AI Savings Plan Creator for Multi-Generational Wealth Continuity
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Solution Overview
Problem
Existing savings mechanisms fail to provide continuity and transfer of wealth across generations, lacking personalization and effective investment strategies for multi-generational wealth accumulation.
Innovation Solution
A multi-generational AI-powered savings plan utilizing a machine learning engine to create and manage a savings fund, which includes a disbursement schedule based on milestones, managed by a virtual trustee, and continuously trained on current financial data to optimize investments and distributions across generations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional savings mechanisms are used, then simplicity and ease of operation are maintained, but continuity of wealth across generations and personalized investment strategies are lost
Solution Approach 1:
The patent introduces a machine learning engine as an intermediary between the user and the savings fund. This ML engine acts as a smart mediator that automatically manages investments, monitors milestones, and executes disbursements based on learned patterns from financial data, thereby providing personalized multi-generational wealth management without requiring direct complex user intervention
Solution Approach 2:
The savings plan operates autonomously through the ML engine that continuously trains on financial data and automatically makes investment decisions, monitors beneficiary milestones, and executes disbursements without human intervention. The system serves itself by maintaining and optimizing its own investment strategies across generations
2Duration of action of moving object
If manual wealth management is used, then control and oversight are maintained, but continuity beyond individual lifespan and optimized investment strategies are lost
Solution Approach 1:
The patent establishes continuous wealth management by creating a savings fund that operates indefinitely beyond the initiator's lifespan. The ML engine continuously trains on current financial data and maintains uninterrupted investment management, milestone monitoring, and disbursement execution across multiple generations, ensuring unbroken wealth accumulation and distribution
Solution Approach 2:
The system dynamically adjusts investment parameters by continuously training the ML engine on current financial data. This allows the investment strategy to adapt to changing market conditions, optimizing returns while maintaining the long-term continuity of the savings plan across generations
3Ease of operation
If simple disbursement schedules are used, then ease of operation is maintained, but milestone-based personalized distributions and evidence verification are lost
Solution Approach 1:
The patent implements a feedback mechanism where the ML engine receives evidence from beneficiaries regarding milestone achievement, verifies this information against predetermined criteria, and adjusts disbursement decisions accordingly. This closed-loop feedback system ensures accurate milestone verification while automating the disbursement process, maintaining both precision and ease of operation
Data Source
AI summary
A non-transitory computer readable medium storing computer-executable instructions that, when executed by a processor, cause a machine learning (ML) engine and/or Artificial Intelligence (AI) to: train a machine learning model of the machine learning engine using financial datasets; providing parameter values to a Savings Plan Creator via a user interface; generating, by the Savings Plan Creator, a savings plan for a short or a long-term savings instrument based on the provided parameter values, the savings plan creator being driven by the machine learning engine that matches the provided parameter values to an existing savings plan selected from a Plans Database having existing savings plans stored therein, or that synthesizes a customized savings plan.