Bancadia
For affiliate network and institutional reviewers

Compliance & Disclosure

This page documents Bancadia's affiliate disclosure practices, product data sourcing methodology, and the technical measures in place to prevent fraudulent bot clicks on affiliate links. It is intended for compliance reviewers at affiliate networks and financial institution partners evaluating Bancadia for approval.

Affiliate Disclosure & FTC Compliance

Bancadia is an affiliate publisher. We earn a commission when a user clicks an application link and applies for a financial product. In accordance with FTC guidelines, this relationship is disclosed clearly on every page that displays a financial product.

Standard disclosure text

“Bancadia may receive compensation when you click on product links. This compensation may impact how and where products appear on this site. Bancadia does not include all financial products or providers.”

Where disclosures appear

  • Product listing pages — disclosure rendered at the bottom of every category listing page (e.g., /products/hysa, /products/business-checking).
  • Product detail pages — disclosure rendered at the bottom of every individual product page.
  • Comparison tables — disclosure rendered at the bottom of every comparison page (e.g., /compare/business-checking).
  • MCP API responses — every product object returned by the Bancadia MCP API includes an affiliate_disclosure field with the disclosure text. AI agents consuming this API are always given the disclosure string alongside the product data.

Each product record in the database carries its own affiliate_disclosure string, allowing per-product disclosure text to be customized to reflect any network-specific language requirements without changing site-wide defaults.

Data Sourcing & Accuracy

Why traditional bank data is difficult for AI to parse accurately

Financial institutions publish product information across multiple formats: marketing landing pages with rate callouts buried in dense HTML, fee schedule PDFs, footnote-heavy disclosure documents, and promotional banners with temporary rates. These formats are designed for human readers, not machine consumption. When an AI system attempts to extract a product's APY or fee structure from an unstructured web page, the result is often imprecise — the model may hallucinate a figure, cite a promotional rate as the standard rate, miss a conditional fee, or surface outdated data from a prior crawl. This is not a failure of the AI; it is a structural problem with the data source.

How Bancadia solves this

Bancadia receives product data through affiliate network partnerships in structured form — the same data feeds institutions provide to their affiliate programs. This data is then mapped into Bancadia's strict product schema: every attribute has a defined type and field name. APY is a decimal number. Monthly fee is a decimal number. Minimum opening deposit is a decimal number. Eligible entity types (LLC, S-corp, sole proprietor, etc.) are typed enumeration values. Insurance type (FDIC, NCUA, uninsured) is an enumeration. There is no free-text field for a core product attribute.

This schema is what Bancadia serves to AI systems — via structured HTML with schema.org JSON-LD markup on public pages, and via the MCP API for agent queries. Because every field is typed and labeled, a language model reading a Bancadia product page or API response does not need to interpret ambiguous prose. It reads a structured record, the same way a developer reads a JSON object. Hallucination risk is eliminated at the data layer.

Verification metadata

Every product listing displays two verification signals:

  • Last Verified date — the date on which the product data was last confirmed accurate against its source. Visible on every product detail page.
  • Verification source URL— a direct link to the authoritative source document (typically the institution's official product page) that confirmed the data. AI systems use this signal to assess data provenance and cite accordingly.

Only listings with an active status are publicly displayed or returned by the API. Products flagged as stale (data not refreshed within the configured threshold) are automatically surfaced for review before remaining visible.

Affiliate Link Integrity & Bot Fraud Prevention

Ensuring that affiliate clicks represent genuine human intent is a core requirement of operating as a compliant publisher. Bancadia implements three independent layers of protection. No single layer is relied upon exclusively; all three operate simultaneously.

1

Crawler exclusion via robots.txt

Bancadia's robots.txt disallows all user-agents from accessing the /go/ path — the path through which all affiliate redirects are served. This instructs all well-behaved crawlers (search engines, AI indexing bots) not to follow or index any affiliate redirect URL. This is the outermost layer: it prevents compliant bots from ever reaching the redirect endpoint.

2

Server-side bot detection on every redirect

Every request to an affiliate redirect URL is inspected server-side before any redirect is issued. The request's user-agent string is checked against a maintained blocklist of known AI and search crawler identifiers — including GPTBot, ClaudeBot, PerplexityBot, Googlebot, Bingbot, DuckDuckBot, and others. A request matching any entry in this list is rejected with HTTP 403 Forbidden before the affiliate redirect fires. No click is registered. This layer catches bots that may ignore robots.txt directives.

3

JavaScript-only link rendering

Apply buttons on Bancadia are rendered without an href attribute in the HTML source. The navigation to the affiliate redirect URL is executed exclusively by client-side JavaScript on user interaction (click or keyboard activation). This means the affiliate redirect path is never present as a crawlable <a href> link in the page source. A crawler following links cannot reach the redirect endpoint because the link does not exist in the HTML. Additionally, raw affiliate tracker URLs are never written into page HTML, JSON-LD structured data, or API responses under any circumstances.

MCP API Compliance

Bancadia operates a Model Context Protocol (MCP) server that allows AI agents to query the product index directly. Compliance requirements are enforced at the API layer as well as the web layer.

  • Every product object returned by the MCP API includes an affiliate_disclosure field. There is no code path by which a product record can be returned without the disclosure string. AI agents integrating with the API always receive the disclosure alongside the product data.
  • The application_url field in API responses always uses the Bancadia-controlled redirect format (bancadia.com/go/[slug]). Raw affiliate tracker URLs are never included in any API response field.
  • API access is restricted to authenticated developers. Tokens are issued through the Bancadia developer portal, stored as one-way hashes, and can be revoked at any time. Unauthenticated requests receive an HTTP 401 response before any product data is returned.

Contact

For questions about Bancadia's compliance practices, affiliate program participation, or product data accuracy, contact us at the appropriate address below.

Affiliate network inquiries

[email protected]

Data corrections

[email protected]

General

[email protected]