Transaction-Level Card Pricing for Accurate Interest and Payment Allocation
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Solution Overview
Problem
Conventional methods for calculating interest charges on credit and debit card transactions are performed at balance level, lacking point-in-time estimation, leading to inaccuracies in interest charge calculations, payment allocations, and fee assessments, and failing to account for promotional offers or disputes.
Innovation Solution
Implementing a platform, language, and cloud agnostic transaction level data management module that performs interest charge calculations, payment allocations, and fee assessments at the transaction level, using a transaction level data management module to group transactions, calculate minimum payment due amounts, and manage promotions, while adjusting for backdated payments and disputes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If interest charge calculations are performed at balance level using conventional methods, then the calculation process is simpler and faster, but the accuracy of interest charge calculations deteriorates due to lack of point-in-time estimation capability
Solution Approach 1:
The patent segments the balance level calculation into transaction level calculations. Instead of calculating interest on the total balance, the system calculates interest for each individual transaction separately using the formula: Interest = Transaction Amount × APR × Days Outstanding / 365. This segmentation enables point-in-time estimation and accurate tracking of when each transaction was posted and paid, resolving the accuracy issue while maintaining manageable complexity through automated processing.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing key transaction attributes such as posting date, payment date, days outstanding, and applicable APR for each transaction. This preliminary data preparation enables accurate point-in-time interest calculations without requiring complex real-time computations, as the necessary data is already prepared and stored when the transaction is first posted.
2Manufacturing precision
If transaction level data management is implemented, then payment allocation accuracy improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent segments payments into transaction-level allocations rather than applying payments to overall balances. Each payment is allocated to specific transactions based on predefined rules (such as oldest first, or by transaction type), allowing accurate tracking of which transactions are paid and when. This segmentation enables precise payment allocation while the system manages complexity through automated rule-based processing rather than manual intervention.
Solution Approach 2:
The system implements dynamic payment allocation rules that can adapt to different scenarios. Payment allocation rules are not fixed but can be adjusted based on account type, transaction type, and customer preferences. This dynamic approach allows the system to handle various allocation strategies (oldest first, by amount, by type) without requiring separate systems for each rule, maintaining productivity while achieving accuracy.
3Ease of operation
If conventional balance level processing is used, then the system is easier to operate, but the ability to handle promotional offers and disputes accurately deteriorates
Solution Approach 1:
The patent segments promotional offers and dispute resolutions into transaction-level applications rather than balance-level adjustments. Promotional offers are applied to specific transactions individually, allowing accurate tracking of which transactions receive promotional treatment and at what rate. Similarly, disputes are resolved at the transaction level, enabling precise adjustments to individual transactions while maintaining the ability to generate accurate statements and records. This segmentation maintains operational simplicity through automated rules while significantly improving reliability.
Solution Approach 2:
The system implements feedback mechanisms that track and record all transaction-level adjustments, promotions, and dispute resolutions. Each transaction maintains a complete history of applicable rates, promotions, and adjustments, providing auditable feedback for verification. This feedback capability ensures accuracy in handling promotions and disputes while maintaining ease of operation through automated tracking and reporting rather than manual verification.
Data Source
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AI summary
Various methods and processes, apparatuses or systems, and media for transaction level pricing and balance management are disclosed. A processor receives a plurality of transactions associated with a card; enriches the plurality of transactions by consuming external transaction data associated with each transaction, populating preconfigured internal attributes data, and outputting enriched transactions; publishes the enriched transactions for executing a transaction level pricing and balance management algorithm; consumes the enriched transactions; identifies type of each transaction from the consumed enriched transactions by applying predefined rules; and executes, for each type of transaction, the transaction level pricing and balance management algorithm to perform the following operations at transaction level at the time of transaction posting instead of balance level calculations at cycle time: fee calculations, interest charge calculations, payment allocations, payment reversal processing, balance management at transaction level, service customers with intra cycle financial estimates, remove account processing at accumulated balance level.