Underwriting Automation

Decision-ready underwriting without manual income work

In partnership with Candor, MOS delivers trusted borrower income and asset data ready for underwriting decisions — in under 3 minutes.

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Why Income Analysis Slows Underwriting


Income analysis preparation and document review consume the most underwriting time of any stage in loan manufacturing. Manual income calculations introduce inconsistency and slow decisions. Self-employed and complex borrower income can extend timelines by days. And income data must be repeatedly verified across systems and document stages — each time a processor, underwriter, or reviewer touches the file.


The result is a bottleneck at the point where speed matters most: the credit decision.



What MOS Automates


Documents, data, and conditions — handled upstream

MOS ingests borrower income and asset documents — W-2s, pay stubs, bank statements, tax returns — and extracts structured data at human-level accuracy. Cross-document comparisons and rule-based checks validate consistency before income analysis begins, so underwriters receive files that are already clean.


Income calculations and verification via Candor

In partnership with Candor, MOS delivers trusted income calculations and verification. Candor performs income analysis using a transparent, auditable decision engine. Results flow back cleanly into the LOS with confidence scores, exceptions, and a full audit trail — no black-box decisions.


Exceptions are transparent and routable

Instead of reviewing every document in every file, underwriters receive a structured list of exceptions that require human judgment. Routine validations — employment verification, income consistency checks, asset sufficiency — run automatically. Every decision is traceable, with clear confidence thresholds and explainable outputs.



Built for Real Underwriting Environments


  • Clear confidence thresholds — every income output includes a confidence score and supporting evidence
  • Transparent exception handling — exceptions are structured, categorized, and routed to the right role
  • Audit-ready outputs — full traceability from source document to income figure, investor-ready
  • No black-box decisions — every calculation is explainable and reviewable
  • Under 3 minutes from docs to income analysis — compared to hours of manual review


Integrating via the MOS API


The Underwriting Automation workflow is accessible through the MOS API. Submit borrower document packages and receive structured income and asset data, conditions, and audit metadata in return. Key capabilities exposed via the API include:


  • Borrower data packages — submit income and asset documents; receive structured extraction results with field-level confidence scores
  • Income Clarity outputs — calculated income figures with supporting evidence, confidence scores, and an explainable audit trail
  • Conditions and exceptions — structured condition objects for every discrepancy, missing field, or rule violation detected during analysis
  • Audit metadata — full traceability from source document through income figure, suitable for investor delivery
  • Status events and webhooks — real-time notifications as analysis progresses through each stage
  • External Field Mappings — income and asset data written directly back to your LOS fields

Authentication uses industry-standard token-based auth. All API calls are scoped to your provisioned environment (UAT or Production). See the API catalog for full endpoint reference, request/response schemas, and Postman collection.



Ready to integrate Underwriting Automation?

Request UAT access and evaluate the income analysis workflow before contract signature.

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Explore Workflows

Loan Setup & Data Quality

Turn uploads into clean, decision-ready files automatically.

Underwriting Automation

Decision-ready income and asset data without manual calculations.

Processing, Closing & Post-Close

Automate condition matching, closing review, and post-close validation.

Ready to get started?

Speak with TRUE about fit, volume, and implementation.

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