Financial Plan Aggregation via Automated Data Updates
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Solution Overview
Problem
Financial planners face challenges in continuously monitoring and updating financial plans due to delays in receiving updated client data, leading to inaccurate or inappropriate plans generated with limited and outdated data.
Innovation Solution
A system that aggregates user data from various internal and external sources, including financial institutions and publicly available databases, to generate and continuously update financial plans, using a financial planning engine that integrates and analyzes this data to provide personalized advice and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If financial planners manually collect and update client data, then data accuracy can be maintained, but time consumption and delays in updating financial plans increase
Solution Approach 1:
The system enables automatic self-updating of client financial data by connecting to external sources such as employers, banks, and investment accounts. Data is automatically retrieved and updated without requiring manual collection by financial planners, thus maintaining accuracy while eliminating time delays in updating financial plans.
Solution Approach 2:
The manual mechanical process of data collection and updating is replaced with an automated electronic system that interfaces with external databases and financial institutions. This substitution eliminates human intervention in data gathering, providing continuous real-time updates without the time consumption associated with manual methods.
2Productivity
If financial plans are generated using limited available data, then the planning process can be completed quickly, but the accuracy and appropriateness of the financial plan deteriorates
Solution Approach 1:
The system implements continuous data collection and automatic updating of client information from multiple external sources. This continuous flow of fresh data ensures that financial plans are always generated with the most current and comprehensive information available, maintaining high accuracy while enabling rapid plan generation through automated processes.
Solution Approach 2:
The system integrates multiple data collection functions into a single platform, automatically gathering information from diverse sources including employers, financial institutions, and investment accounts. This multi-functional approach consolidates what would otherwise require multiple separate data gathering efforts, improving both speed and accuracy of financial plan generation.
3Reliability
If financial planners continuously monitor client financial situations, then financial plans can be kept up-to-date, but the complexity and resource requirements of the system increase
Solution Approach 1:
The system introduces automated intermediary components including data aggregation services, API interfaces with financial institutions, and centralized databases that act as intermediaries between multiple data sources and the financial planning system. These intermediaries simplify the monitoring process by handling data collection, validation, and integration automatically, reducing system complexity while maintaining continuous monitoring capability.
Data Source
AI summary
Aggregation processes and systems acquire user data from many internal and external sources, such as a host financial institution, external institutions, and publicly available websites and databases. The data aggregation may be used to pre-populate the fields in a questionnaire that would otherwise have to be manually populated by the user. A financial plan based on the data is generated and provided to the user. After presenting the financial plan to the user, additional information may be requested from the user. After the additional information is received, the financial plan may be revised and provided to the user.