Automated Payment Detail Extraction from Unstructured Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Financial institutions face challenges in determining complete payment details for funds transfers from unstructured data sets, often requiring user intervention to provide missing information, as the data lacks metadata and context necessary for automated processing.
Innovation Solution
A computing system maintains a database of historical transaction information to identify users and extract contextual data from unstructured data, such as video, audio, and imagery, to determine payment details, including amounts and recipients, allowing for autonomous execution of funds transfers with user approval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated processing is attempted from unstructured data, then productivity is improved, but measurement precision deteriorates due to lack of metadata and context
Solution Approach 1:
The system performs preliminary actions by maintaining a database of historical transaction information and contextual data about users, recipients, and transaction scenarios. Before processing new unstructured data, the system pre-popsulates payment details by matching extracted information (such as recipient names, amounts, or contextual keywords) against historical records, thereby preparing accurate payment information in advance even from unstructured sources
Solution Approach 2:
The system introduces an intermediary matching mechanism that bridges unstructured data and structured payment processing. This intermediary component extracts relevant information from unstructured data (videos, images, text), compares it against historical transaction databases, and generates structured payment details, thereby enabling automated processing without requiring structured input data
2Measurement precision
If user intervention is required to provide missing information, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system implements self-service by automatically completing payment details without requiring user intervention. The matching mechanism autonomously extracts information from unstructured data, queries historical databases, and generates complete payment information including recipients, amounts, and transaction context, allowing the system to serve itself rather than requiring manual user input
Solution Approach 2:
The system performs preliminary matching and completion of payment details before user review. By pre-processing unstructured data and generating payment information in advance using historical data, the system reduces the time users need to spend on data entry while maintaining completeness through pre-populated fields that users can simply review and confirm
Data Source
AI summary
A computing system may be configured to determine payment details for funds transfers from unstructured sets of data. The system may maintain historical transaction information associated with each of a plurality of users. The system may receive data associated with a transaction. The system may identify a user associated with the data, wherein the user is one of the plurality of users. The system may determine, based on contextual information of the data and the historical transaction information associated with the user, payment details about the transaction. The payment details may include a payment amount and one or more recipients. The system may execute a funds transfer for the payment amount from a source account associated with the user to one or more destination accounts associated with the one or more recipients.