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Predictive modelling is utilised in vehicle insurance to assign risk of incidents to policy holders from information obtained from policy holders. This is extensively employed in usage-based insurance solutions where predictive models utilise telemetry-based data to build a model of predictive risk for claim likelihood. [citation needed]
Predictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. [1]
Prescriptive analytics is the third and final phase of business analytics, which also includes descriptive and predictive analytics. [2] [3] Referred to as the "final frontier of analytic capabilities", [4] prescriptive analytics entails the application of mathematical and computational sciences and suggests decision options for how to take advantage of the results of descriptive and ...
Credibility theory. Credibility theory is a branch of actuarial mathematics concerned with determining risk premiums. [1] To achieve this, it uses mathematical models in an effort to forecast the (expected) number of insurance claims based on past observations.
Type of format. Predictive modelling. Extended from. XML. The Predictive Model Markup Language (PMML) is an XML -based predictive model interchange format conceived by Robert Lee Grossman, then the director of the National Center for Data Mining at the University of Illinois at Chicago. PMML provides a way for analytic applications to describe ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Health care analytics is the health care analysis activities that can be undertaken as a result of data collected from four areas within healthcare: (1) claims and cost data, (2) pharmaceutical and research and development (R&D) data, (3) clinical data (such as collected from electronic medical records (EHRs)), and (4) patient behaviors and preferences data (e.g. patient satisfaction or retail ...
Actuarial science is the discipline that applies mathematical and statistical methods to assess risk in insurance, pension, finance, investment and other industries and professions. Actuaries are professionals trained in this discipline. In many countries, actuaries must demonstrate their competence by passing a series of rigorous professional ...