name: loan-application-explanation description: Explain loan approval and denial decisions with full regulatory compliance. Use when generating adverse action notices, explaining credit decisions to applicants, producing Reg B/ECOA-compliant reason codes, or when loan officers need decision transparency for borrower-facing communications.
metadata: display_name: "Loan Application Explanation" short_description: "Explain loan approval and denial decisions with reason codes" default_prompt: "Explain my loan application in simple words and next steps" version: "1.0.0" tags: - financial-services
icon_path: "assets/icon.png"
Loan Application Decision Explanation
Overview
Generate clear, compliant explanations of loan approval or denial decisions. This skill produces borrower-facing narratives that satisfy Regulation B adverse action notice requirements, ECOA fair lending obligations, and internal audit documentation standards. Explanations decompose the decision into contributing factors—credit score, DTI, employment stability, collateral, and policy overlays—ranked by materiality.
When to Use
- Generating adverse action notices under Reg B / ECOA
- Explaining approval conditions (rate tier, required reserves, co-signer)
- Responding to borrower inquiries about decision rationale
- Producing audit-ready decision documentation
- Supporting fair lending examination preparedness
- Reviewing model-driven decisions for human-readable justification
Required Inputs
| Input | Description | Format |
|---|---|---|
| Application data | Borrower demographics, income, employment, assets | JSON or tabular |
| Credit bureau pull | FICO score, tradeline summary, derogatory marks | Bureau report extract |
| Decision output | Approve/deny/counter-offer with conditions | Decision engine output |
| Reason codes | Top 4 adverse action reason codes (if denial) | Standard reason code set |
| Product parameters | Loan type, term, requested amount, LTV | Loan product spec |
| Policy overlays | Any investor or institution-specific overlays applied | Policy rule set |
Methodology
Step 1 — Parse the Decision Engine Output
Extract the binary decision (approve/deny/counter), the scorecard tier, and all triggered rules. Map each triggered rule to its human-readable policy description. Identify whether the decision was purely model-driven, policy-overlaid, or manually overridden.
Step 2 — Rank Contributing Factors by Materiality
Order the decision factors by their marginal contribution to the outcome:
- Credit score impact — Distance from cutoff, score band placement
- DTI ratio — Front-end and back-end DTI vs. product maximums (e.g., 43% QM threshold)
- LTV/CLTV — Loan-to-value against program limits and PMI triggers
- Employment/income stability — Verification status, gap analysis, income trending
- Collateral adequacy — Appraisal vs. purchase price, property condition flags
- Compensating factors — Reserves, residual income, co-borrower strength
Step 3 — Map to Regulatory Reason Codes
For denials and adverse actions, map the top contributing factors to the standardized adverse action reason codes (OCC/FFIEC model codes or proprietary mappings). Select the top 4 reason codes ranked by impact. Verify codes align with the actual decision drivers—never use generic placeholders.
Step 4 — Generate Borrower-Facing Narrative
Compose a plain-language explanation that:
- States the decision clearly in the first sentence
- Lists specific factors in order of importance
- Avoids prohibited language (no references to protected classes)
- Includes required disclosures (credit bureau source, score used, score range)
- Provides the applicant's right to obtain a free credit report within 60 days
- References the CFPB or appropriate regulatory contact for disputes
Step 5 — Produce Internal Audit Documentation
Generate a parallel internal document that includes:
- Full factor decomposition with numeric values
- Policy rules triggered with version identifiers
- Any manual override justification and approver identity
- Comparative analysis against similarly situated applicants (fair lending lens)
- Exception tracking reference number if applicable
Step 6 — Fair Lending Compliance Review
Cross-check the explanation against fair lending red flags:
- Ensure no prohibited basis factors influenced the decision
- Verify similarly situated borrowers received consistent treatment
- Flag any statistical outliers for second-look review
- Document disparate impact analysis results if available
Step 7 — Assemble Final Deliverable
Package the explanation into the required format: adverse action notice (denial), statement of credit terms (approval with conditions), or counter-offer letter. Include all regulatory disclosures, timing requirements (30-day notice window), and delivery method documentation.
Output Specification
## Loan Decision Explanation
### Decision Summary
- **Application ID**: [ID]
- **Decision**: [Approved / Denied / Counter-Offered]
- **Date**: [Decision date]
- **Product**: [Loan type and term]
### Primary Decision Factors (Ranked)
1. [Factor]: [Plain-language explanation with specific values]
2. [Factor]: [Plain-language explanation with specific values]
3. [Factor]: [Plain-language explanation with specific values]
4. [Factor]: [Plain-language explanation with specific values]
### Adverse Action Reason Codes (if applicable)
- Code [X]: [Description]
- Code [Y]: [Description]
- Code [Z]: [Description]
- Code [W]: [Description]
### Regulatory Disclosures
- Credit score used: [Score] from [Bureau] (range [XXX]–[XXX])
- Right to free credit report within 60 days from [Bureau contact]
- Right to dispute accuracy of information with [Bureau]
### Internal Audit Trail
- Scorecard version: [ID]
- Policy overlay version: [ID]
- Override: [Yes/No — if yes, justification and approver]
- Fair lending flag: [None / Flagged for review — reason]
Analysis Framework
Apply the FACT framework for every explanation:
- Factors — Enumerate all contributing decision factors with values
- Action codes — Map to regulatory-compliant reason codes
- Compliance — Verify ECOA/Reg B/TILA disclosure requirements
- Transparency — Ensure plain-language accessibility (8th-grade reading level)
Examples
Example 1 — Conventional Mortgage Denial
Input: FICO 612, DTI 48%, LTV 95%, 2 years employment, 1 month reserves Decision: Denied Explanation: "Your application for a 30-year conventional mortgage was not approved. The primary factors were: (1) your credit score of 612 is below the minimum threshold of 640 for this program; (2) your total debt-to-income ratio of 48% exceeds the maximum of 45%; (3) your available reserves of 1 month are below the 2-month minimum required for loans with LTV above 90%."
Example 2 — Auto Loan Approval with Conditions
Input: FICO 695, DTI 38%, employment 5 years, requested $35,000 Decision: Approved at Tier 2 pricing Explanation: "Your auto loan application has been approved for $35,000 at 6.49% APR for 60 months. Your rate reflects Tier 2 pricing because your credit score of 695 falls in the 680–719 band. A score of 720 or above would qualify for our best rate of 4.99% APR."
Guidelines
- Always use the specific credit score, DTI ratio, and LTV values — never vague language
- Limit adverse action notices to exactly 4 reason codes per Reg B convention
- Include the credit score disclosure addendum on every denial and counter-offer
- Use plain language at an 8th-grade reading level for borrower-facing content
- Never reference race, ethnicity, sex, marital status, age, or other prohibited bases
- Maintain separate internal and external explanation documents
- Timestamp all explanations and link to the specific scorecard/policy version
- Retain explanation records for the regulatory minimum retention period (25 months for ECOA)
Validation Checklist
- Decision factors are ranked by actual materiality, not arbitrary order
- Adverse action codes match the true decision drivers
- All Reg B required disclosures are present (bureau, score, range, rights)
- No prohibited basis language or proxies appear in the explanation
- Internal documentation includes scorecard version and policy overlay IDs
- Plain-language readability target met (Flesch-Kincaid grade 8 or below)
- Counter-offer letters include both original and revised terms
- Explanation is timestamped within the 30-day adverse action notice window
- Fair lending comparative analysis is documented for denials
- Exception-to-policy decisions have documented justification and approval chain