Managing contracts is a key aspect of business management. Your contracts help govern your relationships with clients. They outline your responsibilities to one another. More importantly, contracts contain valuable data you can use to improve your business over time.
Advanced contract analytics is a process that combines artificial intelligence with machine learning technology. Together, these technologies can extract and analyze contract data. This real-time data analysis can provide business owners with actionable insights. The insights, in turn, give you a competitive edge in your industry.
How Advanced Contract Analytics Work
Advanced contract analytics leverage AI technology. The process combines machine learning technology with natural language processing (NLP) to extract and analyze contract data. Advanced contract analytics can be broken into three key steps: contract extraction, data standardization, and pattern and discrepancy identification.
Using NLP To Extract Information
NLP helps work through historical and active contracts. Using tools like entity recognition and semantic analysis, NLP identifies key contract information such as:
Parties involved in a contract
Contract terms
Obligations
Deadlines
Pricing
NLP algorithms break the text into structured data. This makes it easier for contract AI software to analyze and interpret the information in the next step of the process.
Using Contract Intelligence Software To Standardize Data
After extracting the data, the contract intelligence software standardizes and categorizes it. The goal of this step is to make the analysis step easier on the AI system.
Imagine, for example, having multiple contracts that involve dates. On some contracts, the dates are written out as Month, Day, Year. Others have the date written in MM/DD/YY format. And still other contracts have it written in MM/DD/YYYY format.
The standardization process would put all of these dates in the same format. This makes it easier to manipulate the data later.
Using AI Technology To Check for Patterns and Discrepancies
Once data has been standardized and classified, the contract analysis process really begins. The contract analytics software scans the information, analyzing patterns and checking for discrepancies.
When the software notices patterns or discrepancies, it highlights that information for users. You can use AI-generated reports to improve risk management, inform business decisions, and update future contract clauses. AI can also help you perform predictive analysis and make forecasts about the future.
How Advanced Contract Analytics Enhance Business Operations
Contract management analytics do a few major things, including:
Making contracts more visible
Identifying pain points before they become major problems
Ensuring businesses are compliant with local and federal regulations
Optimizing contract lifecycle management
Let's take a closer look at the role of AI contracts and contract analytics in each of these tasks.
Improve Contract Visibility and Management
Advanced contract analytics digitize and centralize contract data. This provides you with a better understanding of your contract portfolio.
Organizing thousands of contracts would be next to impossible using manual processes. Contract review software makes it a manageable task. Document AI can even sort by contract type or contract cycle times. This level of organization makes these centralized portfolios incredibly useful for organizations. Users can search, retrieve, and track them with the touch of a button.
Imagine, for example, if a legal department received new regulatory compliance standards. Previously, the staff would have to review each contract for legal information. Then, they'd have to update the relevant legal documents.
When contract data is organized, legal departments can simply search the centralized database for relevant information. This allows them to update relevant documents quickly and effectively.
Advanced contract analytics also improves collaboration with key stakeholders. By digitizing contracts and centralizing data, your organization can help teams collaborate. Teams can access contracts remotely and asynchronously. This allows them to collaborate on contract reviews and negotiations. Meanwhile, blockchain technology protects sensitive or proprietary information.
Identify and Mitigate Risks Proactively
Advanced contract analytics allow you to proactively identify risks, minimizing the impact of those risks on business operations.
Document AI algorithms analyze contract language and terms to detect inconsistencies, including:
Conflicting clauses
Ambiguous language
Differences between contractual obligations and actual performance
By flagging these inconsistencies early, document AI algorithms help your business address potential problems before they arise. This allows you to avoid costly legal challenges.
Advanced contract analytics software can also perform predictive risk analysis to anticipate future challenges. Document AI algorithms do this by analyzing historical contract data and market trends. The algorithms then identify patterns, which can help point to potential risks, such as:
Supplier performance issues
Market fluctuations
Regulatory changes
In this case, forewarned is forearmed. Based on these insights, you can develop contingency plans. These proactive strategies can help safeguard your interests and minimize potential losses.
Ensure Regulatory Adherence Across Contracts
Legal teams can use AI to analyze contracts. By doing this, they can identify places where contracts may not be following regulatory standards.
Document AI algorithms carefully review contract language and terms. Then, they flag potential compliance issues for review and correction. Legal teams then look into the contracts based on this flagged information.
This proactive approach helps organizations like yours stay ahead of regulatory changes. As legal requirements evolve, your business can keep up with them and stay in compliance.
Legal teams can also use advanced contract analytics in other ways. For example, the software can help them develop contract templates from the ground up. Doing this means they can make sure contracts adhere to regulatory standards. This helps legal teams prevent liabilities down the road.
Incorporating regulatory requirements into contract templates and leveraging AI-driven contract generation tools can help you minimize compliance risks and prevent liabilities.
Optimize Your Contract Lifecycle Management (CLM)
The advanced contract analytics process integrates seamlessly with contract lifecycle management (CLM) systems. This helps you automate and streamline the entire contract management process.
One of the ways advanced contract analytics optimize CLM is by automating workflows. It does this in a few different ways, including:
Using predefined templates
Incorporating approval workflows
Integrating with electronic signatures
Using automated notifications and reminders to reduce bottlenecks and delays
All of these processes can accelerate contract creation, negotiation, and approval cycles. This keeps the CLM as efficient as possible.
The analytics software also uses historical contract data, market trends, and best practices to improve the contract negotiation process. AI algorithms can analyze negotiation patterns, identify optimal terms, and recommend negotiation strategies. This helps you get the most out of both new contracts and contract renewals.
Future of Advanced Contract Analytics
Advanced contract analytics software is a cutting-edge, AI-powered technology. It's designed to help businesses like yours leverage existing contracts and historical data. Doing this makes your business more efficient and effective.
As a leading AI-as-a-service company, Terzo is here to help your business make the most of advanced contract analytics. If you’re ready to set arduous, manual processes aside, Terzo is here to help. We offer streamlined, cost-effective strategies for managing contracts. Contact our sales team today to reduce business risks and improve business forecasting.
