis.
Solution Approach 2:
The patent introduces an intermediary component that acts as a bridge between the real-time payment messaging system and the recommendation engine. This intermediary decomposes incoming payment messages into structured data elements, enabling the system to provide targeted recommendations without compromising payment speed or real-time processing capabilities.
2Loss of information
If structured messaging data is decomposed and analyzed, then customer insights and targeted offers are improved, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-defining message decomposition schemas and customer segmentation rules before real-time payment messages arrive. This allows the system to quickly parse and analyze messages without complex runtime decision-making, reducing system complexity while maintaining insightful customer analysis capabilities.
Solution Approach 2:
The patent changes parameters by transforming unstructured or semi-structured payment messages into standardized structured data formats with specific fields and schemas. This parameter standardization simplifies subsequent analysis and recommendation generation while maximizing the extraction of customer insights from the message data.
3Productivity
If real-time notifications with digital content are transmitted, then customer engagement is improved, but data processing requirements increase
Solution Approach 1:
The patent applies partial action by selectively transmitting only the most relevant digital content and recommendations to each customer based on their payment behavior and profile. This approach maintains high customer engagement by providing personalized content while reducing overall data processing requirements by avoiding unnecessary transmissions.
Solution Approach 2:
The patent implements self-service by enabling the system to automatically generate, prioritize, and transmit digital content based on pre-configured rules and real-time message analysis. This automation reduces the need for manual data processing and content creation while maintaining high customer engagement through timely, relevant notifications.
Data Source
AI summary
The disclosed embodiments include computer-implemented apparatuses and processes that provision, in real-time, targeted recommendations based on decomposed structured messaging data. For example, an apparatus receives a message that includes elements of message data disposed within corresponding message fields. The message data may be associated with a first product provisioned to a second counterparty by a first counterparty. Based on an application of a trained machine-learning or artificial-intelligence process to an input dataset that includes elements of message data, the apparatus determines a value of a parameter that characterizes at least one of the second counterparty or a relationship between the second counterparty and the first counterparty, and transmits digital content associated with the parameter value to a device operable by the second counterparty, which presents a portion of the digital content within a digital interface.