9 steps to simplify contract management with digital documents
It is said that contracts are the lifeblood of today's business transactions. Contracts represent companies' past successes, current obligations, and future opportunities. As companies grow - by building relationships with suppliers, partners, customers, and new employees - it is in their best interest to create agreements that foster trust, mitigate risk, and increase overall profitability.
However, one of the biggest challenges organizations face is dealing with a large volume of contracts, and with between 20,000 and 40,000 active contracts, a typical organization has too many contract data points to reconcile. This unfortunately results in a contracting process. Ineffective, but artificial intelligence (AI) and machine learning are changing the way contract management functions are performed.
Here's how AI-powered contract management of documents helps legal teams succeed.
Digital documents and their benefits for contract management
Digital documents, or intelligent document processing systems, use advanced algorithms, such as neuro-linguistic programming (NLP), optical character recognition (OCR), and ICR, to analyze and extract vital information from various documents, including contracts and legal texts. These technologies simplify document processes. Manage corporate contracts, improve accuracy, and provide valuable insights by automating contract creation, review, and analysis, metadata extraction, search and retrieval, risk assessment, and analytics. Let us now learn about the most important benefits:
1. Increase productivity
Performing manual tasks in corporate contract management distracts from strategic and impactful business initiatives. Contract managers often spend significant time manually searching, organizing, extracting and updating contract information and data.
However, with the advent of artificial intelligence, manual tasks that included redlining, approvals, contract review, and more are now obsolete, allowing contract managers to devote their time to more important matters. Automation in corporate contract management solves tedious manual data entry and information retrieval processes. And expensive, it enables contract managers to access necessary information within seconds, eliminating the need for hours or even days of manual effort.
2. Intelligent contract analysis and risk mitigation
Intelligent document processing tools analyze contracts and identify clauses that may pose risks to the parties involved. They detect clauses that exhibit ambiguous language, inconsistencies, or deviate from industry standards.
For example, when reviewing rental agreements, the platform's AI-powered analysis can identify provisions that may pose risks or deviate from industry standards, and can flag ambiguous language or contradictory provisions that could lead to potential disputes between landlord and tenants. This early disclosure allows the real estate company's legal team to review and refine terms to ensure clarity, fairness, and compliance with legal and regulatory requirements.
3. Accelerate the contract life cycle
Document AI accelerates the contract lifecycle by automating tasks such as extracting data from contracts and creating notifications for important milestones and renewals. This automation streamlines the process, removes bottlenecks, and ensures contracts are executed on time.
Furthermore, its centralized platform enhances collaboration and communication between contracting stakeholders, for example, multiple parties involved in the review process, such as legal teams, finance teams and borrowers, access and review loan agreements simultaneously.
4. Audit trails and version control
A document management system creates robust audit trails and controls the version of contracts. It accurately records and monitors all contract-related activities such as creation, modification and approval. It captures essential details such as timestamps and user information, creating a transparent and accountable record of changes and actions. Such accountability and transparency ensures Contract management: A clear view of the development of contracts over time.
5. Improve data security and compliance
Unlike traditional methods of storing documents in file cabinets, spreadsheets, drives and across disparate sources, document AI ensures secure storage by leveraging encryption and access controls. It protects sensitive contract data from unauthorized access, reducing the risk of a data breach. Or leaked.
Organizations can also achieve enhanced document compliance. Its privacy features comply with security regulations such as CCPA and GDPR. Pre-trained algorithms manage and protect personally identifiable information (PII) within contracts, ensuring compliance with data privacy laws.
DocSuite's document management system provides many benefits for contract management, including:
Organizing documents: It contributes to arranging and organizing contracts effectively, making them easy to access and search for.
Easily share documents: Contracts and related documents can be shared quickly and effectively between different members of the team.
Improved Collaboration: Enhances cross-team collaboration with simultaneous shared access and editing of documents.
Tracking amendments: It allows tracking of amendments made to contracts, which makes it easier to understand the history of amendments and updates.
Saving time and effort: reduces the time spent searching for contracts and increases administrative efficiency.
Enhanced Security: Provides document protection and encryption capabilities to keep information confidential and secure.
Improve strategic management: System reports and statistics can be used to support management decisions and improve operations.
Accessibility across various devices: Allows users to access contracts and documents from anywhere using a variety of devices.
Backup History: Provides a backup system for important documents to ensure they are not lost in the event of a problem.
Compliance with laws and regulations: Contributes to compliance with laws and regulations related to the preservation of records and information.
How to use digital document management systems
We show you a step-by-step guide to the optimal use of digital document management systems:
Step 1: Set goals
Clearly define your goals for AI document implementation. Define specific use cases where AI documents will be applied, such as contract review and analysis, renewal tracking, data mining, search and retrieval. It helps you plan scalability, integration, and train machine learning models appropriately.
Step 2: Evaluate data sources
Assess the availability and condition of your existing document data. Check if documents are already in digital formats or require conversion. It helps ensure quality and potential limitations for training AI models.
Step 3: Select the compatible document AI tool
When evaluating different AI document management tools, consider accuracy, execution time, ease of use, integration, and most importantly, straight through processing (STP) rates. A reasonable STP rate ranges from 90% to 95%, according to industry standards.
Consider your company's budget and requirements as you evaluate your options, consider business size and scale, and ensure that the software results in a positive ROI.
Ask potential vendors about pricing tiers based on features and scalability. You also need to determine if there are additional fees for training and technical support.
Step 4: Prepare and name your document data
It is essential to evaluate the integrity, organization, and relevance of the data to avoid errors and enhance model accuracy. Identify and label key data points such as customer names, dates, and financial terms to automate the extraction process.
Step 5: Choose the learning algorithm
Select a learning algorithm (supervised or unsupervised) based on the specific tasks and goals within a corporate contract management process. While supervised learning algorithms learn patterns and make predictions based on labeled examples, unsupervised learning is more suitable for exploratory data analysis and pattern discovery. Via unlabeled data.
Step 6: Train and fine-tune the AI model
Adjust and optimize various model information, such as complexity, learning rate, regularization, etc. By leveraging techniques such as feature engineering and hyperparameter tuning, you can improve the model's accuracy and performance while maintaining control over various aspects of the learning process.
Step 7: Deployment and Integration
Once the best-performing models have undergone extensive testing, they are ready to be deployed into a production environment where they can continuously learn from live data. This process involves integrating the trained model into larger systems, such as web or mobile applications or existing CRM platforms.
The deployment process is affected by available data, hardware resources, and DevOps practices. In a deployment environment, performance, scalability, data movement, security, and version control are essential to ensure optimal deployment.
Step 8: Implement security and compliance measures
Establish robust security measures to protect sensitive document data, implement access controls, encryption and data privacy protocols, ensure compliance with relevant regulations, such as GDPR or industry-specific guidelines.
Step 9: Monitor the solution
It is essential to continuously monitor the performance, accuracy and effectiveness of the solution. This includes tracking key metrics and gathering feedback from users and stakeholders to identify areas for improvement.
Step 10: Provide training and support
Provide comprehensive training to users who will interact with the digital document system, educating them on how to utilize its features effectively. Provide ongoing support to address any questions, issues or improvements needed. Allow them to take charge of designing the workflow and creating a feedback loop.
Doc Suite has made great efforts to implement features that contribute to the effectiveness of contract management, as it has developed a system that allows companies to better organize and follow up on their contracts, through:
Secure storage of information: Providing a safe and protected environment for storing corporate contracts and related documents, which reduces the risk of data loss and ensures compliance with security standards.
Effective electronic management: Facilitating electronic contract management processes, including electronic signature and digital authentication, which contributes to accelerating the contract approval and signing processes.
Advanced Organization and Indexing: Providing powerful organization tools that allow users to seamlessly index and classify nodes, making it easy to search and access important information at any time.
Tracking changes and updates: Providing a means to track the history of amendments to the contract, which helps in understanding changes to agreements and obligations.
Integration with other systems: Achieving effective integration with other company systems, such as human resources management systems or accounting systems, to ensure the flow of data between the various departments of the company.
In this way, DocSuite has developed innovative solutions to improve corporate contract management by providing tools that contribute to improving efficiency and transparency in this context.
Digital document management systems offer significant benefits for managing corporate contracts, streamlining processes, improving efficiency and enhancing accuracy. Organizations can automate corporate contract analysis and data mining by leveraging advanced technologies such as Neuro-Linguistic Programming (NLP), Machine Learning (ML), and Optical Character Recognition (OCR). Leveraging them enhances accountability, visibility, security and compliance.
However, successful implementation requires data source assessment, comprehensive testing, and seamless integration. Through continuous monitoring and continuous improvement, document AI is revolutionizing contract management, improving workflow and enabling informed decision-making.