CPCU 550 Questions & Answers
Data Science
An interdisciplinary field involving the design and use of techniques to process very large amounts of data from a variety of sources and to provide knowledge based on the data.
Big data
Sets of data that are too large to be gathered and analyzed ...
CPCU 550 Questions & Answers
Data Science - answer An interdisciplinary field involving the design and use of
techniques to process very large amounts of data from a variety of sources and to
provide knowledge based on the data.
Big data - answer Sets of data that are too large to be gathered and analyzed by
traditional methods.
Data-driven decision making - answer An organizational process to gather and
analyze relevant and verifiable data and then evaluate the results to guide business
strategies.
Predictive modeling - answer A process in which historical data based on behaviors
and events is blended with multiple variables and used to construct models of
anticipated future outcomes.
Telematics - answer The use of technological devices in vehicles with wireless
communication and GPS tracking that transmit data to businesses or government
agencies; some return information for the driver.
Text mining - answer Obtaining information through language recognition.
Data mining - answer The analysis of large amounts of data to find new relationships
and patterns that will assist in developing business solutions.
Actuary - answer A person who uses mathematical methods to analyze insurance
data for various purposes, such as to develop insurance rates or set claim reserves.
Domain knowledge - answer Information related to the context of the information a
data scientist is working with.
Structured data - answer Data organized into databases with defined fields, including
links between databases
Unstructured data - answer Data that is not organized into predetermined formats,
such as databases, and often consists of text, images, or other nontraditional media
Premium - answer The price of the insurance coverage provided for a specified
period.
Loss adjustment expense (LAE) - answer The expense that an insurer incurs to
investigate, defend, and settle claims according to the terms specified in the insurance
policy.
, Allocated loss adjustment expense (ALAE) - answer The expense an insurer incurs
to investigate, defend, and settle claims that are associated with a specific claim.
Unallocated loss adjustment expense (ULAE) - answer Loss adjustment expense
that cannot be readily associated with a specific claim.
Salvage - answer The process by which an insurer takes possession of damaged
property for which it has paid a total loss and recovers a portion of the loss payment by
selling the damaged property.
Subrogation - answer The process by which an insurer can, after it has paid a loss
under the policy, recover the amount paid from any party (other than the insured) who
caused the loss or is otherwise legally liable for the loss
Text mining - answer The analysis of text for classification and prediction
Point of sale - answer A seamless transaction, documentation, and payment at the
time and place of a sale
Classification tree - answer A supervised learning technique that uses a structure
similar to a tree to segment data according to known attributes to determine the value of
a categorical target variable.
Regression analysis - answer A statistical technique that is used to estimate
relationships between variables.
Cluster analysis - answer A model that determines previously unknown groupings of
data.
Node - answer A representation of a data attribute.
Arrow - answer A pathway in a classification tree.
Leaf node - answer A terminal node of a classification tree that is used to classify an
instance based on its attributes.
Target variable - answer The predefined attribute whose value is being predicted in a
data analytical model.
Linear regression - answer A statistical method to predict the numerical value of a
target variable based on the values of explanatory variables.
Generalized linear model (GLM) - answer A statistical technique that increases the
flexibility of a linear model by linking it with a nonlinear function.
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