Illustrative walkthrough using seeded data. Product capabilities are marked Built or Planned.
NOTARY AI
Screen 04[BUILT]

Applicant A-1027 denied at score 650

Lending · ECOA / Regulation B — Fair Lending — one entry in Company XYZ's versioned library of : preserved decision conditions paired with an Authorized Expected Behavior, reused on every future candidate version.
Company XYZ decision accountability · LoanCore Underwriting 3.2.0Lending · Applicant A-1027Representative lending boundary case
  1. ACCOUNT13
  2. VERIFY47
  3. DEFEND89
  1. Connect
  2. Landscape
  3. Readiness
  4. 4Scenarios
  5. 5Authorize
  6. 6Verify
  7. 7Release
  8. 8Package
  9. 9Hand-off
VERIFYScreen 04
Question
Which decision conditions must future versions continue to handle correctly?
Answer
Company XYZ has preserved representative, boundary, disputed, and previously failed decisions as reusable Assurance Scenarios.
Output
A versioned library of decision conditions with authorized expected outcomes.
Fault attribution · Rule failure

A rigid deterministic gate denied a case the underlying model would have passed.

Decision chain

[BUILT]captured evidence
INPUT
Application payload
score=650, income=$78k, DTI=22%, tenure=2y
TOOL
Bureau pull
TransUnion — 2 tradelines, 0 delinquencies
MODEL
Underwriting model v3.1
PD estimate = 0.041 (within tolerance)
RULE
Failing or uncertain node
Hard threshold gate
if score < 700 → DENY
DECISION
Adverse action
Notice mailed 2026-06-14
Why this case is useful for release assurance
source_decision
Applicant A-1027, personal loan $18k
trigger
142 lending denials without a policy binding
failing_node
Hard threshold gate
evidence_level
E4
replayability
Replay-ready from the sealed cassette
missing_evidence
None — decision-time policy version, bureau pull, and adverse-action record are all preserved.
applicable_policy
Underwriting Policy 4.2 (2026-06)
expected_behavior
Authorized by Fair Lending Lead — Marcus Bell
suggested_preservation
Preserve decision-time policy version and human-review evidence on the next occurrence
suggested_scenario
Add to the Lending Release Scenario set as a boundary case included in the release-assurance suite
Candidate provenance
evaluator
company-xyz-evaluator v0.6.2
frozen_input_set
lending-sweep-2026-07
evaluated_at
2026-07-22T04:15:00Z
source_evidence
sha256:9f2c…a17b
relationship_confidence
Confirmed — decision and adverse-action record share a source identifier
known_limitations
Excludes decisions missing bureau pull; advisory only.
Captured decision
Applicant A-1027, personal loan $18k
Outcome
DENIED
reason: credit_score (650) below hard threshold (700)
Authorized Expected Behavior
Route to compensating-factor review (2y employment, DTI 22%) under Underwriting Policy 4.2.
Evidence
E4sufficient for verification
cassette · sha256:9f2c…a17b
Next action

Advisory only. An must define or approve the expected behavior before a candidate version can be verified against it.

→ Authorize expected behavior
Screen anatomy

What this screen proves

For any single decision case, Notary AI can show which nodes ran, which node is failing or uncertain, what was captured, what evidence is missing, and what the record is at.

Why it matters

This is how a case earns a place in the release-assurance suite. A useful case has preserved evidence, a known applicable policy, and a clear expected behavior worth testing every future candidate version against.

Built or Planned

Planned capability for candidate generation; the decision-chain view and evidence grading are built. Candidates shown here are a seeded illustration.

Important boundary

The candidate is advisory. Notary AI does not determine what the acceptable outcome should be — an supplies the Authorized Expected Behavior on Screen 05, and the re-checks eligibility server-side.

Related requirements

Next

A scenario preserves the conditions, but it cannot decide what outcome is acceptable. An authorized Company XYZ reviewer must establish that.

Authorized Behavior