---
id: "entity-us-cfpb"
type: "entity"
entityType: "organization"
canonicalName: "U.S. Consumer Financial Protection Bureau"
aliases: ["CFPB"]
source_timestamps: ["§ How to Use Explainable AI Responsibly"]
tags: ["regulation", "united-states", "finance"]
related: ["concept-checkbox-transparency", "claim-transparency-mandates-insufficient"]
sources: ["adoption"]
sourceVaultSlug: "hbr-seg-adoption"
originDay: 9
articleStem: "hbr-edu-37-employees-not-questioning-ai"
sourceUrl: "https://hbr.org/2026/06/employees-arent-questioning-ai-advice-enough"
sourceTitle: "Employees Aren’t Questioning AI Advice Enough"
---
# U.S. Consumer Financial Protection Bureau (CFPB)

**Type:** Organization (U.S. regulator) · **Canonical name:** U.S. Consumer Financial Protection Bureau · **Alias:** CFPB

A U.S. government agency overseeing consumer financial products. In **2023** the CFPB reminded lenders of their legal obligation to provide borrowers with **"specific" and "accurate" reasons** for AI-assisted adverse decisions, such as credit denials — rejecting generic model-based rationales and stressing obligations under the Equal Credit Opportunity Act and Regulation B. Cited in the source among the mandates that can produce [[concept-checkbox-transparency]] (see [[claim-transparency-mandates-insufficient]]).

**Canonical reference (enrichment):** Agency homepage `consumerfinance.gov`.

**Counter-perspective (enrichment):** The CFPB's demand for *specific and accurate* reasons is designed to push lenders toward substantive justification rather than boilerplate — an enforcement trend that works *against* checkbox compliance.