Review Screenings → Compare Application → Flag Inconsistency → Check Language → Report

Screening and Fair Housing Audit Agent

Flags inconsistent screening processes and risky policy language for review, so fair housing risk gets caught internally before it becomes exposure.

The Problem

Criteria get applied unevenly. That is fair housing risk.

Inconsistent screening criteria creates fair housing exposure that nobody notices until a complaint.

What Changes

Inconsistencies and risky language flagged for review.

Reviews screening processes for consistency and flags risky language or uneven criteria application. Catches the pattern before it becomes a complaint.

Humans stay in control: Your team and counsel make the calls. The agent surfaces inconsistency and risky language. It removes the blind spots, not the legal judgment.

HOW THE AGENT WORKS

TRIGGERLLMAPIDECISIONACTIONWAIT

TRIGGERPeriodic AuditScheduled review of recent screenings

APIPull ScreeningsGet recent decisions and criteria applied

LLMCompare ApplicationCheck criteria applied consistently

LLMCheck LanguageFlag risky policy or note wording

DECISIONRisk Found?

ACTIONReport For ReviewSend findings to compliance

The agent doesn't make legal determinations. It flags inconsistent process and risky language for your team and counsel to review.

HOW TO BUILD IT

Three levels of depth. Pick the one that matches where you are.

For the ops person who needs to understand what's involved and brief their team.

Your ScreeningsRecent decisions

The AgentWorkflow engine + LLM

Your ComplianceRisk findings

WHAT YOUR TEAM PROVIDES ONCE

Screening criteria - the standard that should be applied evenly
Decision records - the screenings to review
Risky-language patterns - wording to flag
Review routing - who receives findings
Scope - how far back each audit looks

What happens day-to-day: On a schedule, the agent reviews recent screenings to check the same criteria were applied the same way, and scans notes and policy for risky language. Findings go to compliance for review before uneven treatment becomes a fair housing problem.

For the IT person or technical lead who needs to scope the integration.

INQUIRY SOURCES

Screening records

Policy docs

Decision notes

WORKFLOW ENGINE (N8N)

Trigger - schedule

API - Pull screenings

LLM - Compare application

LLM - Check language

Branch - risk?

Report for review

Log findings

CONNECTS TO

Screening / PMSRead: decisions, criteria applied

Policy / document storeRead: policy language

Notifications (email / Slack)Send findings to compliance

Findings logRecord reviewed items

WITHOUT PMS API

Agent reviews exported records and policy text. The consistency and language checks still run.

WITH PMS API

Agent reviews live screening records for consistency and language risk. Best experience.

For the person who wants to build this agent step by step. Each node below maps to an n8n workflow node.

TRIGGERNode 1

Trigger - Periodic Audit

Cron (e.g. monthly) over recent screenings.

Output: { run_date, lookback }

APINode 2

HTTP Request - Pull Screenings

Get recent decisions, the criteria applied, and notes.

Output: [{ applicant_id, decision, criteria_applied, notes }]

LLMNode 3

LLM - Compare Application

Check whether criteria were applied consistently across similar applicants.

Output: [{ applicant_id, inconsistency, detail }]

You check screening consistency for fair housing risk.

Compare how CRITERIA were applied across the screenings. Flag cases where similar profiles got different treatment, or criteria were applied beyond policy. This is a risk flag for human review, NOT a legal determination.
Return applicant_id, inconsistency (true/false), detail.
Respond ONLY with a valid JSON array.

CRITERIA: {criteria}
SCREENINGS: {screenings}

OUTPUT

[
  { "applicant_id": "a_91", "inconsistency": true, "detail": "Denied for income 2.9x while a_77 approved at 2.8x - inconsistent threshold application." }
]

LLMNode 4

LLM - Check Language

Scan policy and notes for risky or potentially discriminatory wording.

Output: [{ source, phrase, concern }]

You flag risky language in screening policy and notes.

Using RISKY-LANGUAGE PATTERNS, flag wording that could raise fair housing concern. Provide source, phrase, concern. This is for human/counsel review, not a legal opinion.
Respond ONLY with a valid JSON array.

RISKY-LANGUAGE PATTERNS: {patterns}
TEXT: {policy_and_notes}

OUTPUT

[
  { "source": "screening note a_44", "phrase": "not a good fit for the building", "concern": "Subjective language; document objective criteria instead." }
]

DECISIONNode 5

Condition - Risk Found?

IF inconsistencies or risky language found → report. ELSE → log all-clear.

Output: Branch: RISK (report) or CLEAN (log)

ACTIONNode 6

Report For Review

Send the findings to compliance/counsel and log the review.

Output: Findings surfaced for review.

MVP vs Advanced — Where To Start

MVP — START HERE

Manual audit
Exported records
Consistency check
Language scan
Email findings
Findings to a sheet

ADVANCED — ADD LATER

Full Video Walkthrough Coming Soon

From screening records to a fair-housing risk review - step by step.

Everything on this page is free to learn.

When you're ready to build — do it yourself or bring us in.

Book a call to scope this

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Frequently asked questions

Screening and Fair Housing Audit Agent is an AI agent that flags inconsistent screening criteria and risky policy language.

Criteria get applied unevenly. That is fair housing risk. The Screening and Fair Housing Audit Agent addresses this — it flags inconsistent screening criteria and risky policy language.

No — your team stays in control. Your team and counsel make the calls. The agent surfaces inconsistency and risky language. It removes the blind spots, not the legal judgment.

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