Data Analytics: Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life

parts, which are elaborated upon below:
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Data Sources
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Data Scrubbing

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Back-testing
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Predictive Model
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Risk Selection Analysis
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Interface with Company Systems
Data Sources: The system assimilates with six external sources of data
(such as class action lawsuits and other financial material), and the data is
acquired through executive company applications. The external sources are
frequently utilized by the D&O industry. In the case of Freedom Specialty
Insurance Company, they have exclusive sources to contribute to their
predictive model. Freedom in particular occupies a lot of time with
acquiring and retaining valuable information regarding merchant activities.
Classification and back-testing expose merchant flaws, as well as
inconsistencies in their information. Freedom exerts extra time and energy
into collaborating with merchants to catalogue information and maintain it
at a high worth. Freedom also keeps a close watch on their external data,
applying stringent inspections to develop policy and claims information.
The company upholds data liberty from merchants’ identification schemes.
Although it takes more effort to decipher values, the process safeguards that
Freedom can promptly terminate business with certain merchants if
necessary.
Data Scrubbing: Upon its delivery, information undergoes many
“cleaning” processes, which assures that the information is able to be used
to its maximum ability. For example, there is a review of 20,000 separate
class action law suits per month to observe if any variations have occurred.
They were originally classified by different factors, but now they are gone
through monthly. In the past, before the automated system was put into
place and the process needed to be carried out manually, the process took
weeks to finish. Now, with the modernized methods and information
cataloguing devices, everything can be completed within hours.
Back-testing: This is one of the most important processes, and determines
the potential risk upon receiving a claim. The system will use the predictive
model to run the claim and analyze the selection criterion, altering
tolerances as required. Upon being used numerous times, the positive
feedback loop polishes the system.

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