How to mine contracts from unstructured data sources with AI and Machine Learning
By Satish Padala, Senior Director of QTC Products, Live Objects
Companies process a variety of contracts in their business operations. It can be a sales contract, a revenue agreement, a procurement contract, or a legal contract. Authoring a contract with right clauses and obligations is a complex process and requires a lot of manual effort. Many valuable resources are spent in authoring and maintaining these contracts to ensure accuracy and legal compliance. There are contract lifecycle management (CLM) systems available in the market that can streamline the contract processing in an organization. But they cannot address manual touch points in the system that span beyond the scope of the system.
Contracts can come from 3rd party sources, external systems and legacy systems in the form of PDF or word documents. These documents are reviewed by business users and transferred to CLM systems manually. This entire process takes a lot of time and can involve human errors that result in compliance issues and increase the risk. It takes a considerable amount of resources to identify and correct the errors. Many organizations have dedicated resources to manage contracts and handle its complex process. AI and machine learning can learn complex contract process and rules, and maintain contracts accurately.
The Live Objects platform can read and learn contracts data from unstructured sources like pdf and word documents. The AI algorithms will mine the various components of contracts like clauses, T&C’s and obligations, and maintain a repository of contracts in the CLM system. This will eliminate the manual effort to read, understand, and create contracts. Live objects can create orders, invoices and other related transactions from the contracts and link them to the source. This will help reconcile the transactions, renew contracts and manage mid-term contract changes.
