Collections in grace
The grace-period book sorted by days left, with deadline, payment method and the date of each insurer's data.
A premium nobody saw in time and a renewal nobody followed up cost more than a lost sale. orbit retention reads every insurer's payment status each night, builds the day's queue by value at risk and runs campaigns measured against a control group. It is still in development: the platform runs end to end on a demo book, while insurer connectors and messaging are still simulated.
An intermediary working with several insurers finds out who paid by logging into each portal, one at a time. The grace-period book lives in spreadsheets, the call to the client depends on someone remembering, and renewals get handled after they have already lapsed. Nobody knows whether the reminder campaign worked or the client would have paid anyway. And since the insurer's bonus is calculated on paid premium, every premium that drops unnoticed hurts twice: in the book and in the commission.
A multi-tenant platform for insurance intermediaries that syncs payment status with each insurer every night, moves premiums and policies through their life cycle on the legal clock, opens cases ranked by value at risk, runs campaigns with a control group, flags carousels on the same vehicle and projects commissions and bonuses on paid premium.
From the nightly sync to the closed case, with every rule in plain sight.
Every night it reads each insurer's payment status and shows how old that data is, insurer by insurer. If one goes past the threshold without updating, its collection campaigns pause on their own and resume when the data comes back.
Premiums and policies move from in grace to lapsed to reinstatable at the 12:00 deadline on day 30, without anyone marking them by hand.
One case per client with each policy broken out, ranked by value at risk and likelihood of recovery. Campaigns run with a holdout, and every message is checked again for consent, time window and contact cap the moment it goes out.
AI reads the payment receipt the client uploads without touching coverage status. Every contact, parameter change and decision goes into a chained audit log, and each campaign's effect is measured against its control group.
orbit retention does not collect money. It doesn't retry charges, create its own payment links or set up direct debit: it informs, points to each insurer's payment channel and logs reported payments without changing coverage until the insurer applies them. Data is from the previous day, not real time. It doesn't call anything fraud either: on a carousel it reports a detected pattern and a person decides. In the current environment the insurer connectors are simulated and campaign effects are a simulation assumption; the real effect will be measured with a holdout in live operation.
The modules that exist in the platform today.
The grace-period book sorted by days left, with deadline, payment method and the date of each insurer's data.
One case per client, with priority explained factor by factor and each insurer's payment channel at hand.
Preliminary and effective renewal tracked apart, non-renewal reasons from a closed taxonomy and a comparison at indicative prices.
Declarative audiences, channel playbooks and lift with a confidence interval. Whatever doesn't go out is logged with the rule that stopped it.
Carousel detection: the same vehicle moving across insurers, one unpaid grace period after another, with a VIN timeline and an explainable score.
Bonus bands projected on paid premium, a retroactive versus marginal bonus simulator and versioned agreements that never rewrite history.
Five differences from chasing premiums portal by portal.
Request demoEvery screen shows the date of each insurer's data, and collections stop on their own when that data can no longer be trusted.
Every message is checked again on its way out: if the client paid between the nightly sync and the morning, it never goes out.
Every campaign carries a control group. Without enough holdout, the result shows as not attributable.
The queue ranks by value at risk and likelihood of recovery, and every factor that adds or subtracts is visible inside the case.
Deadlines, thresholds and templates change from settings, with a reason and an audit trail. AI agents have autonomy levels and a kill switch.
An honest comparison between chasing premiums by hand and retaining the book with each insurer's own data.
Built for intermediaries who sell through several insurers and across all lines. The insurer is still the one that collects.
One queue for the book across every insurer, with commission calculated on what was actually paid.
Consent, time windows and contact caps enforced on every message, plus a per-client contact file ready when a complaint comes in.
Persistency at 3, 6 and 12 months by channel, set against each channel's acquisition cost.
In 30 minutes we'll tell you whether orbit retention fits your process, what it integrates with and what it doesn't, and what a pilot looks like. If it doesn't fit, we'll tell you that too.
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