Catastrophic claims surface too late
By the time an episode is visible as a high-cost claim, the opportunity to steer site of care or route to a center of excellence has usually passed.
Solutions / Stop-Loss
Exposure tracked all year,
not rebuilt at renewal
Stop-loss runs on the claims data you already load. Six agents watch high-cost claimants, aggregate and specific position, and emerging catastrophic episodes, and pass what they find to renewal pricing.
The problem
What gets
in the way
Aggregate position is reconstructed, not tracked
Knowing where a group sits against its attachment point mid-year requires assembling data that exists in several places and reconciling it by hand.
A quote arrives without its reasoning
Challenging a renewal means rebuilding the carrier’s analysis from your own data, under time pressure, every year, for every group.
How we solve it
What we do
about it
It runs on claims you already load
The same feed that drives payment integrity drives this. If you are already running claims through PulseSync, there is no second integration.
Six agents share what they find
An early catastrophic warning reaches renewal pricing on its own, so the analyst pricing the renewal is working from the same signal as the analyst watching exposure.
Position is tracked, not reconstructed
Aggregate and specific position update continuously through the year, so renewal starts from a number you have been watching rather than one you assemble in two weeks.
What you get
What changes
for your team
- Emerging catastrophic episodes are flagged before they mature into claims, while steering is still possible
- Aggregate and specific position are tracked continuously rather than assembled at renewal
- The six agents pass signals to each other, so an early warning reaches renewal pricing without anyone re-keying it
- You can validate a carrier quote against your own evidence and price a counter from it
- It runs on the same claims data as payment integrity, so the data is already there
The agents
6 agents
do this work
Each one is trained, tested and audited on its own, built from the same skill library and governed the same way as everything else on the platform.
Who uses it
Next step
See it on your
own data
We run your historic records through the agents and show you what each one finds, with its evidence, before anything is switched on.