SBR+Process

Stop-Loss Optimization, Risk Decision Support and Actuarial Services

Risk analysis is part of every decision we make. We are constantly faced with uncertainty, ambiguity, and variability. And even though we have unprecedented access to information, we can’t accurately predict the future. To better understand these risks, SBR utilizes several actuarial and risk decision support tools to help brokers and their clients better assess the impact of risk on a self-funded health plan and allow for better decision making under uncertainty. Some of these tools and resources include: 

SL Advisor 3.0

Strategic Benefit Resources has developed a proprietary stop-loss optimization and decision support tool called SL Advisor 3.0. This tool utilizes Monte Carlo simulation technology and proprietary algorithms to help companies better understand self-funded health plan risk and determine optimal levels of risk retention and risk transfer. 

Actuarial Assistant (powered by Claros)

Detailed modeling of health plan designs, provider network or reference-based pricing (RBP) arrangements, demographic impacts and various risk transfer arrangements. This modeling includes:

  • Values multiple plan changes (plan design, provider network, demographics & stop-loss levels)

  • Produces quick answers and sophisticated analysis

  • Provides details on drivers of change

  • Determines the impact of plan and population changes

  • Simulations: See the impact of adding aggregating specific corridors or health savings accounts to a plan 

Claros Risk Decision Support Modeling (Powered By CLaros)

Sophisticated analysis of the risk/reward tradeoffs in stop-loss structures. This modeling:

  • Assists clients with the decision as to whether the group should transition to self-funding or remain fully-insured

  • Locates the risk structure that meets a group’s risk tolerance level

  • Graphically displays and scores current or proposed risk scenarios versus various other options, illustrating the relative differences in expected return and capital at risk

  • Runs and tests multiple stop-loss scenarios to find the optimal outcome

  • Shows the probability of beating a fully insured program over a 1 year, 3 year and 5 year time horizon. 

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