What “Level 3” AI Means for Lenders
Mario DiBenedetto, President, Brimma Tech
January 20, 2025
For U.S. mortgage lenders, reaching Level 3 AI development—“agents and systems that can take actions”—means integrating AI systems capable of autonomously taking context-aware, goal-oriented actions to improve operational efficiency, borrower experience, and compliance. These systems would actively perform tasks previously reliant on human decision-making, enabling faster, more efficient, and reliable mortgage-related operations.
Here are potential examples of Level 3 AI applications for U.S. mortgage lenders:
1. Intelligent Loan Prequalification
AI systems could:
- Automatically analyze a borrower’s financial data from applications, credit scores, bank statements, and other documents.
- Determine prequalification status in real time and provide preapproval letters without manual intervention.
- Take action to notify borrowers of their eligibility and guide them through the next steps.
Example in Action:
An AI assistant identifies missing documentation during prequalification, prompts the borrower to upload it, processes the data, and updates the preapproval status autonomously.
2. Automated Loan Underwriting
AI systems can:
- Evaluate loan applications by analyzing borrowers’ creditworthiness, income, and property data.
- Make autonomous decisions to approve, deny, or flag applications requiring human review.
- Adjust underwriting criteria dynamically based on market conditions or lender policies.
Example in Action:
An AI system identifies an applicant’s income from structured and unstructured sources (e.g., pay stubs, tax returns, and bank statements) and approves a loan that fits within the risk profile, all without human oversight.
3. Dynamic Document Processing and Management
AI systems can:
- Automatically classify, extract, and validate data from mortgage documents such as title commitments, appraisals, and closing disclosures.
- Initiate corrective actions, such as requesting updates from title companies or verifying discrepancies with appraisers.
Example in Action:
The AI detects an inconsistency in property details between the appraisal and title documents, autonomously flags the issue, and requests corrections from the respective parties.
4. Real-Time Fraud Detection and Prevention
AI systems could:
- Monitor transactions for patterns indicative of fraudulent activity, such as identity theft or false income claims.
- Automatically block questionable applications or transactions and notify relevant teams.
Example in Action:
The AI identifies inconsistencies in borrower data (e.g., mismatched addresses) and autonomously pauses the loan process, sending notifications to compliance teams for review.
5. Proactive Customer Engagement
AI agents could:
- Monitor borrower interactions, financial conditions, and loan progress.
- Take action to send personalized offers, rate adjustments, or reminders about closing deadlines.
- Recommend refinancing opportunities or additional services proactively.
Example in Action:
An AI system notices interest rate drops and automatically identifies borrowers eligible for refinancing, sending personalized offers and prepopulated application forms.
6. Automated Closing Process
AI systems can:
- Coordinate between lenders, title companies, and borrowers to finalize the closing process.
- Schedule appointments, generate closing disclosures, and validate final documents autonomously.
- Identify missing signatures or errors in real-time and request updates.
Example in Action:
An AI agent autonomously prepares closing documents, cross-checks them for compliance with regulatory requirements, and schedules a notary appointment for the borrower.
7. Servicing and Loss Mitigation Actions
AI systems could:
- Analyze payment histories and proactively recommend loss mitigation strategies for borrowers struggling with payments.
- Adjust payment plans or initiate foreclosure proceedings based on lender guidelines.
Example in Action:
The AI identifies a borrower at risk of default, offers a tailored payment plan, and automates the necessary approvals and communications.
8. Portfolio Management and Risk Adjustment
AI systems could:
- Continuously monitor the lender’s loan portfolio, assessing risk and suggesting actions such as rebalancing the portfolio or adjusting pricing models.
- Take action to mitigate risks by modifying terms or offering incentives to borrowers with high-risk profiles.
Example in Action:
The AI detects a concentration of loans in a high-risk area and autonomously adjusts the underwriting criteria to limit exposure.
Benefits of Level 3 AI for U.S. Mortgage Lenders:
- Speed: Significantly faster decision-making and processing times.
- Accuracy: Reduced human error in repetitive tasks like document processing and compliance checks.
- Scalability: Ability to handle surges in demand during peak seasons or rate changes.
- Improved Borrower Experience: Personalized and proactive interactions that build trust and satisfaction.
By achieving Level 3 AI capabilities, U.S. mortgage lenders can streamline their operations, enhance borrower satisfaction, and remain competitive in a technology-driven market.
Let us know if you’d like more detailed use cases or success stories! Contact us at salesinfo@brimmatech.com or our website to learn more!
