Understanding Contract analysis and review
Contract Analysis is a process of understanding what is within your contracts. The main purpose behind trying to understand the ingredients of any contract is to see what are your organization’s obligations with respect to the contract being analysed and what are the associated risks for the organization in the event of failing to perform these obligations.
Most organizations refer this as Contract Review, and this is most likely performed by either an external legal counsel or using in-house legal teams. The normal contract review process happens either when you are authoring a fresh contract with your customer, supplier or vendor or when you are accepting third party paper. In both these cases the reason for review is to figure out if any of the contract clauses are deviating from the standard templates and if yes how much are they deviating and if that is reasonably acceptable.
The process of reviewing or analyzing contracts has been a manual task for a long time which involved going over huge number of documents, understanding large volumes of text to elicit specific information pieces like a date, price, contract value, payment terms, force majeure clause details etc and this is quite time consuming, tedious and pricey.
Adoption of Artificial Intelligence in contract analysis
In the recent years, technologies like Artificial intelligence started being used in contract analysis processes and software which made automatic retrieval of key metadata from contract documents possible and within minutes. In addition, adoption of Machine learning (ML) for Natural language processing (NLP) has seen a lot of success in accurately performing tasks which were only done by humans.
The technologies got further enhanced with the introduction of Deep learning which can get a lot deeper into your contracts. For example, consider a use case of your legal department wanting to know how many of your contracts have a termination of convenience clause which can get your business into risk. Similarly, if your supply chain department wants to know what is the lead time for a particular material from various available suppliers or your sales department want to understand how many customers have a 60 day payment terms as against the normally accepted 30 days. Without using technology this process could take considerable amount of manual effort but with the help of deep learning this process can be fully automated.
So, Contract analysis software that adopts these high impact technologies like AI and ML can quickly learn from the data samples and provide valuable insights. The ability to get a quick snapshot into the contract metadata helps in organizations efficiency and productivity
Let us do a little bit dive into how this whole process of contract analysis using AI and ML works
There are different techniques within Artificial intelligence and machine learning that can be applied to any business for achieving process automation which also includes contract management process. On a high level there are two types of approaches namely rule based, and training / learning based. Most contract analysis software’s that adopt Artificial intelligence and machine learning will follow one of these approaches.
Here is a flow of the different technologies used for analyzing contracts
Optical Character Recognition (OCR)
OCR process is typically applied to printed documents or scanned executed contracts that are unsearchable. OCR has the ability to recognize letters and words and convert these characters to text that can be further fed to a Natural Language Processing (NLP) Engine
The NLP Engine can process the text fed from an OCR or any other digitization process to apply meaning to the text. By way of pre-training an NLP engine all necessary key contract terms can be recognized to identify if any particular contract has non-standard language. Further all identified issues can be automatically routed to be reviewed and corrected
Computer Vision (CV)
This technology is used to understand if the executed contracts have been appropriately signed at the right places and if the signature matches with one on the file ideally to prevent possible fraud.
Deep Learning can be applied to dive through volumes of contracts to identify connection between contracts, as well as correlate the contracts with outcomes.
Advantages of using an AI powered Contract Analysis software
Any organization that need to understand what is inside their contracts quickly and efficiently from tens of thousands of executed contracts can reap the following benefits by using any Artificial powered contract analysis software.
- Extract Metadata from any type of documents (word, PDF, Image etc)
- Document OCR capability with ability to convert images, unsearchable PDF and scanned documents into text.
- Export the extracted data to Excel or client desired format and push the extracted data into any CLM or downstream system
- Generate dynamic ML models based on the contract type
- The Platform can segregate the contracts based on the type of the contract (i.e. MSA, NDA, SOW etc.)
- Ability to rename the contracts – standardize naming conventions if needed.
- Powerful semantic search across the contracts
- Compare two executed contracts of the same type to show differences and also provide clause scoring.
- Compare executed contracts with the standard template at a section/clause level
- Hierarchical mapping of the contracts assuming enough linkage attributes are available within the executed contracts