Financial Analyzer System for Irregular Income Forecasting
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Solution Overview
Problem
Current ledger systems for tracking account transactions are limited in providing an accurate and comprehensive view of available funds, as they require manual analysis and do not account for irregular income sources or future transactions, leading to incomplete financial forecasting and user stress.
Innovation Solution
A financial analyzer system that automatically estimates finances by incorporating multiple income sources, including irregular ones, and provides recommendations through a user-friendly interface, using machine learning and data integration from various sources to offer holistic financial forecasts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of historic ledger records is used to estimate available funds, then users can understand their financial situation, but the process is time-intensive and inconvenient
Solution Approach 1:
The patent replaces manual mechanical analysis of ledger records with an automated machine learning system that processes transaction data, account balances, and spending patterns to generate financial forecasts and available funds estimates, eliminating time-intensive manual work while maintaining or improving accuracy
Solution Approach 2:
The system enables self-service by automatically analyzing user transaction data and generating financial insights without requiring user intervention, allowing users to obtain accurate available funds estimates instantly through a user interface rather than manually reviewing ledgers
2Loss of information
If traditional ledger systems are used to track transactions, then historic transaction records are maintained, but the system cannot accurately predict future fund availability or account for irregular income sources
Solution Approach 1:
The patent implements dynamic financial forecasting that adapts to irregular income sources and varying spending patterns by continuously learning from new transaction data, allowing the system to handle non-recurring events and predict future fund availability more accurately than static traditional ledgers
Solution Approach 2:
The system changes parameters by incorporating multiple income sources, transaction frequencies, and spending categories into the analysis model, transforming the static ledger view into a dynamic forecast that accounts for irregular income and provides comprehensive financial information
3Measurement precision
If comprehensive financial analysis is performed to improve forecasting accuracy, then better financial insights are provided, but the system complexity increases
Solution Approach 1:
The patent segments the financial analysis system into distinct functional modules including transaction data processing, pattern recognition, forecast generation, and user interface components, allowing complex analysis to be performed through coordinated simple operations that reduce overall system complexity
Solution Approach 2:
The system introduces an intermediary machine learning model that processes complex financial data relationships and translates them into simplified forecasts and recommendations, reducing the complexity burden on both the processing system and user interpretation
Data Source
AI summary
Entities may reference ledgers in order to better understand a historic use and/or status of an account. For example, a user may track historic spending or received payments based on referencing a ledger, or an enterprise may check a balance of an account for a user based on a ledger. However, the utility of ledgers in estimating an amount of funds available for a user's use is limited. Embodiments of a financial analyzer as described herein may provide entities with estimations of finances that include contributions from one or multiple income sources, including irregular sources. Some embodiments may provide recommendations to customers to meet needs based on a financial estimation.