Portfolio Fee Comparison Using Sentiment-Scored Fund Alternatives
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Solution Overview
Problem
Investment accounts and mutual funds face challenges in efficiently determining and managing various fees, including hidden fees, which can hinder maximizing returns, especially for individuals outside the financial sector.
Innovation Solution
A system and method for aggregating and analyzing investment fees by utilizing an API to gather portfolio data, calculating sentiment scores based on Euclidean distance, and providing fee information through a user-friendly interface to help individuals and advisors make informed decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If investment accounts are managed by advisors or robo-advisors, then investment decisions are professionally made based on investor goals and risk tolerance, but fee structures become complex and difficult to understand for individuals outside the financial sector
Solution Approach 1:
The patent segments the complex fee structure into distinct components (expense ratios, 12b-1 fees, front-end loads, back-end loads) and presents them separately to investors. This segmentation allows investors to understand each fee type independently rather than facing a monolithic complex fee structure, directly addressing the contradiction between professional management quality and fee complexity.
Solution Approach 2:
The system acts as an intermediary between professional investment management and investors by providing a fee analysis platform that translates complex fee structures into understandable information. This intermediary tool bridges the gap between professional advisors who manage investments and individual investors who need to understand fees, resolving the contradiction by adding an informational layer without changing the underlying professional management.
2Loss of information
If comprehensive fee information is provided to investors, then investors can make informed decisions to maximize returns, but the system complexity and data processing requirements increase
Solution Approach 1:
The system performs multiple functions within a single platform: collecting portfolio data, calculating various fee metrics (expense ratios, 12b-1 fees, load fees), performing tax cost ratio analysis, and presenting comprehensive fee information. This multi-functionality approach consolidates what would otherwise require multiple separate tools, providing comprehensive fee transparency without proportionally increasing system complexity.
Solution Approach 2:
The system performs preliminary calculations and analysis of fee structures before investors make decisions. By pre-calculating expense ratios, comparing fee structures, and analyzing tax cost ratios in advance, the system provides ready-made fee information that investors can use immediately, reducing the computational burden on investors and streamlining the decision-making process.
3Loss of energy
If investors manually analyze fee structures and portfolio data, then they can identify fee savings opportunities, but the time and effort required make this impractical for most individuals
Solution Approach 1:
The system enables self-service fee analysis by automatically collecting portfolio data, calculating fee metrics, and presenting fee comparison information without requiring investors to manually gather or compute data. Investors simply connect their accounts and receive comprehensive fee analysis, eliminating the need for manual analysis while still capturing fee savings opportunities.
Solution Approach 2:
The patent replaces manual mechanical analysis (spreadsheets, manual calculations, paper statements) with an automated digital system that programmatically collects data, performs calculations, and generates fee reports. This substitution of mechanical manual processes with automated computational systems dramatically reduces the time and effort required while maintaining comprehensive fee analysis capabilities.
Data Source
AI summary
A method and system for investing in securities, equities, and funds is currently provided. The method comprises a client selecting at least one security, equity, or fund from their current holdings, comparing their selection with other available securities, equities, and funds in a database and calculating a sentiment score for each of the compared alternatives. The sentiment score is a calculated likeness between, or an inverse distance from, the client's selection and the compared securities, equities, or funds. The compared securities, equities, or funds are ranked by their sentiment scores and an expense ratio, a 12b-1 fee, and a front load fee associated with at least an upper ranked portion of the compared securities, equities, or funds is reported.


