Financial Health Predictor Using App Data Correlation
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Solution Overview
Problem
Existing financial health assessment methods are inaccurate due to the difficulty in obtaining sensitive data, leading to ineffective financial health improvement efforts by individuals.
Innovation Solution
A system that dynamically generates financial health scores using device application data, financial account data, emotional feedback data, and behavioral data, identifying correlations to execute actions on user computing devices to improve financial health.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensitive financial data is collected to improve financial health assessment accuracy, then measurement precision improves, but difficulty of detecting and measuring increases due to data sensitivity and privacy concerns
Solution Approach 1:
The patent introduces a server as an intermediary that collects sensitive financial data from multiple users, processes it, and generates aggregated financial health scores. The server acts as a mediator between users and financial institutions, enabling accurate assessment without requiring direct access to sensitive data by individual applications or users.
Solution Approach 2:
The patent creates a universal financial health assessment system that can evaluate multiple users simultaneously using the same methodology. The server processes financial data from various sources (bank accounts, credit cards, loans) and applies consistent algorithms across all users, making the assessment system broadly applicable and scalable.
2Reliability
If traditional financial health assessment methods are used, then ease of operation is maintained, but reliability deteriorates due to inaccurate assessments leading to ineffective financial improvement efforts
Solution Approach 1:
The system automatically collects financial data from users' bank accounts, credit cards, and loans through automated connections. The server independently processes this data, generates financial health scores, and provides recommendations without requiring manual intervention from users, thereby maintaining ease of operation while improving reliability.
Solution Approach 2:
The system provides continuous feedback to users through generated financial health scores and actionable recommendations. The server monitors changes in financial data over time and adjusts assessments dynamically, creating a feedback loop that helps users understand their financial health and take corrective actions.
Data Source
AI summary
Techniques are described herein for dynamic financial health prediction. In an embodiment, device application data that includes a plurality of data records relating to one or more software applications installed on a user computing device is collected and stored. A plurality of financial health scores is generated for a user account based at least in part on the plurality of data records relating to the one or more software applications installed on a user computing device. A correlation is identified between values from the one or more data record of the plurality of data records and the plurality of financial health scores of the user account. If the correlation satisfies one or more criteria, an action to be executed on the user computing device.