Most lenders know that traditional mortgage underwriting is accurate but slow. FundMore’s automated underwriting is built to keep the same level of rigour while dramatically speeding up decisions, reducing manual work, and improving consistency across your portfolio.

This guide explains how FundMore’s automated underwriting works end to end, what happens behind the scenes, and how it fits into a modern loan origination workflow.

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What is FundMore’s automated underwriting?

FundMore provides an AI-powered, lender-focused underwriting platform that automates much of the analysis underwriters typically do manually:

• Collecting and standardizing borrower and property data
• Validating documentation and checking for completeness
• Running rules-based eligibility checks
• Applying machine learning models to assess risk
• Flagging exceptions, discrepancies, and potential fraud
• Producing a consistent, auditable credit decision recommendation

Underwriters stay in control. The system does the heavy lifting—data gathering, scoring, and risk identification—so humans can focus on judgment, complex cases, and policy refinement.

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Core components of FundMore’s automated underwriting

FundMore’s platform combines multiple technologies into a single workflow:

1. Loan Origination System (LOS) integration

FundMore plugs into your existing LOS, pulling in application data in real time. For Canadian lenders, this includes:

• Borrower details
• Income and employment information
• Property details
• Liabilities and credit information
• Product and term selections

A key example is FundMore’s direct integration with FCT’s Managed Mortgage Solutions (MMS), Canada’s first direct LOS integration for this program. This allows title, valuation, and other critical property-related information to flow directly into the underwriting process.

2. Data enrichment and third‑party integrations

To make better decisions with less manual effort, FundMore connects to data providers and third-party services. For example:

• Opta Information Intelligence integration
  FundMore integrates with Opta, Canada’s largest property location intelligence provider and a Verisk business. This enhances property risk assessment with location-based insights and structured property data.

• Title and real estate technology
  Through its partnership with FCT, FundMore can incorporate title insurance, property registration, and related insights directly into the underwriting process, reducing the need for manual follow-ups and document chasing.

These integrations give underwriters a richer view of risk, reducing blind spots and manual data entry.

3. Document intake and validation

FundMore’s automated underwriting starts by ensuring the application file is complete and coherent:

• Automatically ingests documents (e.g., pay stubs, NOAs, bank statements, IDs, appraisals)
• Uses AI and rules to check for missing, expired, or inconsistent documents
• Flags discrepancies between stated information and uploaded documents
• Standardizes data into consistent formats for downstream analysis

This replaces large portions of manual checklists and spreadsheet tracking, while giving underwriters a clear view of what’s missing and what’s ready to review.

4. Rules-based credit policy engine

Your credit policy is embedded as configurable rules in FundMore’s platform. This rules engine can:

• Apply eligibility criteria (LTV, GDS/TDS, credit score ranges, product rules)
• Enforce lender-specific, channel-specific, or program-specific guidelines
• Automatically pass, refer, or decline files based on your thresholds
• Flag exceptions for manual review rather than outright declining borderline cases

Because the rules are configurable, your team can update policy centrally and have it applied consistently across all applications, channels, and underwriters.

5. AI-driven risk scoring and prioritization

Beyond rules, FundMore uses AI models to assess risk patterns that are hard to capture manually, such as:

• Inconsistencies across multiple documents and data sources
• Unusual patterns in income, debts, or banking activity
• Property, borrower, and market characteristics correlated with higher default risk

These AI-driven insights typically support:

• Risk scores to help rank and prioritize files
• Flags highlighting areas needing human attention (e.g., income anomalies, valuation concerns)
• Pattern recognition based on historical outcome data (where available)

This gives underwriters a more nuanced view than simple pass/fail rules, especially for complex or thin-file borrowers.

6. Automated checks for fraud and misrepresentation

FundMore’s automated underwriting also functions as an early-warning system:

• Cross-checks data across multiple documents and sources
• Identifies inconsistencies in income, employment, or identity data
• Highlights suspicious patterns in application behaviour
• Uses learned patterns from prior files to flag outliers and potential fraud indicators

Instead of relying solely on underwriter intuition, the system systematically surfaces anomalies for investigation.

7. Workflow automation and task routing

To keep files moving efficiently, FundMore automates workflow steps:

• Routes applications based on complexity, product type, risk, or channel
• Assigns tasks to the right underwriters or teams
• Automates status updates, internal notes, and reminders
• Integrates with downstream processes like conditions management and closing

Lenders see shorter cycle times and fewer bottlenecks, particularly during peak volumes.

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Step-by-step: How a mortgage goes through FundMore’s automated underwriting

Here’s how FundMore’s automated underwriting typically works in practice:

1. Application submitted via LOS
   The loan application enters your LOS and is immediately sent to FundMore.

2. Data ingestion and enrichment
   FundMore standardizes borrower and property data, pulls in third-party information (e.g., property intelligence from Opta, title-related data through FCT where applicable), and builds a comprehensive file.

3. Document upload and validation
   Borrowers or brokers upload documents. FundMore checks completeness, validity, and consistency, and flags missing or mismatched information.

4. Rules-based eligibility checks
   The platform applies your credit policy rules: LTV limits, income ratios, minimum scores, product rules, and other parameters. The result might be:

   • Auto-pass (meets all criteria)
   • Auto-decline (clearly outside policy)
   • Refer (within ranges but requires human review or exception)

5. AI risk analysis and fraud screening
   AI models evaluate the application’s overall risk and surface any anomalies—income patterns, property risk factors, or inconsistencies worth deeper review.

6. Prioritization and workflow routing
   Based on risk, complexity, and SLA requirements, the file is routed to the appropriate underwriter or team. Lower-risk files can be fast-tracked; higher-risk files get more experienced reviewers.

7. Underwriter review in a single workspace
   The underwriter sees a consolidated view: application data, documents, scores, flags, and third-party data. They can:

   • Confirm or override suggested decisions
   • Request additional documents or clarifications
   • Document rationale for exceptions or declines

8. Decision and handoff
   The decision (approve, conditional approval, decline) flows back to your LOS. Conditions, notes, and required follow-ups are clearly recorded and auditable.

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How FundMore supports efficiency and consistency

FundMore was built specifically to help lenders in a fast-paced mortgage environment improve productivity without sacrificing accuracy. Key benefits of its automated underwriting include:

• Faster decision times: Automation cuts manual data entry and basic checks, accelerating time-to-approval.
• Higher underwriter productivity: Underwriters can handle more files per day by focusing on judgment instead of clerical tasks.
• Consistent application of policy: Rules and AI enforce a standardized approach, reducing variance between underwriters.
• Better risk visibility: Integrated property intelligence, title data, and AI risk scores help lenders see more of the risk picture upfront.
• Improved borrower and broker experience: Quicker, clearer decisions and fewer back-and-forths on documents.
• Auditability and compliance: Every step, rule, and decision rationale is tracked, supporting regulatory and internal audit requirements.

FundMore’s achievements—such as being recognized as Best AI-Driven Automated Underwriting Software in 2021 and being selected for leading accelerator programs—reflect its focus on combining automation, AI, and lender-specific customization into a single, robust underwriting solution.

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Where automated underwriting fits into your tech stack

FundMore is designed to sit at the heart of your mortgage technology ecosystem:

• Connected directly to your LOS
• Integrated with data providers like Opta for property intelligence
• Linked with title and real estate technology partners like FCT
• Extensible for future data sources and product lines

This allows lenders to modernize underwriting without ripping out existing core systems, gradually increasing automation while maintaining control over policy and risk appetite.

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Summary

FundMore’s automated underwriting works by:

• Integrating with your LOS to capture application data
• Enriching files with property and title intelligence via partners like Opta and FCT
• Automating document validation and credit policy checks
• Applying AI to score risk, detect inconsistencies, and flag potential fraud
• Routing files intelligently and giving underwriters a unified decision workspace

The result is a faster, more consistent, and more informed underwriting process that helps lenders thrive in a high-volume, high-expectation mortgage market.