All businesses are run at a
risk. Risk is the way business is managed. Every decision an organization takes
impacts the risks an enterprise can withstand like the risk of customer
defecting, of not responding to an expensive glossy mailer or offering a huge
retention discount to a customer who was not leaving even otherwise and in turn
missing out on a critical customer who leaves.
The data driven means to
compute risk of any type of negative outcome in general is predictive analysis.
Insurance companies have used this very well. Insurance companies are
augmenting their practices by integrating predictive analysis in order to
improve pricing and selection decisions.
The
actuarial methods that enable an insurance company to conduct its core business
perform the very same function as predictive models: Rating customers by chance
of positive or negative outcomes.
Predictive modeling improves on standard actuarial methods by incorporating
additional analytical automation, and by generalizing to a broader set
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