Operator Data Object Network for Monetary Allocation Logic
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Solution Overview
Problem
Current software for insurance allocation is limited in handling complex and unanticipated allocation situations due to its reliance on predefined policy types and allocation rules, which cannot account for the semantic variability and evolving legal interpretations of insurance contracts, leading to inefficiencies and infeasible work-arounds in legal disputes.
Innovation Solution
The implementation of a universal solution that defines a 'deep logic' for monetary allocation using three Core Operator objects: Distributor, Account, and Trigger, which combine, split, and manage monetary amounts based on defined conditions, allowing for the simulation of any allocation problem conforming to this logic without requiring specific variants of insurance policies or financial instruments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If current software uses predefined policy types and allocation rules, then software structure is simplified and easier to implement, but it cannot handle complex and unanticipated allocation situations
Solution Approach 1:
The patent implements a universal allocation engine that can handle any allocation rule type through a standardized object model. The system defines core operator objects (Distributor, Account, Trigger) that can be combined to represent any allocation scenario, making the software universally applicable to both simple and complex allocation situations without requiring predefined policy types.
Solution Approach 2:
The system changes the approach from fixed predefined types to parameter-driven flexibility. By allowing users to define allocation rules through configurable parameters and conditions rather than fixed categories, the software can adapt to any allocation scenario while maintaining a consistent underlying structure.
2Adaptability or versatility
If software supports arbitrary policy types and allocation rules, then adaptability to complex situations improves, but device complexity increases
Solution Approach 1:
The patent segments the allocation logic into discrete, independent operator objects (Distributor, Account, Trigger) that can be individually defined and combined. This segmentation allows complex allocation rules to be built from simple, well-defined components, reducing overall system complexity while maintaining high adaptability.
Solution Approach 2:
The system introduces intermediary operator objects that mediate between input data and final allocation results. These objects (Distributor, Account, Trigger) serve as standardized intermediaries that simplify the interaction between different parts of the system, making the overall architecture more manageable despite handling complex scenarios.
3Manufacturing precision
If allocation calculations are combined in complex ways to handle real-world situations, then allocation accuracy improves, but calculation time and processing resources increase
Solution Approach 1:
The system performs preliminary actions by pre-defining operator objects and their relationships before actual allocation calculations. The allocation engine is prepared with the complete rule structure in advance, allowing it to efficiently process allocations without repeated interpretation overhead, thus maintaining accuracy while reducing processing time.
Solution Approach 2:
The patent uses object copying and instantiation to efficiently handle multiple allocation scenarios. Once operator objects are defined, they can be copied and reused for different allocation calculations, avoiding redundant processing and maintaining consistency across multiple computations.
Data Source
AI summary
An apparatus including a memory, and a processor coupled to the memory is provided to, obtain information indicating plural rules, a rule among the rules to specify a plurality of conditions including at least one monetary threshold condition and at least one corresponding condition for the monetary threshold condition; obtain information about a sequence of monetary amounts; and execute a process to transform the rules into operator data objects that define a logic common to the rules to control allocation of the sequence of monetary amounts to at least one category. The operator data objects form a network of operator data objects to simulate, according to the defined logic common to the rules, allocation of the sequence of monetary amounts in response to passing in sequence the information about the monetary amounts among the network of operator data objects.