AI-driven contractual compliance process ensures third-party compliance with applicable regulations across multiple authoritative sources and automatically assesses the impact of regulatory changes on contracts.
Artificial Intelligence (AI) driven technologies can handle large data sets with speed and accuracy. Their ability to produce reliable and accurate information consistently has transformed organization’s Contract Lifecycle Management (CLM) process to be efficient, effective, and agile.
AI is an umbrella term that includes related techniques such as Machine Learning (ML) and Deep Learning (DL). ML is a subset of AI. ML algorithms ‘learn’, ‘revise’ and get better with new information. DL is a subset of ML that simulates a human brain by using complex artificial neural networks to process large datasets. They are particularly useful for high volumes of unstructured data such as unstructured text, images, video, and audio files.
The complexity and challenges associated with the current state of contract compliance can be efficiently addressed using Deep Learning techniques for analysis and prediction. Organizations are finding great merit in creating a data lake from both structured and unstructured data and using deep learning techniques for analysis.
AI driven systems aid organizations by playing a major role in simplifying and interpreting regulations, monitoring changes on the horizon, and improving the agility of its Contract Lifecycle Management program.
AI applications can read, interpret, and provide actionable insights with speed and accuracy not possible through manual methods. These applications possess superior ability to scan the regulatory horizon and continuously monitor for upcoming changes. They are slowly replacing traditional and manual third-party monitoring checklists to preemptively identifying compliance gaps and avoid potentially expensive non-compliance penalties.
Artificial Intelligence (AI) can enable firms to identify regulatory requirements and help them ensure that their regulatory requirements are traced to their risk and compliance taxonomy.
Process of tying regulatory requirements to Risk and Compliance taxonomy, aka business obligations, policies, procedures, controls, risks and metrics....