Boom holds collections and research conversations with thousands of customers, reads your data from your own database, and hands sensitive cases to a person.
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.
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.
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.
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.
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.
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.
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.
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, neobankA lending team ran 15 effective collections interviews in two days, versus 2 done by hand in a full week.
Collections research pilot, lendingA 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 |
“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.”
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.