User-Customizable Revenue Recognition Rules for Transaction Matching

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Solution Overview

Problem

Existing payment processors face scalability issues in revenue recognition due to the lack of automated and customizable policies, necessitating manual processes for millions of transactions.

Innovation Solution

Implementing user-customizable revenue recognition rules that apply conditions and effective periods to transactions, allowing automatic recognition through a network commerce system.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual revenue recognition process is used, then accuracy can be maintained for complex transactions, but scalability and productivity are severely limited

Engineering Contradiction:

Improverevenue recognition throughputVSAvoidmanual process dependency

Core Design Contradiction:

ProductivityVSExtent of automation

Solution Approach 1:

The system enables self-service revenue recognition by allowing transactions to automatically match against predefined revenue recognition rules without manual intervention. The automated rule engine processes transactions independently, selecting applicable rules and executing revenue recognition logic without human involvement, thereby scaling productivity while maintaining consistency.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual process with an automated computer-based system. The revenue recognition engine uses software algorithms to match transactions against rules, calculate revenue recognition amounts, and post entries automatically, substituting human manual operations with electronic processing mechanisms.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If customizable revenue recognition rules are implemented, then adaptability to different accounting policies is improved, but system complexity increases

Engineering Contradiction:

Improveaccounting policy flexibilityVSAvoidrule configuration complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The revenue recognition rules are segmented into discrete, modular components that can be independently configured and managed. Each rule is a separate unit with specific conditions and treatments, allowing flexible combination to meet different accounting policies without creating overall system complexity. The rule engine processes these segmented rules independently and combines results.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system allows adaptability through parameter changes in rule configurations rather than structural complexity. Users can modify parameters such as recognition timing, allocation percentages, and condition thresholds to accommodate different accounting policies, while the underlying rule engine structure remains stable and manageable.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If automated rule matching is used, then productivity and scalability are improved, but measurement precision and accuracy may be compromised

Engineering Contradiction:

Improvetransaction processing speedVSAvoidrevenue recognition accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system incorporates feedback mechanisms where the revenue recognition engine continuously monitors transaction characteristics, matches them against rules, and adjusts selections based on the most appropriate rule outcomes. This feedback loop ensures that automated processing maintains precision by validating results and correcting mismatches, balancing speed with accuracy.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The rule matching process may apply multiple rules to a transaction (excessive action) and then select the most appropriate one, ensuring comprehensive coverage and precision. Alternatively, the system can apply rules partially to specific transaction aspects while maintaining overall accuracy, rather than requiring complete analysis of every possible scenario.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12430691B2Systems, methods, and apparatuses for implementing user customizable policies for revenue recognition

Publication Date: 2025.09.30 STRIPE LLC

AI summary

Systems, methods and apparatuses for implementing user customizable policies for revenue recognition are described. In some embodiments, user inputs are received from a merchant that specify components of a set of revenue recognition rules to apply to transactions of the merchant on a per transaction basis, wherein each revenue recognition rule specifies a set of conditions to be met to trigger its application, a rule identifier, status, and whether the revenue recognition rule is applied at least one of: a specified product; a specified invoice; a specified customer; a specified payment; a specified refund; and a specified dispute. The user inputs are converted into rules to enable the rules to be matched to the transactions. A transaction is tracked by a server computer system. One or more applicable revenue recognition rules are identified to apply to the transaction, and revenue recognition is performed against the transaction.