Solution

Risk Rating
Consistency

Identify misalignment between credit narrative, borrower performance, risk factors, and assigned rating.

Key capabilities

Narrative assessment vs. financial performance comparison
Risk factor identification and severity analysis
Rating methodology consistency checks
Trend analysis across review periods
ASI CMR does not autonomously change authoritative risk ratings
Evidence-backed findings for rating review discussions

What reviewers get

Narrative and performance compared side by side

Rating rationale checked for consistency

Deterioration signals surfaced with evidence

Findings framed for reviewer discussion — not auto-applied

Operating principle

AI proposes. Deterministic services calculate. Source documents prove. Humans decide.

How it works

A grounded pipeline that keeps calculation, policy, and human judgment clearly separated.

1

Ingest source documents

Credit memos, financial statements, and supporting files are parsed into structured data with full source provenance preserved.

2

Calculate deterministically

A deterministic calculation engine computes figures and comparisons outside the language model, so numbers are reproducible and auditable.

3

Reason with grounded AI

AI proposes findings only from extracted evidence and the applicable, effective-dated policy — never from unverifiable assumptions.

4

Route to the reviewer

Every finding arrives with its source citation and severity so a human reviewer can confirm, adjust, or dismiss it — and decide.

An illustrative finding

Illustrative

A fictional example showing how a single issue flows from source data to a reviewer decision. Figures are illustrative only.

Scenario

A credit narrative describes “stable and improving” performance while the financials show two quarters of decline.

Extracted data

Narrative language: “stable, improving.” Financials: revenue and EBITDA down across the last two quarters.

Deterministic check

Calculation engine confirms a period-over-period decline in key metrics from the source statements.

Applicable policy

Rating methodology expects the narrative and performance trend to support the assigned rating.

AI finding

AI proposes a consistency flag: narrative tone diverges from the measured downward trend.

Reviewer action

Reviewer weighs the evidence and decides whether the rating warrants reassessment — the platform never changes it automatically.