Risk Inquiry Chatbot Responses for Secure Transaction Insights
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Solution Overview
Problem
Service providers face challenges in understanding the complex data provided by risk insights services, leading to inefficient communication and resource wastage due to excessive queries and potential transmission of confidential information, especially when transactions are flagged as risky.
Innovation Solution
A system utilizing a chatbot interface powered by a large language model to interpret user inquiries, trigger workflows, and provide human-readable responses, thereby reducing the need for direct human interaction and minimizing the transmission of confidential data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If trained personnel directly communicate with risk insights service to understand transaction insights, then transaction understanding is achieved, but communication overhead and resource wastage increase significantly
Solution Approach 1:
The patent introduces an automated communication system that acts as an intermediary between service providers and the risk insights service. This system automatically queries transaction insights, retrieves risk scores and transaction data, and communicates findings back to providers, eliminating the need for direct human-to-human communication and significantly reducing communication overhead while maintaining complete information transfer
Solution Approach 2:
The system enables service providers to self-serve by automatically obtaining transaction insights through automated queries. The system independently retrieves risk scores, transaction data, and analysis results without requiring human operators to contact the risk insights service, allowing providers to autonomously understand their transaction risks while minimizing resource consumption
2Loss of information
If complex transaction data is transmitted between entities, then complete information is provided, but confidential information exposure risk increases
Solution Approach 1:
The automated communication system serves as a secure intermediary that retrieves transaction insights directly from the risk insights service and selectively communicates only necessary findings back to service providers. This intermediary architecture prevents direct transmission of sensitive raw data between entities, reducing confidential information exposure risk while maintaining data completeness for risk assessment purposes
Solution Approach 2:
The system extracts and transmits only the specific transaction insights and risk assessment results that service providers need, rather than transmitting all underlying complex transaction data. This selective extraction approach provides complete risk information while minimizing the transmission of potentially confidential raw data, reducing exposure risk
3Ease of operation
If more personnel are trained to understand transaction data, then better communication capability is achieved, but training costs and operational complexity increase
Solution Approach 1:
The automated communication system performs all complex data retrieval and analysis functions independently, eliminating the need for personnel to be trained on understanding complex transaction data formats and communication protocols. Service providers can operate the system with minimal training since the automation handles all complex interactions with the risk insights service, significantly reducing training costs and operational complexity
Data Source
AI summary
The present technology includes solutions for providing risk insights and/or other responses augmented by retried and/or interpreted data. An example method includes receiving, by a risk insights system from an inquiring entity, an inquiry associated with a transaction by a subject entity, wherein the transaction is associated with a risk score; determining, by the risk insights system, one or more factors contributing to the risk score; providing, by the risk insights system, the one or more factors to a machine learning model, wherein the machine learning model is configured to receive the one or more factors and output a response based on the one or more factors, wherein the response is in a format responsive to the inquiry; and output, by the risk insights system, the response to the inquiring entity. Systems and non-transitory computer-readable media are also provided.