Stop-loss pricing often relies heavily on 50% reports and disclosure requirements to project future risk, particularly in the case of catastrophic claims. However, this static approach can lead to missed opportunities for carriers and financial strain for employers. High-cost claimants from the past year may not remain significant cost drivers, while emerging risks from previously low-cost members often go unnoticed. This creates inefficiencies that limit carriers' ability to price competitively and employers' ability to secure manageable renewal rates.
Small group captives-employer groups that band together to self-fund and share risk-are particularly well-positioned to benefit from a forward-looking approach to catastrophic claims. Predictive analytics can help captives identify potential high-cost claimants across their pooled populations, enabling them to negotiate better terms with stop-loss carriers and optimize retention levels. By leveraging collective data, captives can also smooth volatility, preserve capital, and improve the financial stability of their participating members.
This session will explore how innovative tools and collaborative strategies can help carriers, brokers, and employers-especially small group captives-address these challenges and unlock sustainable growth.
At the conclusion of the session, attendees will be able to:
Understand the limitations of traditional stop-loss pricing methods for catastrophic claims.
Identify key predictive metrics to assess future high-cost claimants.
Explore unique opportunities for small group captives to manage risk collaboratively and negotiate competitive stop-loss pricing.
Develop strategies to implement dynamic pricing models that balance competitiveness and margin preservation.
Foster collaboration across stakeholders to improve renewal strategies and minimize risk.