Spend Memory Records Using Social and Transaction Matching
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Solution Overview
Problem
Current financial statements lack social context for transactions, making it difficult for users to remember which purchases are associated with specific social events.
Innovation Solution
A system that integrates transaction data with geotagged social media and local data to create a spend memory record, linking transactions with photos, status updates, and location data based on timestamp and location similarities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional financial statements are used to record transactions, then the transaction history is provided, but the social context and memory association for transactions are lost
Solution Approach 1:
The patent merges transaction data from financial statements with social media data (photos, status updates, location data) by combining multiple data sources into a unified spend memory record. This integration preserves social context information that would otherwise be lost in traditional financial statements.
Solution Approach 2:
The spend memory processor acts as an intermediary that receives transaction data, social media data, and local data, then processes and correlates them using timestamp and location matching. This intermediary component enables the connection between financial transactions and social events without requiring direct integration between banking and social media systems.
2Loss of information
If transaction data is correlated with social media data and local data, then social context is provided for transactions, but data processing complexity increases
Solution Approach 1:
The system performs preliminary actions by collecting and storing social media data and local data with their associated timestamps and location information before correlation is needed. This pre-processing enables efficient matching when transaction data arrives, reducing the complexity of real-time data processing.
Solution Approach 2:
The patent replaces manual memory and association efforts with an automated computational system that uses algorithmic matching of timestamps and location data. This substitution of mechanical human cognitive processes with automated data processing reduces the perceived complexity for users while enabling sophisticated correlation.
3Ease of operation
If spend memory records are created by matching timestamp and location data, then transaction-society event association is improved, but data matching accuracy requirements increase
Solution Approach 1:
The system applies partial matching by not requiring exact timestamp and location matches, but rather matches within acceptable time windows and geographic proximity thresholds. This partial matching approach maintains ease of operation while accounting for variations in when transactions occur relative to social media posts and location accuracy limitations.
Data Source
AI summary
Systems and methods include a database maintained by a financial institution that stores transaction data associated with a previous financial transaction performed via a financial account of a respective account holder, wherein the transaction data comprises a transaction location and a transaction timestamp, a spend memory processor of the financial institution that retrieves the transaction data from the database, interacts with a social linking application programming interface (API) to receive, via a network, social data from a social networking site, wherein the social data comprises a social location and a social timestamp, compares the social data to the transaction data, and creates a spend memory record based on one or more similarities between the social data and the transaction data, and a communication interface of the financial institution that provides the spend memory record to a mobile device associated with the account holder.