"Businesses should be prepared for losses they don’t expect" Zywave leader

How mining data can prepare insureds for any potential threats

"Businesses should be prepared for losses they don’t expect" Zywave leader



In order to safeguard insureds from potential losses, it is prudent that brokers and underwriters assess the totality of comparable risks through efficient use of data.

“Businesses should be prepared for losses they don’t expect,” said Jeff Cohen (pictured), senior vice president of Zywave, a software service company providing insurers and insurance professionals with products for agency management, data analysis, compliance, and risk management, among other services.

“By gauging data and understanding how policyholders can be affected by losses suffered from similarly sized business and organizations, brokers can help create a more robust product to prevent any foreseeable losses.”

Cohen spoke with Insurance Business during the RIMS Atlanta event about recognizing the importance of economic losses and the need to be proactive when assessing risks for policyholders.

“Economic losses can really trip a policyholder up”

For a client or business, an insured loss is something that can be prepared for based off of common logistics.

“Say you’re the manufacturer of a water bottle, there are certain things that come with producing that commodity that are expected in some capacity,” Cohen said.

“If the bottle is made out of stainless steel, there’s the potential that an employee in the factory may cut themselves on the raw material during the manufacturing process. If you have to put those products on a truck for transport, there is a chance that it may get involved in a fender bender.”

However, where economic losses come into play is when incidents that are not be planned for but can cause significant business disruption or litigation occur — they are almost never covered by insurance.

“Economic losses can really trip a policyholder up,” Cohen said.

He pointed to certain examples that may lead to these types of cases, such as an employee accusing a coworker of sexual misconduct or a company’s delivery truck striking a school bus and causing damage.

These events, while unanticipated and unexpected, require that there be robust and more specialized insurance coverage to mitigate instances like this from spiralling out of control.

A broker or underwriter can resort to all sorts of data to predict whether a client is at risk of an economic loss.

“An attentive broker would look to data compiled on a software system such as Zywave, which collates jury verdicts, newspaper articles, SEC filings, FOIA requests and other publicly available data, to predict what types of losses can occur based off comparable instances in the past,” Cohen said.

“There is a greater obligation to avoid a calamity before it arises”

For a broker, it is imperative to take a proactive approach to risk management to build a certain level of trust with an insured.

“I’m very enamoured by the classic notion of insurance picking up the pieces in the aftermath of a loss,” Cohen said.

“However, I think there is a greater obligation to avoid a calamity before it arises.”

A broker has the duty to counsel an insured to make them an appealing to a carrier, and one of the best ways to shift to a predict and prevent mindset is by viewing loss holistically.

While it may be easier for a broker to look at the claims history of their clients when assessing risk, a more constructive approach would be analyzing data from a policyholder’s peers that are of similar status, size, geography, etc. and anticipate that their losses, insured or not, are a probability.

“The insured would definitely appreciate the broker taking the time to assess all these variables to provide a more robust insurance barrier,” Cohen said.

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