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 Post Denmark uses Palisade's @RISK to reduce insurance premiums
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Author Topic: Post Denmark uses Palisade's @RISK to reduce insurance premiums  (Read 959 times)
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Post Denmark uses Palisade's @RISK to reduce insurance premiums
« Posted: October 22, 2007, 05:44:05 PM »


Post Denmark, the national postal service company in Denmark, is using @RISK from Palisade (www.palisade-europe.com) to reduce its insurance premiums, following risk analysis consultancy from PricewaterhouseCoopers (PwC).

Post Denmark inputs data from every insurance-related incident that has occurred over the past ten years into Palisade's @RISK analysis tool which calculates how likely each is to happen in the future, as well as the severity to Post Denmark if they do.  The outcome gives the company a clear understanding of the chance of a vast range of accidents happening, as a result of which it is able to underwrite a large part of its own risk which means lower insurance premiums.

Ulrik Mester, risk management consultant at Post Denmark, explains:  “Because we record every accident that has happened, in the past we have been fairly confident that the insurance premiums we had been paying were right.  However, we wanted to move this up a level and be more certain that we were investing our funds in the most cost effective way for the organisation.  @RISK has helped us to do this.”

Post Denmark must insure itself against losses resulting from events such as post office robberies, theft and fraud.  It also has to take into account anything that will increase employment costs, such as industrial accidents involving its postmen and women and legislation.   In addition it must have cover for damage, both actual and third party, related to its fleet of vehicles as well as its buildings and property. 

Frank Lyhne Hansen, PwC consultant, explains:  “Post Denmark had been meticulous in collecting data relating to every eventuality against which it must insure itself.  @RISK extracts true value from this information because it quantifies the risk faced by the organisation in a measurable format.  The technical sophistication of @RISK enables models to be built that reflect complex scenarios and are straightforward for users to deploy and interpret.”

Mester concludes: “The combination of our data and @RISK's technology has given us the confidence to predict exactly what risks we face, as a result of which we do not need to pay so much for our insurance.”

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