Abstract: The present disclosure relates to systems and methods for optimizing benefits plan options offered by an organization through balancing derived population preferences with organizational preferences by analyzing historical selections made by individuals. Census data dividing members of an organization into census divisions may be applied to machine learning algorithm(s) to derive estimated selection preferences of the members. Using selection preferences, costs of various product offering scenarios and overall member satisfaction estimates of the scenarios may be calculated. Product offering scenarios meeting member preference criteria and organizational budget criteria may be presented for review.

Abstract: In an illustrative embodiment, methods and systems for cybersecurity assessment of an organization's technology infrastructure include identifying features of the technology infrastructure and automatically generating a threat profile relevant to both the technology infrastructure and the organization's business (and/or business objectives), where the threat profile includes potential threat actors and threat scenarios applicable to the technology infrastructure. The methods and systems may include evaluating cybersecurity controls of the organization's technology infrastructure in light of the threat profile to identify and rate vulnerabilities within the technology infrastructure.

Abstract: In an illustrative embodiment, systems and methods using an agri-food risk tracking and management platform can provide risk mitigation in a food supply chain based on aggregated risk data for each of a set of suppliers in the food supply chain. Aggregate governance and compliance data may be aggregated for the set of suppliers, including data for each supplier relating to inspections, citations, and/or regulatory compliance. Ingredient risk factors may be determined, using trained data models, for supplier food product ingredient(s). The data models may be trained using industry food data, where the risk factors are determined based on historic food born illness data corresponding to attributes of the industry food data. Based on historical governance and compliance performance data, a governance and compliance score representing the relative performance of the set of suppliers may be determined.

Abstract: In an illustrative embodiment, systems and methods for calculating risk scores for locations potentially affected by catastrophic events include receiving a risk score request for a location, the risk score request including a request for assessment of risk exposure related to a type of catastrophic event. Based on the type of catastrophic event, a data compression algorithm may be applied to a catastrophic risk model representing amounts of perceived risk to an area surrounding the location. In response to receiving the risk score request, a risk score for the location may be calculated that corresponds to a weighted estimation of one or more data points in a compressed catastrophic risk model. A risk score user interface screen may be generated in real-time to present the catastrophic risk score and one or more corresponding loss metrics for the location due to a potential occurrence of the type of catastrophic event.

Abstract: The present disclosure relates to systems and methods for optimizing benefits plan options offered by an organization through balancing derived population preferences with organizational preferences by analyzing historical selections made by individuals. Census data dividing members of an organization into census divisions may be applied to machine learning algorithm(s) to derive estimated selection preferences of the members. Using selection preferences, costs of various product offering scenarios and overall member satisfaction estimates of the scenarios may be calculated. Product offering scenarios meeting member preference criteria and organizational budget criteria may be presented for review.

Abstract: In an illustrative embodiment, methods and systems for integrating web content generated by a content management system (CMS) with dynamic content generated by a content development system include an API handler of the CMS configured to communicate an action received from a remote computing device to a web part, where the web part interfaces with both the CMS and a web application framework to coordinate response to the action and to inject information regarding the dynamic content into the web content for use by the remote computing device. The remote computing device may include a view provider module configured to access the dynamic content using the injected information.

Abstract: Automated systems and methods for implementing and managing the submission, quote, proposal and binding stages (i.e., placement process) for securing insurance coverage.

Abstract: Systems and methods for matching subscribers with subscription providers include gathering, via a network from one or more remote computing systems, claims data, performance data, and service data regarding a number of providers; determining, by processing circuitry of a computing device based on the claims data, the performance data, and the p service data, one or more provider metrics for each provider of the number of providers; calculating, by the processing circuitry based on the one or more provider metrics, one or more relationships between a number of subscribers and each provider of the plurality of providers; and ranking, by the processing circuitry, the number of providers based at least on part on the one or more relationships.

Abstract: In an illustrative embodiment, systems and methods for providing subscription product recommendations can identify, from trained data models, cost-driving factors impacting costs of subscription products offered by a provider. The data models can be trained with claims data from a member population with multiple years of claims data. The cost-driving factors can correspond to attributes of the claims data in a first year that predict future costs in a following year. Requests for product recommendations include responses to questions each associated with a cost-driving factor. Based on the responses, the member can be mapped to a cluster grouping associated with a projected cost to the member for a subscription product. Recommendations can be generated based on an economic equivalent score for each subscription product reflecting the respective projected cost and one or more adjustment factors indicating an impact of one or more qualitative factors on subscription product selection choices.

Abstract: In an illustrative embodiment, methods and systems for identifying prospective new clients based upon review of current clients include accessing a book of business of a user of a transactional platform to identify current clients, identifying, key terms relevant to each of the clients, automatically performing Internet searches, each search using different groupings of the key terms, automatically deriving from web sites of the search results information regarding a number of prospects, and presenting prospect information to the user. The key terms may be identified through performing web searches and web scraping of online information related to the current clients. The clients may be categorized based upon organizational attributes prior to searching. An initial set or sets of key terms may be filtered through performing a number of data analyses on the key terms.

Abstract: In an illustrative embodiment, systems and methods for calculating risk scores for locations potentially affected by catastrophic events include receiving a risk score request for a location, the risk score request including a request for assessment of risk exposure related to a type of catastrophic event. Based on the type of catastrophic event, a data compression algorithm may be applied to a catastrophic risk model representing amounts of perceived risk to an area surrounding the location. In response to receiving the risk score request, a risk score for the location may be calculated that corresponds to a weighted estimation of one or more data points in a compressed catastrophic risk model. A risk score user interface screen may be generated in real-time to present the catastrophic risk score and one or more corresponding loss metrics for the location due to a potential occurrence of the type of catastrophic event.

Abstract: Automated systems and methods for implementing and managing the submission, quote, proposal and binding stages (i.e., placement process) for securing insurance coverage.

Abstract: Systems and methods for matching subscribers with subscription providers include gathering, via a network from one or more remote computing systems, claims data, performance data, and service data regarding a number of providers; determining, by processing circuitry of a computing device based on the claims data, the performance data, and the p service data, one or more provider metrics for each provider of the number of providers; calculating, by the processing circuitry based on the one or more provider metrics, one or more relationships between a number of subscribers and each provider of the plurality of providers; and ranking, by the processing circuitry, the number of providers based at least on part on the one or more relationships.

Abstract: In an illustrative embodiment, methods and systems for cybersecurity assessment of an organization's technology infrastructure include identifying features of the technology infrastructure and automatically generating a threat profile relevant to both the technology infrastructure and the organization's business (and/or business objectives), where the threat profile includes potential threat actors and threat scenarios applicable to the technology infrastructure. The methods and systems may include evaluating cybersecurity controls of the organization's technology infrastructure in light of the threat profile to identify and rate vulnerabilities within the technology infrastructure.

Abstract: In an illustrative embodiment, systems and methods for automatically identifying peer organizations of a subject organization within a transactional platform identify peer organizations of the subject organization by accessing characteristic features and transactional features of the subject organization, providing a portion of the features to similarity analysis models, and obtaining, through executing the models, predicted peer organizations. The predicted peers may be presented to a user arranged in priority order with some peer features of the respective organization and a control for selecting the respective peer. The user may select a subset of the predicted peers for use in comparison metrics.

Abstract: Methods and systems for automatically estimating expenses related to property damage caused by at least one catastrophic event may include identifying properties in a geographic region, determining property values for the properties and a customized event loss vector format corresponding to preferences of a user (preferred event model vendor, particular financial perspective, property value scaling factor, etc.), and executing catastrophic event models for the catastrophic event(s) to generate an exposure data set representing estimated losses for each property. The methods and systems may include, for each property, determining an estimated amount of physical damage, calculating an equity position estimate and analyzing it to determine likelihood of mortgage default, and, where likely, calculating an estimated loss due to default. The exposure data set and the estimated loss may be formatted in the customized event loss vector format and added as a row of a loss matrix.

Abstract: In a preferred embodiment, a system for securely delivering source data to a destination system over a network includes a data manager system operatively connected to the network, where the data manager system includes circuitry configured to receive a public key from the destination system, generate a random session key, encrypt the session key with the public key using a public key cryptosystem, divide the source data into a number of chunks, compress each of the chunks, merge all of the compressed chunks into an assembled file, encrypt the assembled file with the session key using a symmetric-key cryptosystem, divide the encrypted assembled file into a number of parts, send each of the parts to the destination system over the network, and send the encrypted session key to the destination system over the network.

Abstract: In an illustrative embodiment, systems and methods for coordinating automated, real-time data sharing and updating between participants using disparate data formats for information transfer include a messaging interface for receiving message initiation requests including messaging data from regionally-distributed computing devices. The message initiation requests may be queued as queuing data in a global message queue. Updates may be made to the queuing data indicating a status of the message initiation requests based on reply messages received from message recipients. A message transmission system may transform the messaging data into a generic data object that is agnostic to messaging formats of a sending computing system and a receiving computing system. The generic data object may be mapped to a message format associated with the receiving computing system.

Abstract: In an illustrative embodiment, systems and methods for predicting subscriber churn include machine learning algorithm(s) for classifying the subscriber's decision to stay with the present subscription provider or to switch (churn) to a new provider. The machine learning algorithms may include a logistic regression/neural network for modeling churn propensity in subscribers. The churn risk analysis systems and methods may identify a group of subscribers most likely to churn. Further, the churn risk analysis systems and methods may identify a group of subscribers least likely to churn. The identified subscribers may be presented to a representative of the subscription provider, for example through a user interface.

Abstract: The present disclosure relates to methods and systems for accelerating the development and distribution of data science workloads, including a consistent, portable and pre-configured data science workspace for development of data science applications allowing for the creation of a standardized, modular and reusable library of data science code product that can be maintained, extended and reused in a clear and repeatable manner. The code may be submitted to a build and deployment process that ensures consistency across multiple environments in terms of the application code and the operating system environment. Runtime execution may be managed through the authoring of definitions which detail aspects of how the workload should operate within a certain environment.