7 Best Practices to Employ NLP for Contract Review
Introduction
Contract agreements are believed to be the backbone of any business transaction. They represent a company's prior success, current commitments, and future opportunities. It's in a firm's best interest to create agreements that establish trust, mitigate risks, and enhance overall profitability.
Yet, handling large volumes of contract analysis and creation is one of organizations' most significant challenges. As per a study by Ernst & Young, 89% of organizations find managing high volumes of low-complexity contracts challenging. At the same time, 54% believe that it consumes their essential time that could be spent on other high-value tasks.
Research from World Commerce and Contracting suggests that the average cost of creating a contract with traditional practices is approximately $7000. Large organizations manage up to 350 contracts a week. Therefore, more and more organizations are planning to use automation to reduce the cost of contracting.
This is where automation technologies such as Natural Language Processing (NLP) emerge as game changers. Today, NLP is transforming the legal sphere by expediting the contract drafting and review process.
Below, we unveil the potential NLP holds with AI contract review and analysis while exploring its benefits, use cases, and implementation in contract review workflow. Let’s understand how intelligent AI supports legal teams in the contract management process.
Understanding NLP in Contract Review
NLP has emerged as a transformative force in contract analysis, revolutionizing how legal professionals navigate and interpret complex agreements. To grasp its impact, let's delve into the essence of NLP itself.
What is Natural Language Processing (NLP)?
NLP is a part of artificial intelligence that allows machines to comprehend text and spoken language meaningfully and helpfully.
NLP is introducing significant transformations across numerous industries. But, it’s the legal realm where it has offered remarkable contributions, particularly with contract analysis.
NLP’s Potential to Revolutionize Contract Analysis
Legal firms can automate and enhance their contract lifecycle by incorporating NLP in contract analysis from drafting and negotiation to execution and renewal. NLP can efficiently process and comprehend the intricate language used in legal documents, extracting critical information and identifying relevant clauses with unprecedented accuracy.
Leveraging NLP-driven tools, solicitors can save significant time and resources, minimize risks, and streamline contract processing.
How Can You Use NLP for Contracts?
NLP can process massive data sets from various sources like emails, social media, and reviews, giving businesses valuable insights. This empowers businesses to make informed decisions, helps enhance customer engagement, tailor their strategies to customer needs, and stay competitive in the ever-evolving market landscape.
Benefits of NLP in Contract Review
The use of NLP in contract analysis extends beyond the legal department, significantly benefiting other departments like finance and sales. Combining NLP with contract analysis aids risk management while increasing efficiency and effectiveness.
Additionally, it assists with drafting legal documents, identifying similar contract phrasing, summarizing legal clauses and data, and organizing data systematically based on clauses, ranges, and agreement terms.
Here’s a list of several advantages of employing AI-powered contract analysis.
1. Efficient Contract Drafting and Reducing Repetitive Tasks
NLP promotes coherent contract drafting by offering language suggestions and ensures document consistency. On average, it takes a lawyer 92 minutes to review a single contract as opposed to AI, which does it in 26 seconds.
With thousands of contracts to review, the human process is time-consuming and prone to oversight. Moreover, NLP in contract analysis accelerates document assembly while reducing production costs, ensuring thorough vetting of agreement terms.
SpotDraft is a legal technology startup that has created an AI-based contract management and drafting software. SoftDraft’s CEO and Co-founder, Shashank Bijapur, remarked that SpotDraft “enables law firms to do more for their clients in a shorter period of time.”
2. Streamlined Contract Analysis
NLP tools can detect errors and discrepancies, automating the contract review process. An NLP tool can analyze contracts by adhering to your criteria and suggest corrective actions for clauses that don’t meet expected standards. It can also offer answers to open-ended queries.
3. Accuracy and Compliance
NLP tools are trained to offer precision and compliance with legal standards. They reduce the possibility of errors while maintaining consistency concerning language and phrases across multiple contracts.
4. Enhanced Decision-Making
NLP-powered tools yield invaluable insights by scrutinizing contracts and retrieving structured data from contracts. These insights are fundamental to informed decision-making, allowing legal teams to comprehend contractual obligations, risks, and trends.
5. Managing Complex Contractual Data Sets
AI-driven contract management utilizes NLP to support efficient search and comprehension of legal terminology, preventing misinterpretations and saving time. The extracted data can readily be used due to the contextual analysis conducted in real-time, accelerating agreement analysis.
An NLP algorithm primarily retains knowledge by extracting knowledge from hundreds of thousands of contracts and applying insights from them to new agreements. This distinguishes them as the ultimate contract expert, eliminating biases and disputes over contracting authority.
AI-Powered Contract Management: Use Cases
AI allows law firms to cater to intricate and disorganized contracting tasks, sparing time for pivotal elements like risk management and compliance. AI opens numerous avenues for integrating automation within many contract management workflows.
Here are a few use cases for AI-driven contract management.
1. Searching Contracts and Extracting Insights
Primarily, AI-powered contract management includes reviewing contracts at a large scale and clustering them based on numerous standard and custom metrics.
This encompasses searching and sorting legal contracts with similar terms or clauses, learning their impact on individual contracts, and affecting bulk modifications. A streamlined approach like this helps create contract clusters by determining specific metrics and KPIs while presenting contract anomalies and insights.
2. Contract Clause and Metadata Analysis
AI-fueled contract management involves grouping contract types and orienting them with current templates, learning crucial terms and metadata for distinguishing typical meta-information.
It incorporates training systems to understand custom metadata and scrutinize important clauses for classification, parsing, and mapping with present templates.
The terms and clauses should adhere to organizational processes suggesting fallback and alternative clauses. This is especially important for managing workflows across various stages.
3. Risk Management and Compliance
Contract management with AI means extracting and categorizing obligations from numerous agreements into operational and financial segments. This incorporates accumulating and assessing myriad compliance and regulatory terms, conducting impact analysis with regulatory transitions, and ultimately assisting with risk mitigation.
Mikita Mikado, the co-founder of PandaDoc, commented, “In the realm of contract management, AI isn’t just a technology. It’s the catalyst for a revolution. AI streamlines and leverages every facet of the process, from contract creation to compliance. It’s not just about efficiency; it’s about empowering businesses to make smarter, data-driven decisions. AI transforms contracts into strategic assets, ensuring businesses stay agile, compliant, and competitive in an ever-evolving landscape”.
Implementing NLP in Contract Review Workflow
An advanced use of NLP contract analysis is interpreting clauses and subclauses in documents. By deciphering the context of the contract languages, an AI contract review software powered by NLP can identify numerous issues like vague terminology and time-critical provisions.
Below are ways in which NLP aids the contract review workflow, along with best practices for implementing NLP in this workflow.
4 Ways NLP Enhances Contract Review Workflow
Strategically implementing NLP in contract management increases efficiency and shares insights for informed legal decision-making.
Here are a few tested ways to apply NLP in your contract review workflow.
1. Quick Contract Drafting with ChatGPT
One of the most adopted NLP-powered language models, ChatGPT, can revolutionize how contracts are drafted. Businesses can create rational and systematic first drafts by offering precise instructions.
This allows contract managers to focus on other crucial aspects of contract creation by saving time and resources.
NetApp, an intelligent data infrastructure company, faced a challenge with sponsorship agreements, as their contract review process took a lot of work. Hence, they decided to use LexCheck, an AI-powered contract review software.
After its deployment Connie Brenton, Vice President Law, Technology & Operations, NetApp, observed that “LexCheck eliminated an entire step of the process, reducing what took hours to a matter of minutes while also increasing the quality and consistency of the work.”
Also read: Technology in the Legal Profession: ChatGPT's Use Cases and Challenges
2. Harnessing NLP in Contract Repositories
Efficient contract management can be conducted by keeping them organized and readily available. One can extract essential information, build user-friendly databases, and automate contract categorization using NLP-powered contract repositories.
This assists contract managers to make informed decisions by quickly retrieving their desired information.
3. Continual Progress with Insights and Analytics
Using NLP for contracts, litigators can also widen the scope to learn valuable insights into trends and user behavior. These analytical capabilities can then be leveraged to revamp negotiation strategies, learn areas of improvement, and refine areas of improvement.
Continuous improvement using NLP-powered contract management ensures processes remain agile and efficient.
“Our AI-driven contract management platform enables us to excel at looking into a contract and understanding what’s written on it. Once you understand that, you can automate a lot of functions both upstream and downstream,” says Shashank Bijapur, CEO and Co-Founder, SpotDraft.
4. Superior Document Quality
Expensive legal documents can directly result from inaccurate or ambiguous contracts. NLP offers excellent assistance in showcasing errors, marking inconsistencies and ambiguities, and enhancing the overall quality of contracts.
This assures comprehensive and legally sound contract creation, preventing legal disputes during execution.
7 Best Practices to Employ NLP for Contract Review
Here are the best practices to follow when employing NLP for contract review.
1. Ensure Ease of Use by Selecting the Right NLP Tool
Choosing NLP tools that best cater to your organization’s needs is essential to reap maximum benefits. One must consider scalability, integration, and the types of contracts they handle.
Here are some pointers to consider for making an appropriate selection.
- Do your contracts have complex legal jargon, high volumes, or need faster turnaround times? Discover the challenges you face in contract management.
- Do you use a CRM or document management system? If yes, ensure that your tool offers seamless integrations with existing systems and if it needs additional technical support.
- An NLP tool should be scalable and capable of handling an increasing volume of contracts without compromising performance.
- Select an easy and intuitive tool to foster easy adoption for your team.
- Address your niche contract management needs by selecting a tool that allows customization.
- Examine the utility and effectiveness of the tool by opting for free trials and demos.
- Inquire about the training and customer support offered by the provider. Adequate support can ease the transition to a new tool.
- Weigh the expected benefits like increased efficiency, time, and risk optimization against the cost of the tool.
2. Check Integration with Current Systems
The key to maximizing efficiency is selecting tailored NLP solutions that integrate with your existing contract management processes.
Here are the key pointers to ensure integration.
- Keep an eye out for bottlenecks, routine errors, and repetitive tasks. Identify areas where NLP can add value to your current contract management workflow.
- Ensure the NLP tool is compatible with standard contracts and data. It must be proficient with reading and processing documents for your prominent formats.
- Communicate with IT to ensure your NLP tool aligns smoothly with your existing document storage and CRM systems.
- Within a controlled environment, perform a pilot test of the NLP integration before full deployment. This verifies the tool’s anticipated functionality and aids in detecting potential issues.
- Grant access and permissions to needed team members.
- Once the integration is concluded, monitor how the NLP tool enhances your contract management processes.
3. Train your Team to Use NLP Tools Effectively
Learning the limitations and capabilities of these tools is crucial. Therefore, training your legal and contract management team members is mandatory.
Below are some steps to ensure practical training.
- Devise a training program incorporating the fundamentals of NLP and the unique functionalities of the chosen tool. You can also include analytical examples and use cases relevant to your organization's contracts.
- Incorporate different learning styles in your training module, such as video tutorials, written materials, and hands-on workshops.
- To make your learning process more engaging, leverage actual contract scenarios for your training sessions.
- Ensure your team members know the scope of NLP tools in contract management to avoid access dependency and rely on human judgment where necessary.
- Gather feedback from your team members on their experience with the tool. This open environment can help identify gaps in training, if any.
- Appoint a go-to expert with the most experience working with the tool. This individual can offer ongoing support and tips to fellow team members.
- Assess the effectiveness of the training program by tracking metrics such as error rates, adoption rates, and speed of contract processing.
4. Timely Maintenance of the NLP Tool
Timely maintenance and upgrades are obligatory for accuracy and keeping your NLP updated with advancements in legal standards.
Here’s how you can attend this task.
- Devise a routine timetable for updating the NLP software, including the primary application, supplementary plugins, and additional tools.
- Keep track of legal regulations and standards modifications, ensuring your NLP tools reflect those updates.
- Continually inspect the tool’s performance. Look for any red flags like longer processing times and decreased accuracy.
- Feed your tool with diverse contract data to foster continuous learning and adapting to new languages and contract formats.
- Stay informed about upcoming upgrades by communicating regularly with your tool’s vendor.
- Plan a training session for team members on new features after each update.
5. Monitor Performance and Gather Feedback
To learn how to improve performance using your NLP tool, you must monitor its performance and collect feedback.
Consider these pointers while implementing this approach.
- Establish precise criteria to assess an NLP tool’s performance effectively. These include efficiency gains and minimization of errors in contract handling.
- Conduct regular assessments to know if your tool meets these metrics.
- Another approach to seeking fair assessment would be learning inputs from the team using NLP in contract analysis. Their perspective on your tool’s performance in real-time is invaluable to your objective.
- Design a system where users can easily report issues or propose enhancements. An ongoing feedback cycle can fuel incremental improvements in your tool’s functionality.
- Track the time and purpose for which your team uses the tool. A decreased engagement rate indicates usability issues and the need for additional training.
6. Data Security and Privacy
Contracts can contain sensitive information; privacy is paramount when using any tool.
Consider these guidelines to enhance security measures with your NLP tool.
- Be aware of the data protection laws in their country and industry, such as HIPAA in healthcare and European GDPR.
- Choose NLP tools recognized for adhering to these security and privacy standards. Verify this with compliance badges or relevant certifications.
- Observe any security vulnerabilities by timely auditing the NLP tool and related systems.
- Limit the tool’s access to authorized individuals by enforcing stringent access controls within the tool.
- Ensure all sensitive contract data undergoes encryption with the NLP tool during transit and storage.
- Educate your team members on maintaining data confidentiality and best practices to avoid data breaches.
- Conduct routine assessments with security and compliance if using a third-party or cloud-based NLP tool.
7. Optimize Contract Templates through NLP Analysis and Adaptation
Revamp your contract templates and strategies by employing insights from the NLP tool.
Take note of these tips when putting this into practice.
- Assimilate regular terms, clauses, and negotiation points by analyzing contract data with your NLP tool.
- Revise contract templates using preferred language and clauses that align best with your business objectives by leveraging the above insights.
- Optimize your negotiation strategies by studying trends and outcomes in contract negotiations.
- Learn areas of improvement like frequently contested clauses and misleading terms using NLP data.
- Timely track the impact of insights after you adjust your contract management processes.
- Encourage a culture of continual learning with your team by comprehending data and upgrading strategies using tool insights.
How do you Address the Potential Risks of NLP for Contract Management?
Though NLP does introduce transformative contract management solutions, one must address its intrinsic challenges and risks.
Here’s a list of the commonly overlooked challenges that accompany this transition.
1. Ambiguity and Confusing Legal Terminology
NLP tools are designed for simple language processing. Therefore, convoluted terminology and vagueness can be a challenge.
Alternatives:
- Keep the NLP systems updated with case law and legal dictionaries so that they can quickly grasp the latest legal terminologies and phrases.
- Develop specialized language models tailored for the legal domain, incorporating nuances and formats in legal documents.
- Employ advanced NLP techniques that analyze and grasp the context and intent behind legal clauses.
2. Data Privacy and Security
Data privacy and security are legitimate concerns due to sensitive data when using tools. In today's time, when data breaches are persistent, tackling this challenge becomes crucial.
Alternatives:
- Select NLP tools that comply with data protection regulations like HIPAA, GDPR, and other industry-specific laws.
- Safeguard data in transit and at rest using robust encryption methods, ensuring restricted access to unauthorized personnel.
- Set stringent authentication protocols for your NLP tool.
- Learn potential security weaknesses in the NLP system by conducting timely security checks.
3. Excess Dependency on NLP Tools
One can overlook critical nuances with their excess dependency on NLP tools. This oversight could result in misinterpretation.
Alternatives:
- Your contract review process must comprise NLP tools and human review.
- Make your team understand the importance of manual review for contracts and the limitations and capabilities of NLP systems.
4. Staying Updated with Technological Upgrades
AI technologies such as NLP are evolving too fast. Therefore, it’s necessary to stay updated with the latest developments. Your incapability to do so might result in outdated NLP systems.
Alternatives:
- Help your legal team stay updated on the latest AI and NLP developments by encouraging a culture of continuous learning.
- Proactively upgrade your NLP systems with the latest features and improvements.
- Perform timely audits with your NLP systems to learn their effectiveness and make needed improvements to foster technological advancements.
Conclusion
Contracts are imperative in today’s business landscape, and NLP has proven to be an essential ally. NLP offers excellent assistance with analyzing vast amounts of information and identifying key insights and critical nuances. This tech also facilitates improved decision-making, risk assessment, and compliance. With NLP, legal teams can concentrate more on other vital aspects of their work by streamlining the contract review process.
However, it’s essential to understand the subtle line between human expertise and technology, acknowledging that NLP tools don’t replace human prowess but rather complement it.
Future advancements in natural language processing promise more intuitive and innovative tools that will reshape legal tech for the better. The advances in this technology are anticipated to revolutionize contract analysis with increased precision in deciphering complex legal language.
In today’s day and age, embracing NLP tools isn’t just an option but a necessity for law practitioners to gain a competitive advantage over firms following traditional practices.
We at Maruti Techlabs have significant experience and expertise in crafting NLP solutions that are finely tuned to law firms' niche necessities. Our expertise is not limited to developing generic NLP applications but extends to devising solutions that foster contextual understanding in analyzing legal contracts.
Contact us today to explore how AI-powered NLP solutions can elevate your contract analysis processes.
