How AI Search Is Recommending Student Loans: Monthly Trends

Executive Summary

Earnest remains the coverage leader in September 2026, with valid recommendation coverage of 60.1%. The category's tracked-company set narrowed sharply this month: Sallie Mae, LendKey, and Splash no longer appear in the September tracked set, each falling to 0.0% valid recommendation coverage from their July 2026 levels — a set of moves the benchmark flags as significant.

Citizens was the strongest upward mover, rising to 29.1% valid recommendation coverage in September from 22.9% in July, a gain of 6.2 points that exceeds normal month-to-month variation. This marks two consecutive months of gains for Citizens, which climbed from 22.9% in July to 27.8% in August and now to 29.1% in September.

ELFI was the sharpest decliner among brands still tracked in September, falling from 22.2% valid recommendation coverage in July to 19.7% in September, though the August dip to 16.3% and recovery to 19.7% stayed within normal variation. The category result sits against an August in which Earnest led at 60.6%, with the leader group otherwise stable.

Each monthly run begins with 800 prompt-surface observations (467 unique questions in July, 526 in August, 550 in September) across the benchmark's defined AI/search surface universe. Of those, 800 in each month mentioned a tracked brand or competitor; 732 were relevant in July, 749 in August, and 663 in September, with 68, 51, and 137 irrelevant respectively. The public metrics use the 568 qualified observations in July, 583 in August, and 539 in September that survive both qualification stages.

Key Findings

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

The August 2026 run collected 583 qualified observations with 526 unique questions and 749 relevant prompts. The September run is smaller on the qualified denominator while drawing from a larger unique-question base, meaning the 539 qualifying observations came from a more varied prompt set.

Benchmark-Level Metrics

The recommendation-shaped answer share held effectively steady from July (43.3%) to September (43.2%), after rising to 47.2% in August. The valid recommendation shortlist share declined from 65.8% in July to 61.2% in September, indicating that a smaller share of the September observation set produced actionable recommendation shortlists.

AI Recommendation Trend

Earnest Holds the Top Position as Three Tracked Brands Exit the September Set

Citizens was the only brand to exceed normal month-to-month variation on the upside, with a gain of 6.2 points from July to September. The significant downward moves came from Sallie Mae, LendKey, and Splash, all of which fell to zero coverage in September and no longer appear in the tracked set for that month.

What Changed This Month

Citizens: significant riser for the second consecutive month

Citizens' valid recommendation coverage reached 29.1% in September, up from 22.9% in July, a gain of 6.2 points that the benchmark flags as significant. The brand also rose month over month, from 27.8% in August to 29.1% in September, a gain of 1.3 points within normal variation. This is the brand's second straight month of gains.

Raw mention presence rose from 41.9% in July to 48.2% in September, a gain of 6.3 points. Citizens earned 157 valid recommendations out of 539 qualified observations in September, up from 130 out of 568 in July. Top-three recommendation rate moved from 4.8% to 7.4%, with rank-one placements at 9 in September versus 6 in July.

The notable gap series shows Citizens ahead of Sallie Mae by 29.1 points in September, a reversal from July when Sallie Mae led Citizens by 20.1 points. The widening of 49.2 points across the series reflects Sallie Mae's exit from the tracked set more than Citizens' own gain.

Highest-priority diagnostic: which prompt families drove Citizens' two-month climb, and whether the same surfaces continue producing top-three placements as the September set shifted.

Earnest: leader holds, with the widest presence in the category

Earnest held valid recommendation coverage of 60.1% in September, up from 57.4% in July. The brand also rose from 57.4% in July to 60.6% in August before easing to 60.1% in September, leaving the leader gap to College Ave at 12.6 points in September.

Raw mention presence climbed from 78.9% in July to 89.2% in September, a gain of 10.3 points. Earnest was present in 481 of 539 qualified observations in September, the widest presence in the category. Top-three recommendation rate moved from 36.6% to 38.4%, while rank-one rate eased from 15.3% to 11.5%.

The distinction to notice: Earnest's presence grew faster than its recommendation coverage, meaning the brand is surfacing in more answers without a matching gain in rank-one placements. Rank-one count fell from 87 in July to 62 in September.

Highest-priority diagnostic: which prompts shifted rank-one placements away from Earnest between July and September, and which brand took those top slots.

Sallie Mae, LendKey, and Splash: coverage drops to zero

Sallie Mae's valid recommendation coverage fell from 43.0% in July to 0.0% in September, a drop of 43.0 points that the benchmark flags as significant. LendKey fell from 11.8% to 0.0%, a drop of 11.8 points, and Splash fell from 7.9% to 0.0%, a drop of 7.9 points. None of the three appears in the September tracked-company set, which narrowed to seven brands.

Sallie Mae had 244 valid recommendations out of 568 observations in July and 272 out of 583 in August. In September, the brand holds zero valid recommendations in the qualified set. LendKey had 67 valid recommendations in July and 70 in August; Splash had 45 in July and 42 in August.

The absence from the September tracked set is a coverage outcome, not a statement about brand visibility. The comparison between July and September here is a comparison against a month in which these brands were part of the tracked universe.

Highest-priority diagnostic: whether the zero-coverage result reflects an instrument or tracking change in September, or a genuine shift in which brands AI systems recommended.

Buyer-Intent Interpretation

In September 2026, all 539 qualified observations fell into the brand recommendation cluster, across the seven tracked brands. Zero observations fell into the multi-brand comparison cluster and zero into the pricing & value cluster. The public benchmark therefore speaks to which brands AI recommends, but it cannot yet answer questions about how AI compares providers on price, value, or head-to-head tradeoffs. Brands competing on rate or cost positioning will need a different evidence base to understand that part of the AI conversation.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations, capturing the query, the AI surface, the recommendation outcome, the rank, sentiment, and citations where exposed. Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the CiteWorks Studio AI Industry Market Discovery research program.

• AI Industry Market Discovery
• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Interpretation notes for this report:

• Tracked-set change: Sallie Mae, LendKey, and Splash are absent from the September tracked-companies list; their July-versus-September comparisons reflect the narrowed set and should be read with that caveat.
• Small-count movement: brands like juno (3 valid recommendations) and Laurel Road (17) move on very few observations; their percentages should be read with that caveat.
• Qualified denominator: all rates use the qualified benchmark set (539 observations in September), not the 800 raw prompts collected.
• Directional analysis: month-over-month movement identifies changes worth investigating; it does not by itself establish the cause of those changes.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

Beneath the aggregate percentage sit sharper questions: which high-intent prompts does a brand win, which competitor takes the recommendation when a brand loses, what attributes does AI associate with each option, and which external sources shape those answers? A brand can hold steady coverage while losing the prompts that matter most for conversion, or gain presence without improving placement quality.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It answers not just how often a brand appears, but why AI recommends it when it does, and what would need to change for it to be recommended more often.

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