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Check whether credit-review claims have supporting evidence

Continua describes using Jev to check a credit-review claim against a source passage, while keeping calculations, document changes and lending decisions outside the model.

Original by ContinuaGuardrails

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Credits

“Jev for Credit Review: Using a Decision Model to Verify Evidence in Credit Files” by Continua. Read the original source.

This expanded guide is an AI-narrated adaptation prepared by JevMade. It expands the source’s essential ideas, examples and caveats in JevMade’s own words and is not a word-for-word reading. The synthetic voice does not imitate the author or imply their endorsement.

Our summary

A credit review brings together loan agreements, financial statements and other records. A sentence in a review can sound right while relying on an old or incomplete document. Continua describes checking whether a specific passage supports the claim, contradicts it or leaves the question unanswered.

First, ordinary code checks that a quoted passage really appears in the document. Then Jev's Choice question selects from three meanings: support, contradiction or missing evidence. The workflow must first establish which agreement and amendments apply. Code handles arithmetic and dates; people review material financial conclusions.

A missing debt schedule does not prove that a borrower has no other debt. Nor does a confident answer establish that the complete file was checked. Continua reports that its internal Jev checks cost 1.34% of GPT checks, but provides too little test-set detail to establish wider reliability.

Key takeaways

  1. Check that the quote exists before asking a model what it means. An exact match can still reject a reworded quote or noisy scanned text.
  2. Keep missing evidence separate from a contradiction, and resolve document amendments before selecting the passage to check.
  3. Use code for calculations and dates, and keep important lending conclusions with people regardless of the model's confidence.

The company describes its own workflow and test results, not an independently checked credit system. Its 1.34% cost comparison does not say how many examples were tested or which GPT version was used. Reporting the same rate of wrongly accepted claims does not establish safety. The linked studies were not checked again here. Check the service's data-handling terms before sending borrower text.

Continua Blog · Original published

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