01
Regulated-entity readiness
SOC 2 Type II compliant, GDPR in progress, a controller-processor DPA, role-based access, and every conversation backed up for audits.
Collections, dunning, and research for regulated fintech
Boom runs collections and research conversations at scale, reads your own database, and hands sensitive cases to a person.
Built for a regulated balance sheet
The work that moves the numbers in fintech
Prove it is safe to run, get more of your book to pay, and learn why the rest does not.
02
Early-stage collections as an art
Payment reminders and promise-to-pay flows, written to lower the risk of a blocked number, with a person for hardship.
03
Dunning by decline reason
Insufficient funds, an expired card and a do-not-honor decline each get their own message and timing, not one generic retry.
How your data is handled
Your customers’ PII stays in your database, not a CSV
Boom reads what it needs from your database or API at run time, so there is never a CSV to export, email or lose.
- PII read from your DB or API, never a CSV
- Role-based access and encrypted credentials
- Delete or export a customer’s data on request
When a number is not enough
A real back-and-forth on getting paid, with a human for the hard cases
Give Boom a goal in plain words: it reads each reply, adapts, and hands the case to your team when someone is in real hardship.
- Promise-to-pay and reminders that read the reply
- Clean handoff to a person for hardship and disputes
- Why they did not pay, captured as data
From pilots in financial services
Conversations a human team cannot hold alone
Early, industry-anonymized pilot results, not guarantees tied to a named client.
A neobank reached 450 customers and held 70 effective conversations in about a week.
Customer research pilot, neobank15 effective collections interviews in two days, versus 2 by hand in a full week.
Collections research pilot, lendingAn honest comparison
Against a human team and against a dunning tool
A team talks but does not scale. A dunning tool scales but blasts. Boom sits in between.
| Human collections team | A messaging / dunning tool | Boom | |
|---|---|---|---|
| Holds a real back-and-forth | Yes, but only so many a day | No, fixed templates | Yes, at scale |
| Personalizes by decline reason | If they catch it | Rarely, same retry for all | Yes, reads the reason |
| Captures why they did not pay | In notes, if remembered | No | Yes, as structured data |
| PII via your DB, never a CSV | Depends on process | Often a CSV upload | Always via your DB or API |
| A person steps in for hardship | Yes | No | Yes, clean handoff with context |
“Collections is a conversation, not a blast, and the part I did not expect to care about is that our customers’ data never has to leave our own database to make it work.”
Go deeper
The Sales CloserDunning and recovering failed payments, by decline reasonThe ResearcherWhy are they not paying, at scaleCustomer Data PlatformPII read through your DB, never a CSVExtractionClosed conversations into why-they-did-not-pay variablesFor mid-marketHow Boom fits a scaling, regulated fintech
See Boom on your own book
Bring a past-due segment or a cohort you want to understand. We will show you the conversations, where a person steps in, and exactly how the data is handled before anything touches a customer.