Adaptive Investing Methodology for Personalized Asset Allocation
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Solution Overview
Problem
Current investment methods, such as target date funds, do not provide an optimum investment strategy for individual investors as they apply the same asset allocation to all investors regardless of personal factors, while managed accounts are expensive and beyond the financial means of many.
Innovation Solution
An adaptive investing methodology that determines asset allocations based on predetermined investor variables like age, income, account balance, and risk tolerance, using a computer-implemented model to generate wealth tables that map these variables to asset allocations between different asset classes, without requiring individual investor input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If target date funds are used to provide automated asset allocation, then ease of operation is improved, but adaptability to individual investor needs deteriorates
Solution Approach 1:
The patent applies local quality by transitioning from a uniform asset allocation approach (same for all investors) to a differentiated approach where each investor receives customized asset allocation based on their specific characteristics such as age, income, risk tolerance, and investment goals. This allows the system to maintain automation while adapting to local (individual) needs.
Solution Approach 2:
The patent implements dynamics by making asset allocations adaptive and changeable over time based on evolving investor circumstances. The system dynamically adjusts allocations as investors age, their income changes, or their risk tolerance evolves, rather than using static allocations. This resolves the contradiction by enabling both automation and individualization through dynamic adaptation.
2Adaptability or versatility
If managed accounts are used to provide personalized investment strategies, then adaptability to individual investor needs is improved, but cost deteriorates
Solution Approach 1:
The patent applies self-service by enabling the system to automatically generate and adjust personalized asset allocations using readily available investor information from record keepers, without requiring expensive human financial advisors. The automated modeling and wealth table generation allow the system to serve itself in creating customized strategies, significantly reducing costs while maintaining adaptability.
Solution Approach 2:
The patent uses copying by creating standardized wealth tables and modeling frameworks that can be replicated and applied to multiple investors simultaneously. Instead of manually creating personalized strategies for each investor (expensive), the system copies and adapts the same underlying model and tables to generate individualized allocations at low marginal cost, resolving the contradiction between personalization and cost.
3Loss of energy
If automated models are used to determine asset allocations, then cost is reduced, but measurement precision of investor-specific factors deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing wealth tables that contain optimized asset allocation recommendations for various combinations of investor characteristics. These pre-computed tables are generated using sophisticated modeling that accurately captures complex investor factors, and then simply looked up during execution. This approach maintains measurement precision in the model development phase while keeping operational costs low.
Solution Approach 2:
The patent implements partial action by using a subset of the most important investor variables (age, income, risk tolerance, investment horizon) rather than attempting to measure and process every possible investor characteristic. This selective approach maintains sufficient precision for effective decision-making while reducing computational complexity and costs, resolving the contradiction between accuracy and expense.
Data Source
AI summary
Method and system for implementing an adaptive investing methodology. An asset allocation is determined for each of a plurality of periods of a model duration that optimize an objective function. The asset allocations identify for each of the periods how much of the investment account to invest in one or more asset classes. The objective function subtracts a value of a shortfall risk function from an expected value of an amount of income to be generated by an annuity purchased at the end of the model duration with funds in the investment account at the end of the model duration. The asset allocations are associated with values of a plurality of investor variables. The values of the plurality of investor variables and their associated asset allocations may be stored in one or more wealth tables and used to look up asset allocations for one or more investors.