Transaction Reconciliation via Object Recognition Signatures
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Solution Overview
Problem
Existing transaction systems lack the ability to reconcile transactions among multiple provider or user accounts and fail to account for derived object attributes, limiting their functionality in complex transaction scenarios.
Innovation Solution
A transaction system comprising a recognition engine, a transaction engine, and device engagement engines that derive digital representations of real-world objects, associate object attributes with recognition signatures, and use reconciliation matrices to map these signatures to multiple accounts, enabling transactions and account reconciliations across multiple providers or users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single provider transaction system is used, then the system is simple to operate, but it cannot reconcile transactions among multiple provider or user accounts
Solution Approach 1:
The system segments transaction reconciliation into distinct functional modules: object recognition engine for identifying items, attribute derivation for extracting relevant data, signature generation for creating unique identifiers, and reconciliation matrix for mapping to multiple accounts. This segmentation allows complex multi-account reconciliation to be handled through coordinated simple operations.
Solution Approach 2:
The patent introduces several intermediary components: recognition signatures act as intermediaries between objects and accounts, reconciliation matrices serve as intermediaries mapping objects to multiple accounts, and the transaction engine acts as an intermediary coordinating between recognition and device engagement. These intermediaries enable complex multi-account transactions without requiring direct complex interactions between all components.
2Productivity
If manual transaction reconciliation is performed, then the system requires less complex processing, but it increases time consumption and reduces efficiency
Solution Approach 1:
The system implements self-service through automated object recognition that derives attributes and generates recognition signatures without human intervention. The reconciliation matrix automatically maps recognized objects to appropriate user or provider accounts, and the transaction engine autonomously coordinates the reconciliation process, eliminating manual intervention while maintaining high efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-establishing reconciliation matrices that define relationships between objects and multiple accounts before transactions occur. Recognition signatures are generated in advance based on object attributes, so when a transaction is initiated, the system can quickly reconcile by matching pre-computed signatures against pre-defined account mappings, significantly reducing processing time.
3Measurement precision
If basic transaction processing is used, then the system is easier to implement, but it cannot account for derived object attributes in transaction reconciliation
Solution Approach 1:
The patent extracts relevant attributes from recognized objects through a dedicated attribute derivation component. This extraction process isolates only the necessary characteristics (such as object identity, quantity, or other relevant properties) from the full object data, creating streamlined recognition signatures that capture essential information without requiring complex processing of all object attributes.
Data Source
AI summary
A number of sets of methods, systems, and apparatuses applicable to transactions are disclosed. One set includes transaction systems configured to reconcile a transaction among multiple provider accounts or user accounts via derived object attributes and reconciliation matrices. Another set includes methods of reconciling payment of a coupon. Another set includes transaction apparatuses configured to derive object attributes from digital representations to identify purchasable items. Still another set includes methods of mitigating risk of transaction fraud.