How LLMs drive information analysis and compliance validation in contract management

Authors

Jesus M. Olivera

Senior AI Engineer, IBM

Large language models (LLMs) are revolutionizing contract management. They provide advanced capabilities to extract entities, validate requirements and enhance overall process efficiency. For example, a legal analyst ensuring contract compliance can use generative AI (gen AI) and retrieval augmented generation (RAG) to streamline the evaluations. By ingesting the contract and relevant internal policies, the system enables efficient contract-to-policy analysis.

Efficient contract management is crucial for maintaining a competitive advantage in today’s fast-paced business world. Contracts govern vital relationships, obligations and compliance between organizations. LLMs help legal teams and business leaders manage the volume and complexity of these documents.

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Extracting information from contracts: Methods and applications

Extracting critical information such as parties, dates, payment terms and clauses from non-standardized contracts requires sophisticated methods. LLMs provide several ways to handle this complexity.

1. Generating embeddings and using RAG

LLMs can generate embeddings, which are numerical representations of text. Converting contract clauses and terms into these embeddings allows for deeper analysis. Embeddings help identify similarities between different sections of contracts, even when the wording differs but the intent is the same.

Returning to our legal analyst example, using embeddings with RAG allows interactive querying of the contract. The legal analyst can ask questions such as, "What is the scope of the indemnification clause?" or "Are there exclusions for third-party claims?"

The artificial intelligence (AI) retrieves relevant sections and summarizes responses in plain language, quickly pinpointing key details. This method improves accuracy by consulting a broader knowledge base beyond the contract itself.

2. Relying on rule-based extraction using business process automation

In certain scenarios, organizations might rely on rule-based systems for extracting specific elements from contracts. LLMs, when integrated with business process automation, can follow predefined rules to search for key-value pairs, such as party names, contract start and end dates and payment amounts.

This method is valuable for standardized contracts or forms where the location and structure of information are consistent. For instance, a rule-based extraction system identifies whether critical clause elements exist and meet a defined internal standard. The system evaluates if the indemnification section includes duration, comparing this element against an internal policy benchmark.

If discrepancies arise, such as a missing duration, the AI flags it for further review. By using the LLMs’ entity recognition capabilities, this predefined field can be efficiently extracted and validated with high precision. This method is ideal for templated documents with regular patterns, streamlining contract review processes for bulk contract uploads or template-based agreements.

3. Validating contract requirements based on internal policies

Information extraction is just one part of the puzzle. Beyond identifying terms and clauses, organizations need to help ensure that contracts comply with internal policies and regulatory requirements. LLMs can validate whether certain contractual clauses exist and meet predefined standards.

For example, contracts might need to include specific indemnification terms as outlined in a company’s internal policy. LLMs can compare contractual content against these guidelines to help ensure compliance. Using RAG, the AI also enables a dynamic dialogue with the contract.

Analysts can interrogate the document interactively, asking nuanced questions such as whether the termination clause includes appropriate notice periods or whether confidentiality clauses align with internal standards. This validation process reduces the risk of noncompliance and protects organizations from potential legal challenges.

IBM watsonx empowers contract management

IBM watsonx™ provides advanced AI capabilities for automating manual contract review tasks, extracting relevant entities and validating content based on predefined policies or regulatory standards. The platform can efficiently classify, extract and validate contract elements, helping to ensure alignment with internal policies while maintaining the ability to interrogate the contract interactively for nuanced insights.

By tailoring its features to align with an organization’s specific contractual frameworks, IBM watsonx streamlines contract management processes, reduces human error and increases operational efficiency.

The application of LLMs in contract management offers transformative possibilities. From extracting key entities through embeddings, RAG, rule-based approaches and key-value pairs to validating contract compliance with internal policies, LLMs unlock tremendous value for businesses.

In an era where legal and compliance teams are overwhelmed with manual tasks, LLMs offer a path to automation and enable professionals to focus on higher-value work. The future of contract management is here, powered by advanced AI capabilities that make complex tasks simple and scalable.

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