MACHINE LEARNING MODEL FOR PREDICTING LITIGATION RISK IN CORRESPONDENCE AND IDENTIFYING SEVERITY LEVELS

摘要

Systems, methods, and other embodiments associated with detecting severity levels of risk in an electronic correspondence are described. In one embodiment, a method includes inputting, into a memory, a target electronic correspondence that has been classified as being litigious by a machine learning classifier. An artificial intelligence rule-based technique is applied to the target electronic correspondence that identifies high and medium risk level keywords. The technique is also configured to generate a litigious score based on a sum of term frequencies-inverse document frequencies using the remaining keywords. An electronic notice is transmitted to a remote computer over a communication network that identifies the target electronic correspondence and the level of litigation risk.