The Challenges Of Contract Extraction

There is an ever increasing amount of information caused by the advancement of technology in all aspects of the corporate world which impacts everything from daily operations to accessing information in contracts and other documents.

One of the emerging issues with the ever increasing amount of available information is using technology for tasks like contract extraction, which involves finding an identifying specific information in a contract and then compiling the information from any number of contracts into one database for easy searching, sorting and management. Using Artificial Intelligence or Natural Language processing involves the complexity of teaching machines how to think and understand the complexities of the written language.

The challenges of contract extractions would not be complicated if all contracts used identical language that was located in the same spot on every contract. However, that is rarely the case, and different contracts contain a variety of clauses that each contain some element of information that is not consistent with other contracts.

Training the System

In using software platforms that use machine learning or Artificial Intelligence (AI) the software can actually be trained to look for specifics in the contract by being exposed to examples and non-examples of the desired fields. To do so, data must be provided to the machine to begin training the software programs.

There programs use NLP or natural language processing. To train these types of programs we use contracts that are marked to highlight data for the software to recognize as of value or interest.

With all of the learning methods for the software such as NLP, the software is not just looking for numbers or looking for specific words or phrases. Instead, the software has to also recognize the context of the characters as to the relevance that a particular set of words or numbers has in relation to the specific information required.

By using technology in contract extraction, systems become more sophisticated and advanced. Tested and proven software can make the process of contract extraction faster, more efficient and also reduce the risk of errors or omissions by human reviewers.

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