Skip to content

Published method

Debt exposure methodology

Ranks reported long-term debt components relative to total assets; higher exposure is not a credit-quality judgment.

1

Version

Oct 26, 2026

Published

1

Board

debt-exposure

Method ID

Where the facts come from

Source Board

company-financials

Allowed Sources
  • sec-companyfacts

How the order is produced

min(sum available reported current and noncurrent long-term debt components / total assets, 2.0), cohort min-max

When the method reruns

Each board shows the date of the snapshot it is built from.

Boards

Boards using this version

BoardPrimary measureRowsConfidenceSnapshotBoard versionRefreshBoard
AI debt exposuredebt-exposure-score19100%Oct 26, 20261Not statedOpen the board: AI debt exposure

Versioned contract

Complete measurement ledger

Range

  • 0
  • 100

Formula

min(sum available reported current and noncurrent long-term debt components / total assets, 2.0), cohort min-max

Evidence

exact observation IDs frozen per snapshot

Selection

latest eligible evidence by reporting period, then observation time; annual periods preferred for flow facts

Score Metric

debt-exposure-score

Source Board

company-financials

Normalization

cohort-relative only; raw values remain in ranking components

Allowed Sources

  • sec-companyfacts

Partial Debt Coverage

explicitly marked as a lower bound

Enter your website. In about two minutes, Rank.ai asks ChatGPT, Claude and Gemini 12 questions your customers ask and grades how often they name you.

  • Your grade out of 100How often AI names you, cites your site, and how high it ranks you.
  • Who gets namedEvery competitor in the answers, most named first.
  • The pages AI readsThe sources behind each answer.
  • Three fixesWhat to fix first, with a brief for the first article.