Peer Group User Profiles for Personalized Financial Guidance
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Solution Overview
Problem
Financial literacy among young adults is often considered boring, irrelevant, and non-relatable, and existing financial content on the internet is inaccurate, impersonal, and difficult to find, leading to stress and a lack of relevant financial advice.
Innovation Solution
A system and method for generating and updating a user profile based on peer group data, using a network service to compare a user's financial profile with similar peers, providing personalized and actionable insights and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generic financial advice is provided to users, then the system can serve a broad audience with minimal customization, but the advice becomes irrelevant and non-relatable to individual users' unique situations
Solution Approach 1:
The system performs preliminary actions by automatically generating user profiles and comparing them with peer groups before delivering financial advice. This pre-processing of user data into structured profiles enables personalized recommendations without requiring complex real-time analysis during the advice delivery phase
Solution Approach 2:
The patent introduces an intermediary mechanism - the peer group comparison system - that mediates between generic financial data and individual user needs. By comparing users with similar peer groups, the system translates broad financial principles into personalized, relatable advice without requiring direct complex customization for each user
2Measurement precision
If detailed user profile data is collected and analyzed, then personalized financial insights can be generated, but the system requires significant computational resources and processing time
Solution Approach 1:
The system applies partial action by focusing on comparing users with their peer groups rather than analyzing every possible aspect of their financial situation. This selective comparison approach achieves sufficient personalization accuracy without requiring exhaustive data processing, reducing both computational resources and time requirements
3Ease of operation
If financial content is made more accessible and personalized, then user engagement and financial literacy improve, but the risk of providing inaccurate or untrustworthy information increases
Solution Approach 1:
The system implements feedback mechanisms by continuously updating user profiles based on new data and comparing results with peer group performance. This iterative process allows the system to refine its recommendations over time, improving both accessibility and reliability through continuous validation against real-world peer outcomes
Data Source
AI summary
A method for generating a user profile based on a comparison to peer group data, the user being a member of an institution, the method comprising the steps of: obtaining user profile data pertaining to a user of a network service of the institution; accessing group profile data associated with the user; comparing the user profile data to the group profile data to generate comparative data; generating a user profile for presentation on a user interface, the user profile including the comparative data; sending the user profile to the user; receiving a request from the user for a product of institution; and updating the user profile to include information pertaining to the product.