Abstract: A computing system can implement a cognitive-based risk mitigation service. The system can train and test a correlation model using a cognitive assessment test (CAT) distributed to control base users. The control base users may further provide access to motor vehicle records such that the system can determine a set of correlations between cognitive health metrics tested by the (CAT) and vehicle accident risk as indicated by actual accident data in the motor vehicle records. Once a threshold level of accuracy is attained, the correlation model may be executed on response data from inquiring users taking the CAT to determine motor vehicle risk of those users without them providing access to their motor vehicle records. This motor vehicle risk may then be used to generate a risk mitigation policy package for the inquiring user.

Abstract: A computing system can implement a health verification and prediction service by generating an interactive user interface through which users can provide responses to health assertions in one or more trivia sessions. Each of the health assertions can include a correlation value to actual health outcomes based on responses received from individuals a control group and the known health outcomes of those individuals. Based on the responses from the user, the computing system can generate a health profile for the user.

Abstract: A computing system can execute a correlation model for a library of health assertions to configure a correlation value for each health assertion. The correlation value comprises a correlation between knowledge associated with the health assertion and known health outcomes of individuals in a control group who have also provided responses to the health assertions. The computing system provides a health trivia session for users and based at least in part on the performance of the user, generates a morbidity risk profile that is used to classify the user in an underwriting class.

Abstract: A computing system can implement a risk-assessment service through execution of a health lab data classifier model that classifies a prospective client's clinical health lab data, comprising a set of health aspect levels, within a set of health aspect ranges. When the set of health aspect levels of the prospective client are within a set of health aspect ranges, the computing system can generate one or more risk-mitigation packages at a particular tier of the risk-assessment service.

Abstract: A computing system can implement a health verification and prediction service by generating an interactive user interface through which users can provide responses to health assertions in one or more trivia sessions. Each of the health assertions can include a correlation value to actual health outcomes based on responses received from individuals a control group and the known health outcomes of those individuals. Based on the responses from the user, the computing system can generate a health profile for the user.

Abstract: A computing system can execute a correlation model for a library of health assertions to configure a correlation value for each health assertion. The correlation value comprises a correlation between knowledge associated with the health assertion and known health outcomes of individuals in a control group who have also provided responses to the health assertions. The computing system provides a health trivia session for users and based at least in part on the performance of the user, generates a morbidity risk profile that is used to classify the user in an underwriting class.

Abstract: A computing system can implement a health verification and prediction service by generating an interactive user interface through which users can provide responses to health assertions in one or more trivia sessions. Each of the health assertions can include a correlation value to actual health outcomes based on responses received from individuals a control group and the known health outcomes of those individuals. Based on the responses from the user, the computing system can generate a health profile for the user.

Abstract: A computing system can execute a correlation model for a library of health assertions to configure a correlation value for each health assertion. The correlation value comprises a correlation between knowledge associated with the health assertion and known health outcomes of individuals in a control group who have also provided responses to the health assertions. The computing system provides a health trivia session for users and based at least in part on the performance of the user, generates a mortality outcome profile that is used to classify the user in an underwriting class.

Abstract: A computing system can execute a correlation model for a library of health assertions to configure a correlation value for each health assertion. The correlation value comprises a correlation between knowledge associated with the health assertion and known health outcomes of individuals in a control group who have also provided responses to the health assertions. The computing system provides a health trivia session for users and based at least in part on the performance of the user, generates a mortality outcome profile that is used to classify the user in an underwriting class.

Abstract: Examples described herein include a computer system to obtain social network content from a user, and to analyze the social network content to determine one or more attributes. The computer system predicts a lifestyle category of the user based at least in part on the determined one or more attributes.

Abstract: A computer system automates the determination of a health profile of a user based on a knowledge of the user regarding health related questions and social network content from an account of the user.

Abstract: A computer system prompts a user to answer a series of questions from a collection of questions. From the user's answers, the computer system predicts a mortality outcome based on the value of a predetermined mortality parameter for one or more of the questions in the series.

Abstract: A computing system can implement a health verification and prediction service by generating an interactive user interface through which users can provide responses to health assertions in one or more trivia sessions. Each of the health assertions can include a correlation value to actual health outcomes based on responses received from individuals a control group and the known health outcomes of those individuals. Based on the responses from the user, the computing system can generate a health profile for the user.

Abstract: A computer system prompts a user to answer a series of questions from a collection of questions. From the user's answers, the computer system predicts a mortality outcome based on the value of a predetermined mortality parameter for one or more of the questions in the series.

Abstract: Examples described herein include a computer system to obtain social network content from a user, and to analyze the social network content to determine one or more attributes. The computer system predicts a lifestyle category of the user based at least in part on the determined one or more attributes.

Abstract: A computer system automates the determination of a health profile of a user based on a knowledge of the user regarding health related questions and social network content from an account of the user.

Abstract: In a system and method for evaluating and comparing variable annuities, ranking and comparison of annuities and their guaranteed riders is performed by coding the performance of the annuities into a computer model based on the behavior of one or more annuity products as described in a prospectus. A user is provided with a computer interface to input his/her preferences and then view anticipated performance. The anticipated performance is based on one or more validated scenarios of future market performance. The output is in part based on showing the total value of two or more different annuities over time as a bar chart. Each bar presents the total withdrawals to date in a lower portion and the cash surrender value as a top portion.