Financial Technology and Banking Software: AI Market Discovery Index

Benchmark Summary

Mambu led the Financial Technology and Banking Software benchmark in September 2026, with valid recommendation coverage of 33.6%, ahead of Thought Machine at 31.2% (a gap of 2.4 percentage points). No tracked brand's month-over-month move exceeded normal variation this month, a quieter period after the sharp rises that marked the series beginning. Azentio Software and SAP Fioneer each eased slightly from their August levels, but no brand recorded a significant decline in valid recommendation coverage in September 2026.

The series began in July 2026 with all ten brands at 0.0% coverage. By September 2026, Mambu, Thought Machine, Q2, and Avaloq had all risen beyond normal variation from that baseline. Mambu rose from 0.0% in July 2026 to 33.6% in September 2026, Thought Machine from 0.0% to 31.2%, Q2 from 0.0% to 4.7%, and Avaloq from 0.0% to 3.9%. Each of these four brands improved in each of the two months since July 2026. A two-brand leadership tier has separated from the remaining field. The benchmark began with 400 prompt-surface observations in July 2026 and 800 in each of August and September 2026, producing 15, 144, and 128 qualified observations respectively after qualification.

Current Benchmark at a Glance

In August 2026, the intermediate month, qualified observations reached 144 and recommendation-shaped answer share peaked at 11.1% before settling to 2.3% in September 2026. Qualified surface breadth counts the canonical AI/search surface families with at least one qualified observation: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. The benchmark measured four of these families in July 2026 and all six in August and September 2026.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Financial Technology and Banking Software

Research Scope and Qualification

The public benchmark is narrower than the raw collection universe by design. The table below shows how the raw prompt collection narrowed to the qualified observations that form the public denominator.

Brand-level percentages use the qualified observations as the public denominator, not the raw collection. See the AI Market Discovery Methodology for full details.

Current Brand Standings

This table is the primary current-month benchmark view, sorted by valid recommendation coverage.

How to Read the Standings

• Presence rate: the share of qualified observations in which the brand is mentioned at all, whether or not it is recommended.
• Valid recommendation coverage: the share of qualified observations in which the brand appears in a valid recommendation shortlist.
• Top-three rate: the share of qualified observations in which the brand appears among the top three recommended options.
• Rank-one rate: the share of qualified observations in which the brand is recommended as the single best option.
• Net sentiment: the balance of positive over negative mentions, scaled from -1 to +1.

For formulas and denominator rules, see AI Market Discovery Metric Definitions.

Recommendation Coverage Movement

Between August 2026 and September 2026, the month-over-month moves were more modest. Mambu rose 1.7 points from 31.9% to 33.6%, Thought Machine rose 3.4 points from 27.8% to 31.2%, Q2 rose 1.2 points from 3.5% to 4.7%, and Avaloq rose 1.1 points from 2.8% to 3.9%. No tracked brand exceeded normal month-over-month variation in September 2026, a quieter period after the series-opening surges. Azentio Software and SAP Fioneer each eased from 1.4% in August 2026 to 0.8% in September 2026, within normal month-to-month variation.

Significant Risers: Mambu, Thought Machine, Q2, Avaloq

Mambu recorded the largest rise in the series, from 0.0% in July 2026 to 33.6% in September 2026 (43 of 128 qualified observations). Its presence rate climbed to 98.4%, and its rank-one rate reached 10.9%. Thought Machine rose from 0.0% in July 2026 to 31.2% in September 2026 (40 of 128 observations), with presence climbing from 0.0% to 81.2% (104 of 128 observations). Q2 rose from 0.0% to 4.7% (6 of 128 observations), and Avaloq from 0.0% to 3.9% (5 of 128 observations). Q2 and Avaloq remain secondary contenders, far behind the top two. Both Q2 and Avaloq improved in each month of the series.

Stable and Absent Brands

Azentio Software and SAP Fioneer each reached 0.8% valid recommendation coverage in September 2026 (1 of 128 observations), within normal month-to-month variation. Bantotal, Silverlake Axis, Technisys, and Tietoevry Banking recorded no presence and no recommendation coverage in September 2026, holding at their July 2026 levels. Silverlake Axis had a single presence observation (0.7%) in August 2026 but none in September 2026.

Recommendation Placement Snapshot

Coverage alone does not show how prominently a brand is recommended. The table below shows top-three and rank-one rates for the leading brands by valid recommendation coverage.

Similar coverage levels can still hide very different first-position rates. Mambu converted most of its top-three placements into rank-one recommendations (10.9% of 11.7%), whereas Thought Machine reached a top-three rate of 10.2% but a rank-one rate of just 0.8%. Thought Machine's rank-one rate is closer to Q2, which held a 2.3% top-three rate and no rank-one placements.

Buyer-Intent Distribution

All 128 qualified observations in September 2026 fell into the Brand Recommendation class, where a buyer is seeking a brand to meet a stated need.

The current public series measures the Brand Recommendation class of discovery and does not yet contain qualified observations in the Pricing & Value or Multi-Brand Comparison classes. Pricing, value, and head-to-head comparison have no public signal in this data.

Historical Measurement Record

This is an evergreen benchmark URL. New measurements are added to the same report.

Evidence and Source Layer

The benchmark is built from prompt-level observations that retain the query, AI/search surface, answer, brand outcome, recommendation placement, sentiment, and, where exposed, citations or attributable evidence sources. Source presence is evidence about the information environment. It is not automatically proof that the source caused the recommendation.

Scope Boundaries

This public benchmark does not measure the following:

• Market share or sales attribution
• Every possible AI response to a given question
• Organic-search ranking
• Social mention volume
• Private or sponsored channels
• Causality from a metric movement alone

About This Benchmark

The LLM Authority Index AI Market Discovery Index tracks how AI search and assistant surfaces present brands in response to natural-language discovery prompts. It measures presence, recommendation coverage, placement, and sentiment for each tracked brand across six canonical AI surface families.

• AI Market Discovery Methodology
• AI Market Discovery Metric Definitions
• AI Market Discovery Research Standards
• Modeled AI Authority Value

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The public industry benchmark shows category-level standings. A company-level Authority Index can go deeper. The public percentages cannot identify the prompts, competitors, or sources driving your brand's result.

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