Bloom Value Corporation

Roona Shree

Arun Hampapur

Sharathchandra Umapathirao Pankanti

Sampoorna Hegde

Venu M Kondle

Megha Kuchhal

Yashpal Gulab Dhawle

Priyanka Rajesh

Blair Bryson

Moumita Dhar

Shravan Conjeevaram

Praveen Guledgudda

Configurations of a system and a method for a dynamic trust-based authorization system (DTBAS), are described. In one aspect, the DTBAS may implement an execution of operations of multiple engines, models, framework, circuits, code, etc., for dynamically authorizing a request for a service or an operation. The DTBAS, when deployed in a managing entity, may receive a request from a managed entity to execute an operation or task. Based on parameters or attributes associated with the managed entity, the DTBAS may execute operations to evaluate a trust score. Based on the evaluated trust score, the DTBAS may compute a weight decision matrix that may include multiple weights associated with the managed entity. Based on the computed weight decision matrix and the evaluated trust score, the DTBAS may authorize or deny the execution of the requested operation.

Dynamic trust-based authorization system

A system and method to authorize requests for procedures or medical claim requests is described. In one aspect, datasets from multiple data sources, including historical authorizations associated with various medical claims, are processed. The machine learning engines and the machine learning models are trained based on the received data. Simultaneously, real-time authorization requests are received and analyzed from secondary data sources. Each request is split into service requests based on second attributes, which include identifiers linked to services. The services are encoded using fixed-length encoding, and unique numeric identifiers are assigned to categorical variables. For each encoded service request, contexts, actions, and decisions are determined by comparing the first attributes of historical authorization requests with the second attributes of real-time requests. Service requests are then categorized into cohorts based on similarity metrics between their second attributes and those of historical authorizations. This comparison enables efficient processing and informed decision-making.

Intelligent authorization system

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Bengaluru, India

Roona Shree