Unified Data Manager for Financial Goal Compatibility
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Solution Overview
Problem
Current financial planning computing systems face challenges in managing and reconciling goals and recommendations across different analytical tools due to data format differences, limiting their use in multiple systems and contexts.
Innovation Solution
A unified data manager system that stores and retrieves goals and recommendations in a database, allowing compatibility with various applications and enabling management independent of specific applications, events, or dates, through interfaces that translate data formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If goals and recommendations are embedded in a particular computer system with specific data formats, then they can be managed within that system, but they cannot be easily used in other analytical tools or systems due to data format differences
Solution Approach 1:
The patent creates a universal data structure for goals and recommendations that can be used across multiple analytical tools and systems. By defining a standardized format that different systems can adopt, the invention enables goals and recommendations to be created, stored, and accessed universally without being tied to any single system's proprietary data format, thus resolving the contradiction between versatility and complexity.
Solution Approach 2:
The patent introduces an intermediary data structure that acts as a bridge between different analytical tools. This standardized format serves as a common language that allows different systems to exchange goals and recommendations without requiring complex reconciliation or conversion processes, eliminating the need for manual data format matching while maintaining compatibility across diverse tools.
2Adaptability or versatility
If multiple computer systems are used to create and analyze goals and recommendations, then various analytical capabilities can be utilized, but the outputs from each system are difficult to reconcile due to data format differences
Solution Approach 1:
The standardized data structure enables information from multiple analytical tools to be aggregated and compared effectively. By providing a common format that all systems can output to, the invention prevents information loss during reconciliation and allows financial planners to leverage the full capabilities of multiple tools without losing data integrity or requiring complex manual reconciliation processes.
3Ease of manufacture
If goals and recommendations are created based on specific events, then they can be tailored to particular circumstances, but their use is restricted to those specific contexts
Solution Approach 1:
The patent segments the goal and recommendation data into distinct, independently manageable components. By separating the core goal definition from event-specific parameters, the invention allows the fundamental goal structure to be created once and then adapted or reused across different events and contexts, maintaining both the ease of event-specific creation and the versatility for broader application.
Data Source
AI summary
A particular method includes creating a financial planning goal for a financial planning client based at least in part on a financial planning objective. A financial planning recommendation is associated with the financial planning goal, and data identifying the financial planning goal and the financial planning recommendation is stored in a data store. The method also includes monitoring activity of the financial planning client and at least one other financial planning client to detect a financial planning trend. In response to the detected trend, a financial planning product is selected for potential incorporation into subsequent recommendation(s).