Aggregation Routing System with Fallback Logic
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Solution Overview
Problem
The financial industry faces challenges in efficiently accessing, sharing, and utilizing large volumes of transactional data due to the unreliability and high costs of data aggregation services, which can lead to disruptions when aggregators become unavailable or provide incomplete data.
Innovation Solution
A system and method for optimizing data aggregation by determining the optimal aggregation source based on user requests, using a combination of algorithms and preference criteria such as cost, reliability, and compatibility, and merging data from multiple sources to ensure continuity and accuracy, while normalizing data for proper presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data aggregation services are used to access and share transactional data across multiple financial institutions, then data accessibility and sharing capability are improved, but system reliability deteriorates due to aggregator unavailability and data completeness issues
Solution Approach 1:
The patent segments the data aggregation function by implementing multiple independent aggregation sources (primary and secondary) rather than relying on a single aggregator. This segmentation allows the system to divide the data access pathway into separate, independent channels that can operate autonomously, thereby maintaining reliability while preserving data accessibility.
Solution Approach 2:
The patent introduces an intermediary component (the data aggregation system with fallback logic) that mediates between the user/requestor and the multiple aggregation sources. This intermediary automatically routes requests through the primary source when available and switches to secondary sources when the primary fails, thus resolving the contradiction by maintaining reliable access without sacrificing versatility.
2Reliability
If multiple aggregation sources are used to ensure data continuity and accuracy, then data reliability is improved, but system complexity increases due to source selection and data merging requirements
Solution Approach 1:
The patent applies preliminary action by pre-configuring the system with multiple aggregation sources and establishing the fallback hierarchy before any data request occurs. The system pre-defines primary and secondary sources, eliminating the need for complex real-time decision-making during data retrieval. This approach maintains data reliability while minimizing operational complexity.
Solution Approach 2:
The patent changes the parameter of source selection from a dynamic, complex algorithmic process to a static, pre-defined hierarchy. By establishing fixed primary and secondary aggregation sources with clear fallback rules, the system maintains data reliability through multiple sources while significantly reducing the complexity of source selection and data merging operations.
3Quantity of substance
If data is aggregated from multiple sources with different formats, then data comprehensiveness is improved, but data processing complexity increases due to normalization requirements
Solution Approach 1:
The patent extracts the data normalization requirement from the core aggregation process by implementing format standardization at the point of data extraction from each source. By taking out the normalization task and handling it separately during the data retrieval phase, the system achieves comprehensive data aggregation while minimizing processing complexity in the main data flow.
Data Source
AI summary
Apparatuses, methods, systems, and program products are disclosed for optimizing aggregation routing over a network. An apparatus includes a processor and a memory that stores code executable by the processor. The code is executable by the processor to select a data aggregator server from a plurality of data aggregator servers to service a request for aggregated account data based on a plurality of factors associated with each of the plurality of data aggregator servers, format a request for the aggregated account data to be compatible with the selected data aggregator server, route the formatted request over the network to the selected data aggregator server, receive the requested aggregated account data over the network from the selected data aggregator server, populate a form for a personal financial manager (“PFM”) with the aggregated account data, output the populated form to the PFM, and present the aggregated account data to a user.