Loyalty Points Borrowing Prediction System

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Solution Overview

Problem

Users often face the challenge of not having sufficient loyalty points to purchase goods or services, such as flights, hotel stays, or concert tickets, even if they anticipate accumulating enough points by the time of purchase.

Innovation Solution

A system and method for loyalty point borrowing, where a points borrowing computer program predicts the user's future loyalty points earnings, approves the purchase, borrows necessary points, conducts the purchase, and periodically reduces the borrowed points balance against new earnings, ensuring the user can complete the purchase by the event date.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If users wait until they have sufficient loyalty points to make a purchase, then they can afford the good or service, but the good or service may no longer be available or priced differently

Engineering Contradiction:

Improvepurchase completion reliabilityVSAvoidtime delay until purchase

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by predicting future loyalty point earnings before the purchase date and pre-approving purchases that users will be able to afford. This allows users to secure bookings now rather than waiting until they accumulate sufficient points, eliminating the time delay while ensuring purchase completion through the prediction mechanism.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system segments the loyalty point accumulation process into predictable future earnings that can be calculated and committed in advance. By breaking down the total points needed into predicted future earnings plus any shortfall, the system enables partial pre-approval and reduces the waiting time while maintaining purchase reliability.

Inventive Principle:

Principle #1Segmentation

2Adaptability or versatility

If users make purchases with borrowed loyalty points before accumulating enough points, then they can secure the good or service, but they will have a points deficiency to repay

Engineering Contradiction:

Improvepurchase timing flexibilityVSAvoidloyalty points balance

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The system implements feedback by continuously monitoring actual loyalty point earnings against predicted earnings and adjusting the points deficiency balance accordingly. As users earn points, the system automatically updates their repayment status, providing real-time feedback on their borrowing status and enabling dynamic adjustment of the points balance.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system makes the loyalty points balance dynamic by allowing it to fluctuate based on actual earnings versus predicted earnings. The points deficiency is not a fixed debt but a dynamic value that changes as users accumulate points, enabling flexible repayment without rigid constraints on the points balance.

Inventive Principle:

Principle #15Dynamics

3Measurement precision

If the system predicts future loyalty points earnings accurately, then users can make informed borrowing decisions, but the prediction process adds system complexity

Engineering Contradiction:

Improveloyalty points earning prediction accuracyVSAvoidprediction system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system employs self-service by using automatically collected user transaction data and spending patterns to generate predictions without requiring manual input or complex external systems. The prediction mechanism leverages existing data infrastructure to provide accurate forecasts while minimizing additional system complexity through automated data processing.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250191021A1Systems and methods for loyalty points borrowing

Publication Date: 2025.06.12 JPMORGAN CHASE BANK NA

AI summary

A method may include: receiving from a user computer program, a selection of a good or service to purchase from a good/service provider using loyalty points and an identification of a date for an event associated with a purchase; determining that the user does not have sufficient loyalty points in a user loyalty point account for the purchase; predicting a predicted number of loyalty points that the user will earn before the date of the event; approving the purchase and borrowing loyalty points necessary for the purchase; conducting the purchase using loyalty points in the user loyalty point account and the borrowed loyalty points; periodically reducing a borrowed loyalty points balance against new loyalty points earned by the user by redeeming the new loyalty points; determining at the date of the event, a final loyalty points deficiency; and executing a transaction to pay for the final loyalty points deficiency.