Financial Wellness Scoring for Personalized Banking Services
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Solution Overview
Problem
Banks struggle to provide personalized financial products and services that address the changing needs of their clients due to financial stress and lack of knowledge, particularly among younger Americans, leading to inadequate financial planning and management.
Innovation Solution
A financial wellness scoring system using machine learning models to evaluate and monitor a client's financial wellness, providing tailored banking product and service recommendations based on collected data over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If banks use traditional conversation guides to identify client needs, then they can provide some personalized service, but the system lacks real-time monitoring and continuous evaluation of financial wellness
Solution Approach 1:
The system pre-establishes a comprehensive data collection framework and machine learning models that continuously monitor financial wellness indicators. By preparing the analytical infrastructure in advance, the system can immediately evaluate changing client needs and provide timely recommendations without waiting for periodic manual assessments.
Solution Approach 2:
The system implements continuous feedback loops where client financial data is constantly collected, analyzed, and used to update wellness scores and product recommendations. This real-time feedback mechanism enables the system to adapt to changing client needs dynamically, maintaining personalization without time delays.
2Measurement precision
If banks collect comprehensive financial data to assess client needs accurately, then they can improve recommendation quality, but the data processing complexity increases
Solution Approach 1:
The system segments the comprehensive financial data into distinct categories (income, expenses, debts, assets, lifestyle factors) and processes each category through specialized analytical modules. This segmentation allows accurate assessment of multiple financial dimensions while managing processing complexity through modular architecture.
Solution Approach 2:
The machine learning model acts as an intermediary that automatically processes and synthesizes complex multi-source financial data. The model transforms raw data from various sources into meaningful wellness scores and insights, reducing the apparent complexity for end users while maintaining high assessment accuracy.
3Reliability
If banks provide extensive financial education and monitoring services, then client financial wellness improves, but the service cost increases
Solution Approach 1:
The system enables clients to actively participate in their own financial wellness improvement by providing them with real-time feedback, personalized recommendations, and educational resources through the application. Clients can make informed decisions and take actions based on system insights, reducing the need for expensive human financial advisors while maintaining service effectiveness.
Solution Approach 2:
The system dynamically adjusts the level and type of monitoring and education provided based on individual client needs, wellness scores, and engagement patterns. By changing service parameters adaptively rather than providing uniform extensive services to all clients, the system improves financial stability for those who need it most while optimizing resource allocation and reducing overall costs.
Data Source
AI summary
A system and method that evaluate and monitor the financial and physical wellbeing of a person that is a client of a bank, and provides a financial wellness score that is used to provide banking service recommendations that may act to increase the wellness score. The method includes collecting data and information as it is being received over time about the financial wellness of the person, processing the collected data and information as it is being received over time using a machine learning model, determining the financial wellness of the person based on the processed data and information, and providing recommendations for bank products and/or services based on the financial wellness of the person.