Predictive Spending Management for Payment Variability
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Solution Overview
Problem
Individuals face challenges in managing payment variability due to periodic spending patterns, leading to inconsistent monthly expenses and billing fluctuations.
Innovation Solution
A predictive spending and payment management system that evaluates historical spend patterns to predict future spending behavior, allowing for the creation of a structured payment plan that accounts for variability, ensuring balanced monthly payments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If historical spend patterns are used to predict future spending, then payment variability is reduced and monthly payments are balanced, but system complexity increases due to predictive modeling requirements
Solution Approach 1:
The system performs preliminary analysis of historical spend patterns to predict future spending behavior. By evaluating historical data in advance and creating predictive models before the billing period, the system can proactively structure payment plans that balance monthly payments, rather than reacting to spending variability after it occurs.
Solution Approach 2:
The patent introduces an intermediary predictive modeling layer between historical spending data and payment structure decisions. This intermediary component analyzes patterns and generates predictions that inform payment plan creation, acting as a mediator that translates raw historical data into actionable payment structures without requiring direct complex processing of all historical data.
2Ease of operation
If predictive modeling is implemented to smooth spending spikes, then financial control is improved, but data processing requirements increase
Solution Approach 1:
The system extracts only the essential predictive signals from historical spend patterns that are necessary for forecasting future spending. Rather than processing all historical data in detail, the model identifies and extracts key patterns and trends that drive spending variability, focusing computational resources on the most relevant predictive features.
3Stability of the object's composition
If monthly payment balancing is implemented, then spending variability is reduced, but payment plan flexibility decreases
Solution Approach 1:
The payment plan structure is designed to be dynamic rather than static. The system continuously monitors actual spending against predictions and can adjust the payment plan as new spending patterns emerge. This dynamic approach allows the payment plan to adapt to changing user needs and spending behaviors while maintaining the overall goal of balancing monthly payments.
Data Source
AI summary
Disclosed are various approaches for managing payment variability by developing a schedule of monthly payments. An exemplary method of the present disclosure comprises predicting, using an eligibility data model, a level of volatility of spending for a user based on at least transaction data and transaction account balance data of the user during a previous year; predicting, using a balance prediction data model, a future spend behavior for the user during an upcoming period of time, wherein the upcoming period of time comprises a plurality of months; generating a monthly payment schedule for the user for the upcoming period of time based on the predicted future spend behavior of the user; and for each month of the upcoming period of the time, issuing a monthly payment statement to the user based on the generated monthly payment schedule. Other methods, systems, and computer-readable mediums are also presented.