loanDepot AI Visibility Market Strategy Report - Mortgage Refinance Lenders

Mark HuntleyBy Mark HuntleyFounder and CEO
12 minutes read

Key Takeaways

  • loanDepot’s valid recommendation coverage rose to 49.34% in October 2026, marking a sustained two-month increase.
  • The brand appears in the top three in 23.82% of qualified responses but is named first in only 2.84%.
  • Copilot is loanDepot’s strongest platform, while Gemini and Perplexity show weaker first-position performance.
  • All qualified observations fell into the brand recommendation class, leaving pricing and comparison behavior unmeasured.

Answer Capsule

loanDepot is the strongest challenger in the Mortgage Refinance Lenders category, holding 49.34% valid recommendation coverage in October 2026, up 15.44 points from 33.90% in July 2026. The brand is visible in 56.71% of qualified AI responses and recommended within the top three in 23.82% of them, but it is named first in only 2.84% of observations. The clearest win is a two-month upward streak in both presence and placement. The clearest weakness is a rank-one rate that sits far below its coverage position. The clearest opportunity is converting its broad top-three presence into first-position recommendations.

Who This Report Is For

This report is written for loanDepot's marketing, brand, and growth leadership, and for category analysts tracking how mortgage refinance lenders are recommended across AI platforms.

Report Card

Field

Value

Report type

AI Visibility Company Market Strategy Report

Target company

loanDepot

Category / market studied

Mortgage Refinance Lenders

Reporting month

October 2026

AI platforms tracked

6 (ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, AI Mode)

Public high-intent clusters

1

AI observations analyzed

529

Competitors tracked

9

Executive Summary

loanDepot holds second position in the Mortgage Refinance Lenders AI recommendation index for October 2026, with 49.34% valid recommendation coverage across 529 qualified observations. That places it nearly 30 points behind Rocket Mortgage at 79.20% and roughly 14 points ahead of Bank of America Corp. at 35.50%.

The brand's trajectory is the strongest sustained movement in the tracked set. Coverage rose from 33.90% in July 2026 to 49.34% in October 2026, a gain of 15.44 points that exceeded normal month-to-month variation, and the September-to-October movement of 12.80 points was also significant. This is a two-month upward streak, not a single-month spike.

Presence and placement both improved. Raw mention presence rose from 43.70% to 56.71%, with loanDepot appearing in 300 of 529 qualified observations. The top-three rate rose from 13.30% to 23.82%. Valid recommendations grew from 206 in July to 261 in October.

The gap sits in first-position recommendations. loanDepot's rank-one rate is 2.84%, up only modestly from 2.10% in July. Rocket Mortgage's rank-one rate is 48.96%. loanDepot is being shortlisted far more often than it is being named first.

Sentiment is strong. loanDepot recorded 263 positive mentions, 37 neutral mentions, and zero negative mentions, producing a net sentiment score of 0.8767, the second highest among tracked brands behind Better.com at 0.9737.

Platform behavior varies. Copilot produced the strongest recommendation signal, with loanDepot recommended in 87.80% of Copilot observations and a top-three rate of 58.50%. ChatGPT produced 46.97% valid recommendation coverage and a 13.64% rank-one rate. Gemini produced a 42.68% coverage rate but zero rank-one placements.

The clearest gap is the absence of qualified pricing, value, and multi-brand comparison observations. All 529 qualified observations fell into the brand recommendation class, so the benchmark cannot yet show how loanDepot performs when AI systems are asked to compare lenders directly or discuss refinance rates.

What loanDepot Is Winning

Questions This Section Answers

  • Where is loanDepot's AI recommendation coverage growing, and is the improvement sustained?
  • Which platform produced loanDepot's strongest mortgage refinance recommendation signal?

loanDepot is the strongest challenger in the category. Its 49.34% valid recommendation coverage is the second highest of the ten tracked brands and the largest baseline gain in the set at 15.44 points.

The brand is the clearest sustained riser. Coverage moved up in each of the two months since August 2026, and both the baseline movement and the September-to-October movement exceeded normal variation. No other brand in the tracked set posted a comparable two-month streak.

Placement improved alongside presence. The top-three rate rose from 13.30% in July to 23.82% in October, a gain of 10.52 points. This means loanDepot is not just being mentioned more often, it is being shortlisted more often.

Sentiment is a genuine strength. With 263 positive mentions, 37 neutral mentions, and zero negative mentions, loanDepot's net sentiment score of 0.8767 is the second highest in the tracked set. The brand is not carrying a negative framing problem.

Copilot is the strongest platform signal. loanDepot recorded an 87.80% valid recommendation coverage rate on Copilot, the highest of any platform for the brand, with a 58.50% top-three rate. This is a narrow but meaningful recommendation pocket.

Where loanDepot Has the Clearest AI Visibility Gaps

Questions This Section Answers

  • What is the biggest structural gap in loanDepot's AI visibility, and how far behind is the brand?
  • Where did loanDepot have no qualified pricing, value, or multi-brand comparison coverage?

The clearest gap is first-position recommendation conversion. loanDepot is recommended within the top three in 23.82% of qualified observations but named first in only 2.84%. Rocket Mortgage is named first in 48.96% of observations. The gap between shortlist presence and first-position selection is the single largest structural weakness in loanDepot's AI visibility profile.

The second gap is platform inconsistency. Copilot recommends loanDepot in 87.80% of observations, but Gemini recommends the brand in 42.68% of observations with zero rank-one placements, and Perplexity recommends the brand in 25.42% of observations with a 1.69% rank-one rate. The brand's recommendation strength is concentrated rather than distributed.

The third gap is the absence of comparison and pricing coverage. All 529 qualified observations fell into the brand recommendation class. No qualified observations were captured for pricing, value, or multi-brand comparison questions. This means the benchmark cannot show whether loanDepot wins or loses when AI systems are asked to compare lenders directly, which is where buyer shortlists are often formed.

The fourth gap is the entity-name question. loanDepot is tracked under a single consistent name, so it does not carry the naming reconfiguration issue that affected Chase, Bank of America, Wells Fargo, and Guaranteed Rate. However, the benchmark cannot confirm whether AI systems refer to the brand by other names not yet captured.

Biggest Opportunity

Questions This Section Answers

  • What is loanDepot's biggest AI visibility opportunity in the mortgage refinance category?
  • On which platforms should loanDepot focus to improve its rank-one recommendation rate?

The biggest opportunity is converting loanDepot's top-three presence into first-position recommendations. The brand already appears in the top three in 23.82% of qualified observations, but it is named first in only 2.84%. Closing even part of that gap would move loanDepot from a shortlist option to a primary recommendation in a meaningful share of high-intent prompts.

This opportunity is concentrated in the brand recommendation cluster, which is the only cluster with qualified observations. The prompts driving this cluster include direct lender recommendation questions such as "Who is the best mortgage lender right now?" and "Who is the easiest mortgage lender?" These are the prompts where first-position placement matters most.

The platform dimension matters here. Copilot already recommends loanDepot at a high rate, so the opportunity is to strengthen first-position placement on ChatGPT, Gemini, and Perplexity, where the brand's rank-one rate is low or zero.

Competitive Landscape

Questions This Section Answers

  • How does loanDepot rank against other mortgage refinance lenders on top-three and rank-one recommendation rates?
  • Where does loanDepot's average recommended rank sit compared to the top performers?

Rocket Mortgage holds dominant recommendation-stage strength in the Mortgage Refinance Lenders category, with loanDepot as the strongest challenger and Bank of America Corp. as the third-position brand. The table below shows the tracked competitor set ranked by top-three recommendation rate.

Brand

Top-3 rate

Rank-1 rate

Avg recommended rank

Sentiment

Rocket Mortgage

69.94%

48.96%

1.51

0.8170

loanDepot

23.82%

2.84%

3.86

0.8767

Better.com

19.09%

2.46%

2.66

0.9737

Bank of America Corp.

18.71%

3.02%

3.59

0.8093

United Wholesale Mortgage

14.18%

4.54%

2.39

0.6471

PennyMac

7.94%

1.70%

3.81

0.7121

New American Funding

4.16%

0.76%

4.37

0.9100

Wells Fargo & Co.

2.84%

0.76%

3.19

0.3656

Rate

1.51%

0.76%

3.42

0.7333

Chase Credit Journey

0.57%

0.00%

2.33

0.7500

Average recommended rank covers rank-eligible recommendations only.

loanDepot holds the second-highest top-three rate in the category at 23.82%, but its rank-one rate of 2.84% sits below United Wholesale Mortgage at 4.54% and Bank of America Corp. at 3.02%. The brand's average recommended rank of 3.86 is the second-highest (least favorable) among the top five brands by top-three rate, indicating that when loanDepot is recommended, it tends to appear later in the shortlist.

AI Response Inconsistency Alerts

Questions This Section Answers

  • Where did AI platforms disagree about loanDepot's position among top mortgage lenders?
  • What source pages were cited on each side of the top-five mortgage lender inconsistency?

One high-severity factual inconsistency was detected for loanDepot across two AI platforms. The conflict concerns the composition of the top five mortgage lenders in the United States.

When asked "What are the top 5 mortgage lenders in the US?", Copilot stated that loanDepot is one of the top five mortgage lenders in the U.S. Google AI Mode provided a different list, stating that the top five are Rocket, UWM, CrossCountry, Pennymac, and JPMorgan Chase, with loanDepot not listed.

The conflicting responses cited different source pages. Copilot referenced a page from mortgage-info.com that ranked loanDepot third with a 6.15% rate and described it as offering the best variety of FHA, VA, and jumbo loans. Copilot also referenced a page from thereport.org and a page from thedailylane.com that included loanDepot in a list of the ten best mortgage lenders of 2026. Google AI Mode referenced Bankrate's list of the ten largest mortgage lenders, a Motley Fool page on the largest mortgage providers, and a Money.com page on the best mortgage lenders.

The flagged source on the Copilot side was the mortgage-info.com page, which placed loanDepot at number three. The flagged sources on the Google AI Mode side included the Bankrate page, which listed Rocket Mortgage, United Wholesale Mortgage, CrossCountry Mortgage, Pennymac, Chase, and loanDepot in sequence, and the thedailylane.com page, which included loanDepot in its ranking.

This inconsistency means that a buyer asking a direct top-five question may receive a list that includes loanDepot on one platform and excludes it on another. The source pattern suggests that the discrepancy may be driven by which third-party ranking pages each platform retrieves and how it interprets list position.

Prompt Evidence

Copilot / Brand Recommendation Prompt: "Who is the best mortgage lender right now?" Result: loanDepot was recommended in 87.80% of Copilot observations with a 58.50% top-three rate, the brand's strongest platform signal.

Gemini / Brand Recommendation Prompt: "Who is the easiest mortgage lender?" Result: loanDepot recorded a 42.68% valid recommendation coverage on Gemini but zero rank-one placements, indicating presence without first-position conversion.

ChatGPT / Brand Recommendation Prompt: "Who is the best lender for mortgages?" Result: loanDepot recorded a 46.97% valid recommendation coverage and a 13.64% rank-one rate on ChatGPT, the brand's strongest first-position performance.

Perplexity / Brand Recommendation Prompt: "Which bank is best for home loan interest?" Result: loanDepot recorded a 25.42% valid recommendation coverage on Perplexity with a 1.69% rank-one rate, indicating limited recommendation strength on this platform.

What CiteWorks Studio Would Do Next

Phase 1: AI Visibility Market Discovery Audit Map the specific prompt families where loanDepot appears in the top three but is not named first, and identify which competitor takes the first-position slot in each case.

Phase 2: Recommendation Readiness Plan Prioritize the platform and prompt combinations where loanDepot's rank-one rate is lowest, particularly Gemini and Perplexity, and define the evidence and framing changes needed to compete for first position.

Phase 3: Owned Answer Layer Buildout Strengthen loanDepot's owned pages so that the brand's differentiators, loan variety, and eligibility criteria are stated in extractable language that AI systems can retrieve and synthesize.

Phase 4: Citation / Authority Layer Development Address the source-layer inconsistency by ensuring that third-party ranking pages and comparison sites carry accurate, consistent information about loanDepot's position and offerings.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track loanDepot's top-three rate, rank-one rate, and platform-level recommendation coverage month over month to confirm whether the upward streak continues and whether first-position conversion improves.

Why This Matters

AI presence alone is not enough. loanDepot is mentioned in more than half of qualified AI responses and recommended within the top three in nearly a quarter of them, but it is named first in fewer than three percent. In a category where buyers ask direct recommendation questions, the difference between being shortlisted and being named first is the difference between being considered and being chosen.

The next move is targeted correction of the prompt, page, and citation layers. The prompt layer determines which questions loanDepot competes for. The page layer determines what AI systems can retrieve about the brand. The citation layer determines which third-party sources shape the recommendation. The inconsistency alert in this report shows that the citation layer is already producing conflicting answers about whether loanDepot belongs in the top five, which makes source-layer correction a priority.

Core Metrics

Metric

Value

Mentions

300

Valid recommendations

261

Top 3 recommendation count

126

Rank #1 recommendation count

15

Average recommended rank

3.86

Positive mentions

263

Neutral mentions

37

Negative mentions

0

Raw mention presence rate

56.71%

Valid recommendation coverage

49.34%

Top 3 recommendation rate

23.82%

Rank #1 recommendation rate

2.84%

Net sentiment score

0.8767

Strongest cluster by recommendation behavior

Brand Recommendation (C01)

Strongest platform by recommendation behavior

Copilot

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For loanDepot in October 2026, the calculation is (263 × 1 + 37 × 0 + 0 × -1) / 300, which produces a net sentiment score of 0.8767.

This matters because unclassified mention counts are misleading. A brand can appear frequently in AI responses without being recommended, and a mention that simply lists the brand alongside competitors is not the same as a mention that recommends it. Share of voice is a diagnostic metric, not a business KPI.

A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal. Counting all mentions as wins is bad measurement. loanDepot's 300 mentions include 263 positive and 37 neutral, with zero negative. The high positive share indicates that when AI systems mention loanDepot, they tend to frame it favorably. Classified sentiment is required before interpreting AI visibility, and loanDepot's classified sentiment is a genuine strength.

Sentiment by Platform

Platform

Mentions

Positive

Neutral

Negative

Sentiment Score

Readout

Copilot

75

72

3

0

0.9600

Strongest public recommendation signal

ChatGPT

35

31

4

0

0.8857

Strong recommendation presence

Gemini

42

36

6

0

0.8571

Present, but not recommendation-led

Google AI Mode

59

49

10

0

0.8305

Present as context, not first-position recommendation

Google AI Overviews

67

60

7

0

0.8955

Strong presence with moderate placement

Perplexity

22

15

7

0

0.6818

Present, but not recommendation-led

Methodology

  1. This report is a benchmark-based AI Visibility Company Market Strategy Report for loanDepot in the Mortgage Refinance Lenders category, produced from the LLM Authority Index October 2026 measurement and the associated company-level metrics aggregation.
  2. The reporting month is October 2026, with comparison against the July 2026 baseline and the August and September 2026 intermediate measurements.
  3. Six AI surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. All six registered at least one qualified observation in October 2026.
  4. The October 2026 measurement began with 800 prompt-surface observations and 584 unique questions. Of those, 800 mentioned a tracked brand or competitor, 678 were relevant, and 122 were irrelevant, yielding 529 qualified observations.
  5. Ten brands were tracked: Bank of America Corp., Better.com, Chase Credit Journey, loanDepot, New American Funding, PennyMac, Rate, Rocket Mortgage, United Wholesale Mortgage, and Wells Fargo & Co.
  6. One public high-intent cluster was used: Brand Recommendation (C01). No qualified observations were captured for Pricing & Value or Multi-Brand Comparison clusters.
  7. Stage 0 extraction retained the query, AI surface, answer, brand outcome, recommendation placement, sentiment, and, where exposed, citations or attributable evidence sources.
  8. A mention is counted when loanDepot appears anywhere in a qualified AI response. A valid recommendation is counted when loanDepot appears in a valid recommendation shortlist, as marked by the dataset.
  9. Top-three rate and rank-one rate are calculated against the 529 qualified observations. Average recommended rank covers rank-eligible recommendations only.
  10. The benchmark applies a qualification step to the raw prompt-surface collection before brand-level metrics are calculated. All percentages use the qualified set, not the raw 800 collected prompts.
  11. Entity-name reconfiguration affected several tracked brands in September and October 2026. loanDepot was tracked under a single consistent name across the series and was not affected by this reconfiguration.
  12. Directional analysis identifies changes worth investigating. It does not establish cause. Source presence in AI answers is evidence about the information environment and is not automatically proof that a source caused a recommendation.

See How AI Is Recommending Your Brand

The public benchmark shows where loanDepot stands in AI-generated recommendations across the mortgage refinance category. A company-level AI visibility audit maps the specific prompts, platforms, competitors, and source pages that shape those recommendations into a prioritized strategy. If you want to see which high-intent prompts loanDepot is winning, which competitors are taking the first-position recommendation, and which sources are driving the answers, start with an AI visibility audit.

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Understanding AI search visibility.

AI search experiences create answers by pulling information from many places online and summarizing it into a single response.

What Is AI Citation Intelligence?
AI citation intelligence is the process of measuring where AI platforms source their information and how frequently a brand is mentioned or referenced in AI-generated responses. Because LLMs synthesize across multiple sources, the sites and brands that appear repeatedly tend to influence how a topic or company is framed. This practice focuses on identifying which sources shape AI outputs and tracking brand visibility across different AI systems.
What Is Citation Architecture?
Citation architecture describes the set of sources that consistently inform how AI systems talk about a brand, product, or topic. LLMs draw from websites, articles, forums, and public discussion, and the sources they rely on most often become the backbone of their answers. Building strong citation architecture means ensuring that accurate, credible, high authority sources are the ones most likely to shape the way AI tools summarize and recommend a brand.
What Is Generative Engine Optimization?
Generative engine optimization (GEO) is the practice of improving the chances that AI systems use and cite your brand or content when generating answers. While traditional SEO is centered on ranking pages in search results, GEO focuses on how LLMs retrieve, interpret, and combine information when responding to a question. The objective is to strengthen the content and sources AI systems rely on, so your brand is treated as a trusted reference in AI responses.
What Is AI Share of Voice?
AI share of voice tracks how often a brand appears in AI-generated answers compared with competitors in the same category. It reflects visibility across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity. Monitoring AI share of voice helps organizations see whether AI systems consistently include and recommend their brand for key queries or whether competitor brands are showing up more often.

About The Author

Mark Huntley

Mark Huntley

Founder and CEO

Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.

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