USE CASES

Mortgage Underwriting Automation

MightyBot runs a GSE conventional delivery-eligibility pre-screen on first-lien 1-4 unit mortgages that could be sold to Fannie Mae or Freddie Mac so compiled floors execute and underwriters keep the judgment.

What is mortgage delivery-eligibility screening?

Agents on the MightyBot platform run a GSE conventional delivery-eligibility pre-screen for first-lien 1-4 unit mortgages that could be sold to Fannie Mae or Freddie Mac, calculating income and DTI with evidence trails and returning delivery-eligible, ineligible, or refer from compiled floors.

The Problem

For financial services teams, a single mortgage file spans dozens of document types. The underwriter extracts data from each document, cross-references the package, and evaluates it against layered guidelines: Fannie Mae and Freddie Mac delivery floors, plus lender overlays.

Hard floors — occupancy, conforming limits, LTV, credit score, DTI, reserves, evidence clocks — should compile the same way on every conventional file. Self-employed cash-flow stability, short history, declining income, and variable-income continuance stay open judgment. Volume spikes create backlogs. QC adds another layer. Missing or stale evidence cannot stamp a file delivery-eligible.

Document volume

Large files across dozens of document types

Layered guidelines

GSE delivery floors plus lender overlays, all interacting

Income complexity

Self-employed, co-borrower, and variable income — cash-flow arithmetic compiles; stability stays open

Volume volatility

Rate-driven waves overwhelm manual capacity

QC burden

Re-underwriting closed files creates repurchase risk if missed

How MightyBot Executes It

Every step. Automated.
Every calculation. Traced.

  1. Full File Document Processing

    Ingestion & Classification

    Entire mortgage file ingested and classified simultaneously. Every document type routed to specialized extraction. Missing, stale, or conflicting required evidence cannot produce a delivery-eligible stamp. Consistent structured data. In parallel.

  2. Agency Guidelines as Executable Policies

    Guideline Enforcement

    Policies written in plain English compile into deterministic execution. Occupancy, property, purpose, conforming loan limits, LTV/CLTV/HCLTV, representative credit score, DTI, reserves, and required evidence clocks are hard floors on conventional GSE files. Other agency guidelines can be modeled as policies. Updates deploy centrally and run on the next file.

  3. Automated Income Calculation

    Income Analysis

    Income extracted from pay stubs, W-2s, and tax returns. Self-employed: Schedule C, K-1, 1120-S, 1065 with add-backs and trending. The cash-flow worksheet compiles; stability, short self-employed history, declining income, and variable-income continuance stay open. Thin write-ups refer. Every calculation shows source documents and methodology.

  4. DTI, LTV, and Disposition

    Evaluation

    DTI, LTV, CLTV, and HCLTV computed with evidence trails linking every input to source. Conventional GSE files return delivery-eligible, ineligible, or refer. A labeled AUS finding is an input, never a live engine call, and never the official action.

Use-case map

How Mortgage Underwriting Automation works in MightyBot

MightyBot runs a GSE conventional delivery-eligibility pre-screen on first-lien 1-4 unit mortgages and returns a disposition, findings memo, and audit record.

Inputs Mortgage files, income documents, bank statements, credit reports, appraisals, labeled AUS findings, agency guidelines, and lender overlays.
Execution Classifies the file, extracts borrower facts, compiles GSE delivery-eligibility floors and overlays from plain English, calculates income and DTI, and leaves self-employed and variable-income judgment open.
Outputs Delivery-eligible, ineligible, or refer disposition, underwriting-findings memorandum, and exportable audit record.
Audit trail Every gate records the Selling Guide or Freddie Guide cite, evidence pointer, observed value, threshold, result, and whether a rule or a reviewer computed it.
Best for Mortgage teams handling large files, GSE delivery-eligibility floors, self-employed borrower complexity, guideline changes, and QC pressure.

"We automated what no one else could."

The platform compiles GSE delivery-eligibility floors on occupancy, loan limits, LTV, credit score, DTI, reserves, and evidence clocks. Self-employed cash-flow stability and variable-income continuance stay open for the underwriter.

95%
Time reduction in production Built Technologies — Production Deployment

Before vs After

After Before

Loan files processed. Delivery-eligibility floors compiled. Underwriters keep the judgment.

Request a demo Calculate underwriting ROI/TCO

FAQ

Frequently Asked Questions

What is mortgage delivery-eligibility screening?

A GSE conventional delivery-eligibility pre-screen evaluates first-lien 1-4 unit mortgages that could be sold to Fannie Mae or Freddie Mac against compiled floors: occupancy and property, conforming loan limits, LTV/CLTV/HCLTV, representative credit score, DTI, reserves, and required evidence clocks. Official outcomes are delivery-eligible, ineligible, or refer. The delivery-floor pass (APPROVE_ELIGIBLE) is this pre-screen’s result; it is not Desktop Underwriter Approve/Eligible and not LPA Accept. Agents on the platform calculate income and return the disposition, findings memo, and audit record. Delivery-eligibility is not a credit approval.

What do AI mortgage underwriting agents do?

They read the full loan file, calculate qualifying income (including self-employed borrowers), compile delivery-eligibility floors and lender overlays, flag missing required evidence, and assemble findings with evidence links. A labeled AUS finding is an input, never a live engine call. Approval authority stays with the underwriter. The platform does not approve the loan, compute LLPAs, or quote MI.

Can MightyBot handle self-employed borrower income?

Yes. 1040, Schedule C, 1120-S, 1065, and K-1 documents are processed with agency-specific add-backs, trending, and declining-income flags documented. The cash-flow worksheet compiles; cash-flow stability, short self-employed history, and declining income stay open. Thin write-ups refer.

How does MightyBot stay current with agency changes?

Guidelines are written in plain English and compiled into deterministic execution. When Fannie or Freddie publish updates, the policy changes centrally and all new files evaluate against the latest rule set immediately.

Does MightyBot support lender overlays?

Yes. Lender-specific overlays can be layered on top of agency guidelines so the platform evaluates both and shows which policy drove each finding.

Can MightyBot automate post-close QC?

Not this pre-screen. Post-close QC is a later desk activity. This workflow returns the delivery-eligibility disposition, findings memo, and audit record. It does not re-underwrite closed files or rate repurchase risk.

How does MightyBot handle AUS findings?

A labeled Desktop Underwriter or LPA finding is a structured input, never a live engine call, and never the official action. The platform cross-references it against the file and evaluates it alongside compiled delivery-eligibility floors. Delivery-eligible on this pre-screen is not DU Approve/Eligible and not LPA Accept.

What about non-QM and portfolio products?

Bank statement programs, asset depletion, DSCR investor loans, and other portfolio products can be modeled as policies on the same platform.