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Marsh Canada offers clients access to cargo theft analytic tools


May 30, 2013   by Canadian Underwriter


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Marsh Canada is the latest company to join the CargoNet and National Equipment Register (NER), efforts aimed at preventing cargo and heavy equipment theft and improving theft recovery rates.

Truck

Marsh’s clients will now have access to CargoNet and NER’s data sets and analytical tools, used to detect theft trends and support loss prevention activities, the company announced Thursday.

Related: Cargo theft on the rise in Canada, U.S.: report

CargoNet and NER are data sharing and intelligence systems aimed at fighting cargo and heavy equipment theft. They allow for secure information sharing, analytics and collaboration among theft victims.  Both systems are centered on secure North American databases and information-sharing platforms managed by crime analysts and other experts.

“Many of our clients are concerned about the increase in the instances of cargo and heavy equipment theft,” Matthew Yeshin, managing director of Marsh Canada’s Marine Practice noted in a statement. “We are pleased to be able to offer CargoNet’s and NER’s tools to help them strengthen their loss control strategies and mitigate this risk.”

Both CargoNet and NER are part of Verisk Crime Analytics, a provider of crime-prevention services for retailers, manufacturers, logistics companies, equipment owners, and insurance companies that also offers data and analytical support to law enforcement.

“Effective information sharing by insurers, logistics companies, and equipment owners is critical to reversing the tide of high value property theft in Canada and cross border crime,” David Shillingford, president of Verisk Crime Analytics commented in a statement. “The influence and expertise of Marsh Canada has been a key element of our early progress and we look forward to working together to enhance Marsh’s loss control programs.”

CNA Canada and the Canadian Trucking Alliance have also partnered with CargoNet and NER to help combat theft.


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