Financial services
AI collections case study
Collections at scale, without growing the team.
Collectors called whoever came first, not whoever mattered most.
- 100,000+
- contacts a month
- US$2.4M+
- annualized value
1The situation
What the operation faced
Collectors called whoever came first, not whoever mattered most.
2What we did
How Boldr AI fixed the process first
- 1
Queue by risk and value
not by memory
- 2
Agents on repeatable contacts
reminders, links, promises
- 3
Collectors on what matters
negotiation and hardship
- 4
Promises tracked
broken ones escalated
3Built with
Capability, solutions and products used
4Results
Measured results
100,000+contacts a month
US$2.4M+annualized value
Measured against the baseline taken at the start. Client name withheld; references on request.
Next step
Could this work in your operation?
Define the scope in minutes. We turn your answers into a focused Value Discovery Sprint.
Scope your sprint
in three questions.
Pick the capability. Your answers tell us where a Value Discovery Sprint would look first; a value consultant comes back with a proposed scope.
Your readout
Your answers shape the scope.
A sprint would likely look first at:
- Repeat reasons to fix
- Requests an agent can resolve
- After-hours demand