COVID-19 requires companies with
self-insured or high-deductible programs to take a new look at their
operations, which may vastly reshape their risk profiles. The degree to which
risk managers can come to new understandings of their changing exposure levels
could have significant effects on current and future liability estimates.
Estimating outstanding claim
liabilities for a self-insured or large deductible program depends heavily on the
exposure levels for the present and recent past. A change in operations alters
a company’s risk profile and can have a significant impact on reserving and
loss projections for the next quarter or year. The larger the change in
operations, the greater the impact on a company’s exposures and claim reserves.
In today’s climate, it is extremely
important to make sure exposure estimates reflect the latest information
available and that any changes in operations have been clearly communicated.
Likewise, when life returns to normal, it will be important to frequently
monitor the resulting increases in exposure levels.
In this article, Milliman’s David Lang explains why estimating the new exposure levels is likely to be difficult for many risk managers.
Companies should try to avoid any conflict of interest when subscribing to the principles under the Sarbanes-Oxley Act. When determining if an actuarial firm is independent, a company can ask two questions: Is the actuarial firm a provider of another service to your company? Does the firm present any possible conflicts?
In the article “Why independence matters in actuarial services,” Milliman’s Richard Frese and Tony Bloemer discuss how actuaries in various roles interact with key decision-makers and the business benefits of working with an independent actuary.
Self-insureds that understand the factors used by actuaries to project workers’ compensation losses can better integrate them into their projection processes and benefit from insightful discussions with actuaries. Milliman consultants Carly Rowland and Richard Frese offer some perspective in the Business Insurance article “Ten considerations for projecting self-insured workers compensation losses.”
A captive insurance program can offer healthcare organizations several benefits such as broader coverage, improved cash flow, and direct access to reinsurance markets. However, not every organization is suited for a captive. Its management must assess the benefits and drawbacks before creating one. Milliman’s Richard Frese provides perspective in his article “Captive insurance: Is it the right choice for your insurance exposures?” He also discusses the background of captives, how organizations should choose a domicile, selecting coverage policies, actuarial analysis for loss projections, and considerations when shutting down a captive.
Self-insureds are experiencing benefits assessing risks and controlling costs using predictive analytics. In this Insight article, Elizabeth Bart discusses how these tools can help self-insureds mitigate claim losses.
Here is an excerpt:
A notable benefit of predictive analytics is that it provides quantitative cost-saving information to risk managers. Continuing with the prior example, assume 2,500 employees are newly hired, low-wage employees in Illinois and their average costs have been shown to be three times higher than the company average of USD $1.50/$100 of payroll. We can estimate that a reduction from $4.50 to $1.50 could create $2.25 million in savings. Asking senior management for $100,000 for more new hire training in Illinois facilities will be much easier with the quantitative support provided by predictive analytics.
(2,500 employees with an average payroll of $30,000 save $3 = 2,500 x 30,000/100 x 3 = $2.25M)
Not only can predictive analytics assist with reducing cost ‘pre-claim’ by focusing on exposure, it can also reduce costs once a claim has occurred. Knowing the easy-to-identify large claims will be second nature to risk managers, however, ‘post-claim’ predictive analytics can look into claim development details to find characteristics that late-developing, problematic claims (and often not the obvious large ones) have in common. After a loss has occurred, one of the most effective ways to manage costs is to involve a very experienced claims handler as soon as possible. The results of effective ‘post-claim’ predictive analyses will assist in implementing cost-saving claims triage. Because the best resource post-claim is good claim management, predictive analytics can get late-developing, problematic claims the timely attention they need to contain the ultimate costs or even settle the claim.
Loss savings based on predictive analyses extend beyond claim cost reduction. Being able to quantitatively show potential savings and concrete mitigation plans will make a positive impression on senior company management and excess insurance carriers. Demonstrating shrewd knowledge of the loss drivers and material plans to reduce the losses can aid in premium negotiations with excess carriers for all future policy years. And if the insurer or state is holding any collateral, the predictive analytics’ results can be used by the self-insured in negotiating.
The key to unlocking further potential cost savings in your self-insured plan is readily available in your own data. Predictive analytics is the tool that will help risk managers make better claim reduction decisions and produce actionable items with real cost savings now and in the future. Risk managers and self-insured companies can look forward to possible benefits such as loss cost reductions along with reductions in excess premium and collateral, and quantitative information to help them with budgeting and allocation. As more self-insureds begin applying predictive analytics to control costs, companies that are not using these tools will be at a competitive disadvantage.
For more perspective on how self-insureds can benefit from predictive analytics, watch this Google Hangout.
Insurance companies capture and store large amounts of data that influence key business decisions. Predictive analytics allows insurers to identify granular patterns in data that can lead to better business practices.
In this Google Hangout, Milliman’s Elizabeth Bart, Michael Paczolt, and Terry Wade discuss how self-insureds can benefit from the use of predictive analytics.
Milliman offers predictive analytics and modeling solutions that produce clear, actionable results, and critical strategic insights. To learn more, click here.