Collections, dunning, and research for regulated fintech
Banking and lending do not run on win-back the way subscriptions do. They run on getting paid, learning why people fall behind, and converting the next cohort. Boom is an AI workforce that holds real payment and research conversations with thousands of customers across the channels they already use, personalizes each one to the situation, and hands off to a person when a case turns sensitive. It reads your customer data through your own database, never a file you export and email around, for a fraction of the cost of the team it would replace.
Trusted by teams that grow with Boom
The work that moves the numbers in fintech
Most fintech teams start with one of three problems: proving the engagement is safe to run, getting more of their book to pay, or understanding why it does not. Boom is built around all three.
- 01
Regulated-entity readiness
SOC 2 and GDPR are in progress, with a controller and processor DPA, role-based access, and encrypted credentials. Every conversation is backed up so you can answer a complaint or a regulator audit, and a customer can have their data deleted or exported on request. The point is that your compliance and security reviewers can clear Boom without a fight.
- 02
Early-stage collections as an art
Our founder ran a lender for seven years, so we will be honest: early-stage collections is a craft, not a formula. Boom runs payment reminders and promise-to-pay flows, keeps the tone right so numbers do not get flagged and blocked, and pulls a person in for hardship cases. No vendor can stop a platform from blocking an aggressive number, and we will not pretend otherwise.
- 03
Dunning by decline reason
A card that hit insufficient funds, a card that expired, and a do-not-honor decline are three different conversations, not one retry. Boom reads the reason and changes what it says and when it says it, so failed-payment recovery stops being a single generic nudge sent to everyone.
Your customers’ PII stays in your database, not a CSV
Sensitive financial PII does not belong in a spreadsheet passed between tools: Boom connects to your customer data through an API or a database connector and reads what it needs at run time, so there is no list to export, email around, and forget on someone's laptop.
- PII read through your DB or API, never a CSV upload
- Role-based access and encrypted credentials
- Conversation backups for complaint and regulator audits
- One-click delete or export of a customer’s data on request
A real back-and-forth on getting paid, with a human for the hard cases
You give Boom a goal in plain language, it holds the conversation, reads the replies, and adapts instead of firing the same template at everyone, handing off to a person on your team the moment someone is in genuine hardship.
- Promise-to-pay and payment reminders that read the reply
- Clean handoff to a person for hardship and disputes
- Every conversation captured as why-they-did-not-pay data
Against a human team and against a dunning tool
A collections team holds a real conversation but does not scale. A messaging or dunning tool scales but blasts the same message. Boom is meant to sit 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 |
Conversations a human team cannot hold alone
These are early, industry-anonymized results, not guarantees tied to a named client. Teams in this space also see failed-payment recovery improve once dunning is personalized by decline reason rather than sent as one generic retry.
- 450 → 70
A neobank reached 450 customers and held 70 effective conversations in about a week, work that would tie up a person for many days.
Customer research pilot, neobank
- 15 in 2 days
A lending team ran 15 effective collections interviews in two days, versus 2 done by hand in a full week.
Collections research pilot, lending
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 reason
- The ResearcherWhy are they not paying, at scale
- Customer Data PlatformPII read through your DB, never a CSV
- ExtractionClosed conversations into why-they-did-not-pay variables
- For 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.