Bank of America Corporation

Lonnie Jason Carter

Lisa Matthews

Cris Jay Gwin

Theresa Kruse Leahy

Aspects of the disclosure relate to controlling enterprise software policy compliance assessment processes based on quantum combinations of assessment elements. A computing platform may receive an assessment dataset and may generate a time-independent requisite work dataset. The time-independent requisite work dataset may include assessment information identifying a plurality of real branded assessment quanta and priority information identifying a plurality of priority scores. Each priority score of the plurality of priority scores may correspond to an assessment quantum of the plurality of real branded assessment quanta. The computing platform may optimize the time-independent requisite work dataset by aggregating related assessment quanta associated with the plurality of real branded assessment quanta, and this may produce a prioritized schedule of application assessment quanta. Subsequently, the computing platform may generate and send a plurality of non-overlapping assessment prompts based on the prioritized schedule of application assessment quanta.

Controlling enterprise software policy compliance assessment processes based on quantum combinations of assessment elements

The present disclosure is directed to a novel system for using a distributed blockchain ledger to conduct, manage, and store application assessment data. In particular, computing systems may be used to perform assessments on the various applications within the enterprise environment and store the assessments as data records within the blockchain. The entity system may further comprise one or more blockchain interjectors which may trigger the addition of updated data records for one or more application assessments in the blockchain. In this way, the system provides for a highly efficient way to perform application assessments.

Blockchain system for assessment and management of assets

Aspects of the disclosure relate to dynamically filtering and analyzing internal communications in an enterprise computing environment. A computing platform may receive communications data associated with electronic messages sent by various enterprise users. Subsequently, the computing platform may identify a subset of the communications data as being sent by a first enterprise user. Next, the computing platform may apply a grounded theory model to the subset of the communications data to produce a set of psycholinguistic parameter sub-scores, which the computing platform may map onto a plurality of predefined character traits to produce a user-specific character trait set. The computing platform may set a user-specific risk identifier based on the user-specific character trait set and may process communications data associated with other users. Then, the computing platform may apply an anomaly density evaluation and may produce and/or send a dataset that includes a prioritized list of high risk enterprise users.

Dynamically filtering and analyzing internal communications in an enterprise computing environment

Embodiments of the present invention provide a system for monitoring and addressing events based on triplet metric analysis. In some embodiments, the system transmits control signals to cause a vendor database system to continuously monitor a vendor database for a new data input and, in response to identifying the new data input, automatically transmits the new data input back to the system. From the new data input, the system may identify actors, actor values, means, means values, assets, and asset values associated with certain events. The system may then determine a model based on the new data input and transmit control signals configured to cause a computing device system associated with a user to display a three-dimensional representation of the model.

Growing community of inventors

Kingwood, TX, United States of America

Lonnie Jason Carter