AI Contract Management System with Blockchain Risk Assessment

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Solution Overview

Problem

Current contract management systems are inaccurate and risky due to their inability to consider varying contract types and risk clauses, and they lack advanced data processing techniques, leading to inefficient contract creation and execution processes.

Innovation Solution

A contract management system utilizing AI engines and machine learning algorithms to analyze contract parameters, extract data attributes, and generate scripts for processing, along with a blockchain-based system for secure and efficient contract management, including risk assessment and KPI monitoring.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated processing is applied to contract management, then productivity is improved, but reliability deteriorates due to inability to consider varying contract types and risk clauses

Engineering Contradiction:

Improvecontract processing speedVSAvoidcontract assessment accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system dynamically adapts its processing approach based on the type of contract being analyzed. Different contract types (fixed price, cost-reimbursement, time and material) are routed to specialized processing modules that understand their specific characteristics and risk profiles, allowing automated processing to maintain high reliability across diverse contract varieties.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes processing parameters based on contract characteristics. By analyzing contract type, scope clarity, and risk factors, the system adjusts the depth and type of analysis performed, applying more rigorous scrutiny to high-risk contracts while maintaining efficient processing for standard agreements, thus balancing productivity and reliability.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If advanced data processing techniques are used, then measurement precision is improved, but device complexity increases

Engineering Contradiction:

Improvedata extraction accuracyVSAvoidsystem architecture complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The complex data processing system is segmented into specialized modules: OCR engines for data extraction, NLP modules for clause analysis, risk assessment engines for identifying risk factors, and validation systems for verifying extracted data. Each module focuses on a specific task, achieving high measurement precision while managing overall system complexity through modular design.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces intermediary processing layers between raw contract data and final analysis results. Data extraction intermediaries clean and structure raw text, while validation intermediaries verify accuracy before results are presented to users. These intermediaries enhance measurement precision without requiring the entire system to be overly complex.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Reliability

If comprehensive risk assessment is performed, then reliability is improved, but loss of time increases during negotiations

Engineering Contradiction:

Improverisk identification accuracyVSAvoidnegotiation cycle duration

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary risk assessment by analyzing contract templates and clauses against a database of known risk patterns before negotiations begin. This upfront analysis identifies potential issues that can be addressed during negotiations, improving reliability of risk identification while reducing time loss by preventing surprises during the negotiation process.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system provides real-time feedback during negotiations by monitoring contract changes and alerting parties to new risks introduced by proposed modifications. This continuous feedback mechanism maintains high reliability of risk assessment while minimizing time loss by immediately highlighting issues that require attention, rather than requiring comprehensive re-analysis of the entire contract.

Inventive Principle:

Principle #23Feedback

4Reliability

If manual review processes are used, then reliability is improved, but productivity deteriorates

Engineering Contradiction:

Improvecontract analysis accuracyVSAvoidcontract processing volume

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs self-service by automatically extracting data, identifying clauses, assessing risks, and generating analysis reports without requiring manual review for every contract. The AI-powered processing handles routine analysis tasks with high reliability, freeing human reviewers to focus on complex cases that require judgment, thus maintaining productivity while preserving reliability for critical assessments.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS11348352B2Contract lifecycle management

Publication Date: 2022.05.31 NB VENTURES INC DBA GEP

AI summary

The present invention discloses a method, a system and a computer program product for Contract management. The invention includes optical character recognition for extraction of data attributes from the contracts. The invention further provides AI engine configured for processing a contract creation request through a bot based on analysis of a set of parameters associated with the request.