Developing a Strategy for Reducing Your Total Cost of Casualty Risk

To effectively manage total cost of casualty risk, businesses must look at a variety of cost elements, according to speakers on Marsh’s The New Reality of Risk® webcast.

Casualty risk represents about 60% of a typical company’s total cost of risk, but can vary depending on several factors, said Chris Flatt, leader of Marsh’s Workers’ Compensation Center of Excellence. Although most businesses have historically focused mainly on insurance costs, calculating total cost of casualty risk generally includes examining five key elements:

• Retained loss.
• Claims management costs.
• Risk transfer premiums.
• Collateral.
• Implied risk, or unexpected loss potential.

“Considering these five elements generally provides a good starting point for calculating total cost of casualty risk,” Flatt said. Once that calculation is completed, businesses can look at specific cost drivers and prioritize where improvements or gains in efficiency can be realized.

In order to reduce individual elements of total cost of casualty risk, businesses can take several steps. Examples include:

• Using loss projection models to project potential losses at different retention levels. “By examining the projected spits between retained losses and risk transfer, you can determine the most beneficial retention structure for your organization,” said Annette Sanchez, a senior vice president at Marsh Risk Consulting.

• Using analytics to evaluate claims outcomes, rather than judging third-party administrators on upfront fees only. “About 90% of workers’ compensation claims costs are variable — so simply comparing the transactional costs associated with claim and medical management addresses only a small fraction of your true spend,” Sanchez said.

• Differentiating your risk profile to better position your company’s risk with underwriters. For example, insurance buyers could present auto liability insurers with evidence of training programs designed to combat distracted driving or identify common causes of auto collisions.

• Using analytical tools to negotiate paid loss credits to reduce insurer collateral requirements. Such tools can be used in concert with a broader analysis of legacy claims, which can help to release redundant collateral in prior years.

• Focusing on pre-loss mitigation and operational risk activities to reduce risk volatility and implied risk. For example, quality control programs that aim to identify and resolve product defects can help avoid large-scale or catastrophic casualty claims.

During each step of the risk management process — including risk identification, transfer, retention, and mitigation — data and analytics are critically important. “Using data, statistical modeling, and financial modeling in each of these areas can help a company measure and subsequently monitor progress, and more effectively managing these costs,” said Steve Jones, a senior vice president in Marsh Global Analytics.

Listen to the webcast replay.