High risk passage automation in a digital transaction management platform

A non-transitory computer-readable storage medium storing instructions that, when executed by a hardware processor, cause the hardware processor to:

• access a training set of information including training documents within a document execution environment, each training document including one or more passages, the training set of information is separated into a positive training set and a negative training set, wherein the positive training set includes a subset of document passages, associated passage types, and associated risks designated as above a threshold level of risk, and the negative training set includes another subset of document passages, associated passage types and associated risks designated as below the threshold level of risk;
• train a machine learning model based on the accessed training set of information, the machine learning model is trained to determine a level of risk associated with a document passage based at least in part on the passage type of the document passage;
• modify the training set of information based on a feedback received to indicate an accuracy of a level of risk determined by the machine learning model for one or more passages;
• and
• re-train the machine learned model based on the modified training set of information.

An apparatus, comprising:

• a hardware processor;
• and
• a non-transitory computer-readable storage medium storing executable instructions that, when executed by the hardware processor, causes the hardware processor to:
• receive a first document within a document execution environment, the first document to include multiple document passages;
• apply a trained machine learning model to determine a level of risk associated with a first document passage of the first document based on at least in part on a passage type of the document passage, the trained machine learning model has been trained using a training set of information including training documents within the document execution environment, each training document including one or more document passages, the training set of information is separated into a positive training set and a negative training set, wherein the positive training set includes a subset of document passages, associated passage types, and associated risks designated as above a threshold level of risk, and the negative training set includes another subset of document passages, associated passage types and associated risks designated as below the threshold level of risk;
• determine whether the level of risk associated with the first document passage exceeds a risk threshold by more than a threshold amount;
• in response to determining that the level of risk associated with the first document passage exceeds the risk threshold, identify a second document passage of the same passage type and related to the first document passage within a second document within the document execution environment, the second document passage not exceeding the risk threshold;
• automatically perform a mitigating action associated with the first document passage in response to the determined level of risk exceeding the risk threshold by more than the threshold amount;
• and
• present the first document passage on a first portion of a graphical user interface (GUI) of an electronic device and the second document passage on a second portion of the GUI of the electronic device.