Winning in a volatile mortgage market is less about forecasting the next rate move than making useful decisions while conditions remain uncertain. In this Settling Scores conversation, cohosts Abdel Khawatmi of PRMG Got Mortgages and Eric Levin, cofounder of Model Match, connect borrower education, local market research and consistent relationship work. Their central argument: technology can help professionals respond faster, but it cannot replace the judgment and follow-through that earn trust.
Episode originally published September 11, 2026. Archive recap added October 24, 2026.
Watch the full Winning in Volatile Markets conversation on YouTube.
Economic releases, rate movements and housing conditions discussed below are historical episode context, not current market reporting, available pricing or advice to lock or float a loan. The useful lessons concern how to evaluate options and communicate uncertainty, not whether the episode’s market expectations came true.
Key takeaways: turn uncertainty into useful work
- Explain what changing conditions mean for a particular borrower instead of repeating alarming headlines.
- Combine discoverable educational content with direct conversations; neither channel excuses neglecting the other.
- Research nearby markets and referral relationships rather than waiting for a broad recovery.
- Monitor past-client opportunities without assuming every refinance is beneficial.
- Use AI to organize a well-reasoned explanation, not to supply unverified mortgage judgment.
- Show the tradeoffs and respect the borrower’s final choice.
Replace market prediction with an explanation people can use
Eric opens the business discussion by asking where an originator finds the next loan when the market feels persistently difficult. Abdel’s answer starts with understanding information and translating it for consumers. He describes returning to more educational posting after spending time on AI infrastructure, and relaunching Got Mortgages University Live. The practical shift is from building tools behind the scenes to helping people understand decisions in front of them.
Abdel discusses employment and inflation releases as part of his historical rate-lock thinking. Those comments describe his approach during the recorded period; they are not a repeatable instruction to lock before a particular report. The broader point is accountability: explain the reasoning, acknowledge uncertainty and stay in touch after the decision. A borrower needs context for an actual transaction, not a confident prediction detached from closing dates and costs.
Build an educational publishing routine that survives busy periods
The source-grounded example here is Abdel’s return to educational content and the relaunch of Got Mortgages University Live. He describes recognizing that time spent building AI infrastructure had displaced some market explanation. The business lesson is to connect behind-the-scenes innovation with something the audience can actually use.
A suggested implementation is to reserve a recurring editorial planning session. Choose a public educational question, identify the reliable source material and decide which professional will review the explanation. Keep the question narrow enough to answer clearly. An article explaining what an employment report measures is more manageable than a broad prediction about the entire housing market.
Turn that approved explanation into complementary formats: a short video introducing the question, an article providing context and a FAQ answering common follow-ups. Check that every format preserves the same limitations rather than becoming more certain as it gets shorter.
Protect the routine during busy weeks by assigning responsibility in advance. If there is no time to verify a new market claim, publish evergreen education rather than an unchecked reaction. Consistency means maintaining a useful standard and a dependable presence, not generating the maximum possible number of posts.
Digital visibility and personal contact reinforce each other
Eric asks whether a shrinking opportunity pool favors broad marketing or direct relationship work. Abdel rejects that either-or framing. He describes improving websites and educational blogs while continuing to attend networking meetings and speak with people directly. When a new contact searches for him afterward, the online material can reinforce the explanation they already heard.
The website discussion includes Lovable and WordPress, along with attention to search visibility, structured information and common borrower questions. Abdel reports inbound results after making changes, but those are his account of a particular effort, not independently established performance or a promise that the same edits produce leads elsewhere. The durable takeaway is to inspect whether a site answers useful questions clearly and gives readers a straightforward next step.
His local publishing example focuses on Ocean County and Monmouth County. For New Jersey readers, that specificity matters: a question rooted in a local purchase is more useful than a page that simply claims nationwide reach. Still, local focus should mean substantive relevance, not repeated town names. Eric adds the operational warning: automation is not permission to forget the marketing or the people responding to it.
Use data to expand deliberately, not indiscriminately
Eric brings observations from Model Match into the discussion, including a market-signals comparison and examples of growing originators. He distinguishes an unusually refinance-heavy growth example from others whose activity appears more broadly supported. That distinction matters because a short transaction window can make a headline growth figure look more durable than the underlying business mix warrants.
Across the other examples, he identifies a wider referral network, modest geographic expansion and, in one case, greater attention to first-time buyers. His Arizona example concerns an originator reaching surrounding communities rather than jumping into distant states. These observations are directional examples, not proof that any single tactic caused growth or that every nearby county offers equal opportunity.
A New Jersey application is to compare neighboring markets before committing time and resources. Ask where purchase activity fits the team’s capabilities, which buyer’s agents already know the team and where useful service could deepen a relationship. Expansion should remain connected to licensing, capacity and local knowledge. The episode supports intentional adjacency, not spreading thinly across a map.
Past relationships need a dependable service rhythm
Eric warns that opportunities can arrive quickly. Without monitoring and alerts, an originator may miss a chance to help someone already served. He also accepts that a competitor can sometimes offer a genuinely better fit. Retention is not an entitlement, and a successful relationship does not require keeping every transaction at any cost.
His closing advice is to manage past relationships with alerts and monitoring rather than treating a database as a passive collection. A suggested implementation is to assign an owner to incoming alerts, define how the team checks relevance and record the follow-up task. An alert should prompt a review, not automatically trigger a transaction recommendation.
Keep ordinary relationship maintenance separate from sales opportunities. Periodic educational updates and an easy way to ask questions can support continuity without implying that every contact should produce a new application. Respect communication preferences and use organization-approved information and channels.
Review missed handoffs as a process issue. Did an alert go unseen, did the assigned person lack context, or was there no clear next step? These suggested review questions support the hosts’ emphasis on timing and consistency without promising that monitoring can eliminate customer churn.
Give AI a defined communication job
Eric explicitly distinguishes using AI for formatting, graphics and grammar from asking it to do the professional’s thinking. The source-grounded principle is direct instruction: the professional supplies the substance and purpose, and the tool helps package it. A polished output cannot establish that the underlying explanation is correct.
For a practical business application, use an approved public market explainer as the input. Specify its intended audience, the question it answers, the source date and the uncertainties that must remain visible. Ask for a short outline or FAQ, then compare the result against the original. Remove any figures, conclusions or promises that were not supported.
Treat visuals as another version of the same explanation, not a separate source of authority. Check labels and captions as carefully as body text. Offer a route to a real conversation when a reader needs clarification. These suggested editorial practices keep the professional responsible for the substance while giving AI a clear formatting task.
Turn adjacent-market research into a service plan
Eric’s growth examples offer a useful contrast with indiscriminate expansion. He describes referral networks becoming broader and geographic coverage extending into nearby communities. The Arizona example stays around the existing base, including places such as Buckeye, Glendale and Goodyear. Those are business-development observations, not private borrower stories or proof of causation.
As a suggested planning exercise, compare a small set of adjacent counties using the same reporting periods and definitions. Separate application activity from closed-loan activity rather than mixing them into a single growth claim. Note where the team already has relevant relationships and where additional local knowledge would be needed.
Next, review referral concentration and choose a manageable outreach list. Ask what useful contribution the team can make, such as a general educational session or a clearer communication process. Track agreed follow-ups rather than simply counting introductions. The aim is a repeatable service commitment, not a claim that every researched agent will become a referral partner.
Suggested checklist: put the episode’s approach into practice
The following is a suggested implementation checklist drawn from the discussion, not a verbatim routine prescribed by the cohosts. It connects market awareness to specific borrower and business-development actions.
- Choose one borrower question. Explain a public educational topic, such as what an inflation release measures, using verified sources.
- Review the local footprint. Compare nearby counties and identify where the team can deliver knowledgeable service.
- Map referral concentration. Look for overdependence on a few relationships and opportunities to contribute to others.
- Review past-client needs. Assign responsibility for alerts and follow-up rather than merely collecting contacts.
- Check published explanations. Confirm that educational pages answer the question, identify the author and offer a clear contact route.
- Review every AI-assisted comparison. Verify numbers and remove unsupported assumptions before sharing it.
- Close the communication loop. Record the borrower’s choice and the next agreed action, including when no transaction is appropriate.
Frequently asked questions
What does winning in a volatile mortgage market mean here?
It means responding with useful service rather than waiting for friendlier conditions. The episode emphasizes education, deliberate referral development, local research and continued attention to past customers. It does not promise that a particular process eliminates market risk.
Does the episode recommend predicting mortgage rates?
No reliable forecasting formula emerges from the discussion. Abdel describes historical decisions around economic releases, but the transferable lesson is to explain uncertainty and the reasons for a decision. Current lock questions require a fresh review of the transaction.
How can a team make educational publishing consistent?
Set a recurring planning session, choose a focused question and assign a reviewer. Abdel’s return to educational posting motivates this suggested routine. Keep publication quality ahead of volume, and distinguish evergreen explanations from time-sensitive market commentary.
Should loan officers choose online marketing or networking?
The cohosts favor combining them. Educational content can establish relevance before or after a meeting, while direct contact creates opportunities to understand individual needs. Neither an automated campaign nor a networking introduction replaces dependable follow-through.
How does the discussion apply to New Jersey?
Abdel describes county-focused education in Ocean and Monmouth counties. Eric’s broader point suggests researching adjacent markets and agent relationships before expanding. The historical statewide observations in the episode should not be treated as a current assessment of any New Jersey neighborhood.
What role should AI play in borrower education?
AI can help organize an explanation into readable text or a visual comparison. The mortgage professional must supply and verify the underlying reasoning. The episode’s strongest use case keeps the professional in the conversation rather than sending a graphic and asking the borrower to decide alone.
What should happen after a monitoring alert?
A suggested process is to assign an owner, verify relevance and record the next follow-up. The episode supports timely attention to past relationships, not automated recommendations. An alert is a reason to review information, not evidence that a new transaction is appropriate.
Can better follow-up prevent every lost customer?
No. Eric explicitly recognizes that another provider may sometimes offer a better fit. Monitoring and timely contact help reduce avoidable neglect, but the borrower’s interests remain more important than retaining every transaction.
How can I discuss my own mortgage options?
Call 973-536-0276 or visit GotMortgages.com. You can also use the Contact page or Build My Mortgage Plan page to start a conversation about your goals, timeline and questions.
Build trust while conditions change
The episode’s most practical conclusion joins old-fashioned relationship work with modern tools. Research can identify where to focus; technology can make an explanation easier to deliver. Neither substitutes for listening, checking the comparison and following through. For borrowers, the useful question is not who sounds most certain about the market, but who explains the available choices clearly.
To talk with PRMG Got Mortgages, call 973-536-0276, visit GotMortgages.com, contact the team or build your mortgage plan.
Explore more Mortgage Intel and Abdel Khawatmi’s profile.
Author: Abdel Khawatmi with PRMG Got Mortgages | 973-536-0276
This article is general mortgage information only. It is not a commitment to lend, a rate quote, or legal or tax advice. Loan approval, terms and pricing depend on a full application, credit review and property details, and market conditions change. Talk with a licensed loan officer and your own legal or tax professional about your situation. NMLS #1712023 | PRMG NMLS #75243.