Abstract: A system incorporates a platform for analysis of electronic files relating to an old insurance policy using computer protocols such as visual analytics tools to identify attributes of the insurance policy. A policy migration process automates typically complex custom migrations in a methodical workflow employing a simplified metrics-driven process. Layers of a data migration and policy transformation workflow include source policies layer, normalization layer, and target policies layer. The normalization layer includes an extraction, transformation, and loading (ETL) engine. The ETL engine inputs configuration files that incorporate mapping rules for mapping source policies to normalized values within a data dictionary. Systems of the disclosure incorporate built-in personas that cater migration features to a specific set of migration execution team roles such as policy edit and QA.

Abstract: System and method for automatically calling back a customer via a predictive model determines a plurality of call-back metrics for a plurality of advisor records. The predictive model is applied to call-back data to identify customers that are likely to require a series of call-backs, and automatically generates a preferred call-back to such customers to reduce this risk. The automated call-back may follow termination of an identified customer's inbound call, or at some time after completion of a previous call interaction of the identified customer with an advisor. In the predictive model, a first compilation of call-back metrics record is representative of an overall likelihood of call-backs associated with each advisor record, and a second compilation of the plurality of call-back metrics is representative of a likelihood of call-backs for each of the plurality of products of the enterprise associated with the advisor record.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprises an analytic server, which evaluates user data for premium financing status and dynamically renders graphical user interfaces. The server trains an artificial intelligence model based on historical user data. The artificial intelligence model comprises one or more data points with each data point representing one of a plurality of attributes and applies a logistic regression algorithm to identify a weight factor for each attribute. The server uses a dynamic algorithm to generate a score by combining the plurality of attributes based on the weight factors. The server receives responses regarding the scores that indicate the premium financing status of each case. The server retrains the artificial intelligence model to identify new weight factors based on negative responses data. The server automatically displays new scores calculated based on the new weight factors.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprises an analytic server, which evaluates user data for premium financing status and dynamically renders graphical user interfaces. The server trains an artificial intelligence model based on historical user data. The artificial intelligence model comprises one or more data points with each data point representing one of a plurality of attributes and applies a logistic regression algorithm to identify a weight factor for each attribute. The server uses a dynamic algorithm to generate a score by combining the plurality of attributes based on the weight factors. The server receives responses regarding the scores that indicate the premium financing status of each case. The server retrains the artificial intelligence model to identify new weight factors based on negative responses data. The server automatically displays new scores calculated based on the new weight factors.

Abstract: An attachment assembly including a connector secured to a garment for coupling to a device which is adapted to be worn by a wearer over the garment, such as for body surfing.