Use cases

How lenders put Loyola AI to work

Start with the two highest-impact areas in mortgage operations, then expand across the loan lifecycle. Both automate the work end to end and surface what needs a decision — the lending calls stay with your team.

01

Setup & Processing

Who it's for

Loan setup specialists and processors (and the loan officers waiting on them).

Trigger

A new document upload, a folder update, or an LOS milestone (e.g., “submitted to processing”).

At setup and processing, the file arrives as a stack of documents in mixed formats. The team manually classifies and renames them, keys data into the LOS, re-derives income and assets by hand, and chases missing items — the “stare-and-compare” work that drives most turn-time delays and downstream conditions.

What Loyola AI does

  1. 1

    Intake & classify

    Detects each document type as it arrives, renames it to your convention, organizes the file into stacking order, and keeps only the latest version per account or document.

  2. 2

    Extract

    Pulls borrower, employer, income, asset, property, and transaction fields as structured, MISMO-aligned data.

  3. 3

    Validate

    Compares extracted data against the URLA/1003 and LOS fields and your required-document list; flags what's missing, inconsistent, or needs review.

  4. 4

    Build worksheets

    Generates income worksheets (wage earner and self-employed cash-flow) and asset worksheets (bank-statement analysis, accounts parsed to the 1003, large-deposit identification).

  5. 5

    Surface gaps

    Produces a missing-item and completeness report, and answers loan-officer “where's my file?” questions from the loan file.

  6. 6

    Prepare the file

    Write-back and field updates so the file is submission-ready.

Outputs

A clean, stacked file · income and asset worksheets · missing-item report · LO-facing status summary · LOS field updates.

What stays with your team

Loyola AI runs setup and processing end to end and cross-checks the data as it goes, so the processor can verify the outputs at a glance instead of re-keying. Judgment calls stay with your team.

Value

Less manual document handling and re-keying · faster, cleaner hand-off to underwriting · fewer conditions created downstream · faster answers for loan officers and borrowers.

02

Initial Underwriting

Who it's for

Underwriters and underwriting managers.

Trigger

File submitted to underwriting, or the AUS run is complete (DU, LPA, TOTAL, or GUS).

On the first underwriting touch, the underwriter reads the file, reconciles it against the AUS findings and lender overlays, and hand-builds the condition list — hunting through documents to decide what's satisfied, what's missing, and what needs an exception. It's repetitive, time-consuming, and inconsistent across a team.

What Loyola AI does

  1. 1

    Read the file and findings

    Ingests the documents plus the AUS output (DU Verification Messages / Approval Conditions, or the LPA Feedback Certificate) and your overlays and condition templates.

  2. 2

    Reconcile

    Matches the evidence in the file against each AUS verification message and lender requirement; marks each as satisfied, missing, or inconsistent.

  3. 3

    Auto-generate the condition set

    Drafts the prior-to-doc, prior-to-close, and prior-to-funding (PTD/PTC/PTF) conditions an underwriter would otherwise build by hand.

  4. 4

    Flag risk early

    Surfaces likely manual-downgrade triggers (undisclosed debt, large unsourced deposits, a >20% business-income decline), overlay conflicts, and red flags — before they reach the closing table.

  5. 5

    Hand over a summary

    An underwriter-ready snapshot (DTI, LTV, reserves), the key data, exceptions, and the drafted conditions.

Outputs

A drafted condition list plus an initial underwriting summary, ready for the underwriter to review, edit, and approve.

What stays with your team

Loyola AI generates the condition set end to end and cross-checks it against the findings and your rules. The underwriter owns the credit decision and any subjective calls — Loyola AI does not approve, deny, price, or make adverse-action decisions.

Value

Underwriters skip manual condition-building and document hunting · cleaner, more consistent condition sets · fewer missed conditions and post-close defects · a faster, more uniform initial underwriting touch.

Workflow availability and configuration depend on implementation scope. We typically start with a focused set of high-priority workflows, launch quickly, and expand based on lender feedback.

Ready to automate your first mortgage workflow?

Start with a focused workflow, launch quickly, and expand as your team sees value.

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