AI Contract Lifecycle Management for Clause Risk Review
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Solution Overview
Problem
Modern business organizations face challenges in managing the lifecycle of contracts due to the lack of standardization, complexity, and difficulty in ensuring transparency and effective risk management, especially in IT and BPO services, with existing systems being tailored for buyers rather than sellers.
Innovation Solution
An automated system leveraging AI techniques for contract lifecycle management, using deep learning, natural language processing, and fuzzy logic to generate, review, and manage contracts, identify risks, and track fulfillment of obligations, involving an authoring unit, legal review, stakeholders review, and management review.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual contract management processes are used, then flexibility in handling diverse contract types is maintained, but productivity and time efficiency deteriorate due to voluminous contracts requiring extensive human review
Solution Approach 1:
The contract management system segments contracts into standardized templates with distinct clauses, allowing automated processing of individual contract components while maintaining overall contract integrity. This segmentation enables parallel processing of multiple contracts without requiring complex human review of each entire document.
Solution Approach 2:
The system creates and manages contract templates that can be copied and adapted for different contract instances. These templates contain pre-defined clauses and structures that can be automatically instantiated and modified based on specific contract requirements, dramatically reducing processing time while maintaining consistency.
2Manufacturing precision
If standardized contract templates are implemented, then manufacturing precision and consistency improve, but adaptability to diverse service types and customer requirements deteriorates
Solution Approach 1:
The contract templates are designed to be dynamic rather than static, allowing clauses to be selectively activated, modified, or removed based on specific service types and customer requirements. The system maintains a library of clause variations that can be automatically selected based on contract parameters, enabling both standardization and adaptability.
Solution Approach 2:
Different portions of the contract template can have different levels of standardization. Critical legal clauses maintain strict standardization for precision, while sections dealing with service-specific details allow greater variability and customization based on the particular contract type and customer needs.
3Reliability
If comprehensive risk evaluation of all contract clauses is performed, then reliability and risk management improve, but loss of time and processing efficiency deteriorate
Solution Approach 1:
The system performs partial risk evaluation by focusing on specific high-risk clauses and sections rather than analyzing every clause in detail. Risk assessment is applied selectively to clauses identified as potentially problematic based on template history, service type, and predefined risk criteria, maintaining reliability while reducing time loss.
Solution Approach 2:
Risk evaluation criteria and red flag indicators are pre-configured in the contract templates during template creation. This preliminary action allows the system to automatically identify and flag potentially risky clauses before the actual contract review process begins, enabling faster and more targeted risk assessment.
4Reliability
If multiple stakeholders are involved in contract review, then reliability and governance improve, but device complexity and coordination difficulty worsen
Solution Approach 1:
The contract review process is segmented into distinct stages with different stakeholder groups involved at appropriate phases. Legal teams review specific clauses, business stakeholders review commercial terms, and technical teams review service specifications. This segmentation allows parallel review processes without requiring all stakeholders to coordinate on every detail.
Solution Approach 2:
The contract management system acts as an intermediary platform that coordinates stakeholder reviews, manages feedback, and synthesizes approvals. The system automatically routes contracts to appropriate stakeholders based on contract type and requirements, tracks review status, and consolidates feedback, reducing the coordination complexity among multiple parties.
Data Source
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AI summary
Contracts are a fundamental tool for coordinating economic activity and need to be managed throughout the lifecycle of contracts. The existing methods are incomplete, expensive, time-consuming, and error-prone. A method and system for management of lifecycle of contracts have been provided. The system leverages a combination of artificial intelligence (AI) techniques appropriate for different micro services in contract lifecycle management. The deep learning and natural language processing (NLP) techniques help in understanding of clauses of the contract, risk levels involved in the contract. The system is configured to automatically generate contracts for a customer based on the other criteria of the customer. The system also identifies alternate options to risky clauses and mandatory clauses to be included. The system is also configured to manage the workflows based on context of contract to seek exception approvals from appropriate stakeholders during contract creation and alert appropriate stakeholders on delivery governance issues.