See how your CFPB complaints compare with 5 peers: trend, top issues, relief and timeliness gaps, and the one issue to fix first. Public data only.
| Complaints, 12 mo | 1,516 ▲62% YoY |
| Peer median, 12 mo | 1,236 |
| Timely response (90d) | 99.7% · peers 99.4% |
| Relief rate (90d) | 0.0% · peers 2.4% |
| Top issue (90d) | Credit report info, 28% |
CFPB complaints in 12 months across 10 fintech & nonbank lenders
filed under debt collection (32.7%) or credit reporting (32.4%)
filed under the loan product itself
of closed complaints ended with any relief (213 of 12,278)
Every week: who's rising, which issues are spreading across the peer set, and one thing to check on Monday. Five-minute read, built on public CFPB data.
They're about what happens after the loan. Plus: one BNPL lender's 30-day jump (+28%), and the one lender behind 70% of all relief.
Tell us your company and up to 5 peers. We map them to their CFPB entity names.
12+ months of complaints, cleaned and compared: volume trend, issue mix, relief and timeliness, state hot spots.
A one-page snapshot in 48 hours with the issue to fix first and the questions to ask your own data.
Built only from public CFPB data, with lenders anonymized. These are sample analyses, not client work.
One BNPL lender (Lender B) accounts for 148 of the peer set's 213 relief outcomes. The other nine combined: 0.6% relief.
Lender C, a BNPL lender: 77 complaints vs 60 the prior 30 days. "Debt not owed" doubled (7 → 14). Hypothesis: payment posting, not the collections script.
"Problem when making payments" across the peer set: 146 → 184 in 90 days, while total volume fell 13%.
I'm Miguel A. Flores. For 13 years I've built enterprise applied-AI products at the largest bank in Latin America, turning 110M+ customer interactions a year into customer intelligence the whole bank runs on.
My 8 product squads feed a shared customer-intelligence asset that 1,000+ customer-facing squads use to set backlog priorities, gather evidence and test hypotheses.
Complaint triggers solved issues for 300K customers a month and helped the bank reach its best regulator complaint ranking since 2012, cutting the program budget by 95%.
AI copilots and next-best-action guidance for supervisors and frontline reps, plus practice with synthetic customers before real ones.
Michigan Ross MBA. Tellbird brings that playbook to US companies, starting with public complaint data.
Founder-led. You work with me, supported by an AI analyst team.
Talk to me directly → miguel@tellbird.ai
No. The snapshot and benchmark use only the public CFPB Consumer Complaint Database. Your own data comes in only with the Diagnostic, de-identified and under NDA.
No. Tellbird is independent and not affiliated with or endorsed by the CFPB.
Yes. Complaints aren't verified or normalized by customer base. That's why we compare you with peers and show trends, not rankings.
US fintech and nonbank lenders with roughly 50+ CFPB complaints in the last 12 months.
Most teams want to know why. That's the Diagnostic: we classify your own interactions and build a root-cause tree with owners and impact.
No. It's operating analysis. Check regulatory decisions with your counsel.