To control costs and optimize insurance availability anoverwhelming number of risk managers feel their organization mustconduct deeper research into their risk to reap the full benefitsof analytics, according to an online survey taken by insurancebroker Marsh.

Nearly 80 percent of risk managers attending a Marshwebinar, "Using Data and Analytics for Optimal RiskManagement," says their companies need to take a closer examinationof risk-related data.

Of companies employing a risk manager, close to 44 percent saythey do not have a set dollar-amount threshold for unexpectedlosses and 29 percent do not know if their company is aware of howmuch risk they can take on—about the same number that do quantifyand share risk information with their insurance managers.

"When it comes to property risk, the market is driven by netcatastrophe exposure for wind, earthquake and flood," says RyanBarber, Marsh's Property Practice managing director. "Not only isthe quality of that data important, but also its completeness. Inits absence, [catastrophe] models will default to cautiousassumptions that can distort underwriting perception, inflatepremiums and reduce available capacity."

Risk analysis, which predicts how natural and human-causedcatastrophes will endanger property and business production, canhelp align the risk department's loss-mitigation expertise withcorporate growth objectives. 

"We use our analytics for internal discussion with leadershipfor the foundation of our [risk] program strategy," says MichaelMulray, manager of insurance programs for General Electric, whichrecently revamped its Workers' Compensation program. "We went toour actuaries and asked them to tell us the perfect amount ofinformation needed. We focused on the concentration of employeerisk at our individual locations."

Mulray says GE didn't take time to review data qualityabout three years ago, when the company last revised its Workers'Comp strategy. During its last review, however, Mulray's departmenttook a "deep dive" into analytics to incorporate information aboutsite security, shift work, and the number of employees at anylocation at all times.

"The outcome was quite amazing, because in some locations,overall estimated loss dropped by over 50 percent," he says. "Ifunderwriters had the wrong data and used it to make decisions onpricing and structure, they would be misleading management aboutwhat their true risk is."

Not only did targeting location-specific data add credibility tothe risk department's role in corporate decision-making, he says,it led to savings in premiums as well.

Digging into data is crucial for large corporations, such as GE,which have complex layers of coverage and can suffer if a singleunforeseen, or "black swan," event derails the manufacturing andtransportation process, but it can also benefit smallercompanies.

"Smaller companies are just as engaged [in analytics] as largerones," says Claude Yoder, head of Global Analytics at Marsh. Hesays the dollar amounts may be smaller, but they will still derivethe same amount of benefit from the analysis.

"Because GE is large, the issues we face with data and analyticsare different from those faced by small companies," says Mulray,"but it is important for them to understand that we all use thesame principals, regardless of size."