“By 2024, the amount of manual effort for contract review will be reduced by 50% for those that adopt advanced contract analytics solutions.”Gartner Report on Contract Analytics
Current state of Contract Reviews
The departments that are mostly involved in dealing with Contracts are Legal and Procurement and the adoption of the AI tools for contract review is still in a nascent state.
As the contracts are getting more complex and accelerated by Covid-19 to go fully digital, there are several key areas related to business processes and human involvement wherein the Contract Analytics tools can bring in efficiencies from different perspectives.
For example, manually keying in key contract data into an Excel sheet or even into a CLM system is error prone and makes it difficult to keep track of obligations such as renewing the contracts on time, ability to keep track of contracts that are not in force (expired), and preventing unwanted services or licenses getting renewed automatically.
How Artificial Intelligence accelerates contract reviews.
With the new AI/ML/NLP powered platforms, the contractual documents can be analyzed by understanding the structure of the document, clauses that are important for the legal department to manage the risk and meta data that procurement wants to keep track of (Expiry dates, Termination Notice Periods, Volume Rebates, Discounts, Auto Renewals etc.).
One of the use cases that our customers frequently ask is to determine whether a document is fully signed, partially signed and whether all the signatories signed the documents.
This simple use case is critical when a company is doing due diligence during an M&A deal. For the acquiring party, the legal needs to submit all the fully executed contracts and the terms associated with each one of the contracts. The manual intervention required to do this simple task over a contract set of 10,000+ documents would itself takes several months to segregate the documents.
As one can imagine, the document folder may contain Master Service Agreements, NDA’s, Amendments, Addendums, and other supporting documents and all of them needs to be classified and able to establish the lineage and determine the most relevant ones for the legal teams to work with. The complexity of this task increases exponentially based on the size of the deal and number of documents to be reviewed.
The AI based tools using Visual Segmentation (Computer Vision) techniques can help in identifying the signature block and applying pre-trained models can help in quickly determining whether the document is fully signed or not, and the corresponding files can be renamed (Prefixed or Suffixed) with the appropriate status and this can trigger any of the downstream activities needed for further actions.
What is the ROI?
Speeding up the deal velocity
With the help of Artificial intelligence, extraction of relevant data from the contracts and contract reviews can be fully accelerated and automated by doing the heavy lifting. This will help the M&A teams to speed up their work.
Reduction in resource costs
Artificial Intelligence and NLP will perform the deep dive and sifting of the documents which are normally performed by Para Legal teams resulting in reduction of resource costs.
With Artificial Intelligence and Machine learning, efficiency is at its best as the typical human errors are substantially reduced which could normally cause work delays. We, at Docskiff Inc built Smart Contract Analytics (SCA) platform to solve common use cases and pain points related to business contracts at a massive scale using the state-of-the-art ML and NLP algorithms. Please check out more information and use cases on our website: https://docskiff.ai