Automated Digital File Compliance Verification Using Machine Learning

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing systems for verifying digital files against established rules are inefficient, requiring multiple communications between users, which consume power, processing resources, and network overhead, and often result in non-compliant files being stored in digital asset management systems, necessitating future re-validation.

Innovation Solution

A system that utilizes a machine learning model to automatically verify digital files against sets of rules selected by users, reducing the need for multiple communications and integrating with digital asset management systems to automatically reject non-compliant files.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional manual verification methods are used to check digital files against rules, then users can review and correct files, but multiple communications are required which consume power, processing resources, and network overhead

Engineering Contradiction:

Improvefile compliance verificationVSAvoidpower consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent replaces manual verification processes with an automated machine learning model that analyzes digital files against compliance rules. The model processes files, generates compliance scores, and identifies specific rule violations automatically, eliminating the need for multiple human review cycles and associated communications.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service verification where the machine learning model autonomously evaluates files, generates compliance assessments, and provides actionable feedback without requiring human intervention for each verification step. The DAM system integration allows automated enforcement of compliance decisions.

Inventive Principle:

Principle #25Self-service

2Reliability

If traditional manual verification methods are used, then users can review files, but processing resources and network overhead increase due to multiple communications

Engineering Contradiction:

Improvefile compliance verificationVSAvoidprocessing resources

Core Design Contradiction:

ReliabilityVSPower

Solution Approach 1:

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If traditional verification systems are used, then files can be reviewed, but non-compliant files are often stored in DAM systems requiring future re-validation

Engineering Contradiction:

Improveverification efficiencyVSAvoidcompliance assurance

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs preliminary compliance verification before files are stored in the DAM system. The machine learning model evaluates files against compliance rules upfront, and the DAM system is configured to reject non-compliant files, preventing them from being stored and eliminating the need for future re-validation.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system provides detailed feedback to users about compliance violations, including specific rules that are not met and guidance for correction. This feedback loop enables users to understand and address compliance issues before submission, improving overall compliance rates.

Inventive Principle:

Principle #23Feedback

4Use of energy by moving object

If automated machine learning verification is implemented, then power and processing resources are conserved, but the system complexity increases

Engineering Contradiction:

Improvepower consumptionVSAvoidsystem architecture

Core Design Contradiction:

Use of energy by moving objectVSDevice complexity

Solution Approach 1:

The patent introduces a machine learning model as an intermediary between file upload and DAM storage. This intermediary automatically assesses compliance and communicates requirements to users, simplifying the overall process despite the added computational layer by eliminating multiple human review cycles.

Inventive Principle:

Principle #24Intermediary (Mediator)

5Reliability

If multiple communication cycles are used for verification, then thorough review is possible, but network overhead increases

Engineering Contradiction:

Improvecompliance verification accuracyVSAvoidnetwork overhead

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250124153A1Verifying digital files against rules

Publication Date: 2025.04.17 CAPITAL ONE SERVICES LLC

AI summary

In some implementations, a rules system may receive a digital file associated with an entity. The rules system may receive, from a user device, an indication of a set of rules associated with the entity. The rules system may apply a model, associated with the set of rules, to determine whether the digital file is compliant with the set of rules and may determine at least one compliance result based on output from the model. The rules system may transmit, to the user device, instructions for a user interface that indicates the at least one compliance result.