Automated Positive Pay Return Decision Processing

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Solution Overview

Problem

Financial institutions face challenges in manually processing client positive pay return decisions within tight time constraints, leading to potential errors and increased liability due to the manual nature of the current processes, which also lack an efficient audit trail.

Innovation Solution

Automated systems and methods for processing positive pay return decisions, including identifying suspect pay items, receiving client decisions, and automatically crediting accounts, deleting paid status, and creating return files, thereby reducing manual labor and human errors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual processing methods are used for positive pay return decisions, then flexibility in handling complex cases is improved, but processing time and labor intensity increase significantly

Engineering Contradiction:

ImproveFlexibility in handling complex casesVSAvoidProcessing speed

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The system enables automatic self-processing of return decisions through rule-based engines that autonomously evaluate pay items against predefined criteria, client preferences, and regulatory requirements. The automated system handles routine decisions without human intervention, freeing representatives to focus on complex cases requiring manual review.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical processing steps are replaced with automated computer-based systems including rule engines, decision support algorithms, and electronic communication platforms. This substitution eliminates manual data entry, automated credit memo generation, and electronic transmission of return decisions to the returns department.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If manual processing steps are implemented, then detailed human review and judgment are improved, but time constraints and error rates increase

Engineering Contradiction:

ImproveHuman review qualityVSAvoidProcessing deadline

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system implements continuous feedback loops where automated decisions are monitored, validated, and adjusted based on outcomes. Decision support systems provide real-time feedback to representatives, highlighting exceptional cases requiring human review while confirming routine automated decisions. This ensures both speed and reliability through iterative validation.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary automated evaluation of all return decisions before human review is needed. Pre-defined rules and algorithms pre-assess pay items, identify obvious returns, and prepare draft decisions in advance, allowing human representatives to focus only on edge cases requiring judgment rather than reviewing every item from scratch.

Inventive Principle:

Principle #10Preliminary action

3Productivity

If automated systems are used for processing, then processing speed and consistency are improved, but adaptability to unusual cases decreases

Engineering Contradiction:

ImproveProcessing efficiencyVSAvoidHandling of unusual cases

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The system employs dynamic rule configurations that can be adjusted based on case characteristics. Adaptive algorithms modify processing behavior in real-time, routing unusual or high-risk cases to specialized review queues while maintaining automated processing for standard cases. The system dynamically balances automation and human review based on case complexity indicators.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes processing parameters and decision thresholds based on case characteristics, client risk profiles, and regulatory contexts. Adjustable parameters allow the same automated framework to adapt to different client preferences, risk tolerances, and unusual case scenarios while maintaining consistent automated processing for routine matters.

Inventive Principle:

Principle #35Parameter changes

4Measurement precision

If manual entry and processing steps are required, then data accuracy through human verification is improved, but operational costs and labor requirements increase

Engineering Contradiction:

ImproveData accuracyVSAvoidSystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system creates and validates data through automated copying and verification processes. Return decisions, credit memos, and transaction records are automatically generated as digital copies from source data, eliminating manual transcription errors. Automated validation rules verify data consistency across systems, providing accuracy comparable to or exceeding manual verification without additional labor.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS8504477B1Systems, methods and computer program products for automating financial institution client positive pay return decisions

Publication Date: 2013.08.06 BANK OF AMERICA CORP

AI summary

Systems, methods, and computer program products are provided for automatically processing positive pay return decisions. Positive pay return decisions are financial client decisions that authorize return of a pay item, such as a check, in the event that the client determines that the pay item warrants return, such as in the instance in which the check has been fraudulently altered or the like. Automated processing provides for deleting pay status from a service management system, creating a credit transaction to credit an appropriate demand deposit account and creating a return file that identifies the item and the reason for return.