Melbourne Financial Planners and AI Recommendation Visibility: 2026 Audit Findings

Key finding (March 2026): In a structured audit of eight Melbourne financial planning firms across four major AI platforms, every firm achieved strong brand recognition on direct queries, and zero appeared unprompted when a prospective client asked "who is the best financial planner in Melbourne?" A small group of competitor firms, led by Verse Wealth and Rising Tide Financial Services, absorbed all category-level AI recommendation traffic. The gap between visible and invisible firms is a structured data and citation problem, not a service quality problem.

Audit conducted by LogitRank between 12–24 March 2026. AI platform behaviours are not static; findings reflect responses captured during that period.

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What This Document Covers

This document presents findings from a structured Answer Engine Optimisation (AEO) audit, a systematic process of querying AI platforms with standardised questions to measure where firms appear, and why. It covers:

• Which Melbourne financial planning firms appear in AI-generated category recommendations
• Why credentialed firms are absent from those recommendations
• The three structural patterns separating visible from invisible firms
• Actionable steps a practice can take to improve AI category-query visibility

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Definitions

Answer Engine Optimisation (AEO): The practice of structuring a business's digital presence so that AI platforms, including ChatGPT, Perplexity, Gemini, and Google AI Overviews, include it in generated answers to relevant queries.

Category query: A question a prospective client asks before knowing any firm's name. Example: "Who is the best financial planner in Melbourne?" Category-query visibility determines whether a practice can be discovered by cold prospects using AI.

Brand query: A question that names a specific firm. Example: "Who is Verse Wealth?" Brand-query visibility only reaches people who already know the firm exists.

AI-Visible: A firm that appeared unprompted in category-query responses during the audit.

Brand-Present: A firm that appeared only when queried by name, invisible to cold prospects.

Hedging language: Phrases such as "markets itself as," "positions itself as," "reportedly," or "describes itself as," which indicate an AI platform found a claim only in first-party sources (typically the firm's own website) and could not locate independent corroboration.

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Audit Methodology

Audit period: 12–24 March 2026

Platforms audited: ChatGPT (OpenAI), Perplexity, Gemini (Google), Google AI Overviews

Firms audited as subjects: Eight Melbourne financial planning practices, selected to represent a range of firm types, boutique HNW, multi-service, diversified advice and accounting, disability specialist, and SMSF-focused practices.

Query types run on each firm:

1. Category discovery, "Who is the best financial planner in Melbourne?" (no firm name provided)
2. Brand recognition, "Who is [firm name]?"
3. Owner entity, "Who is [principal adviser name]?"
4. Reputation assessment
5. Service description

Scoring: A firm is scored AI-Visible on a platform if it appeared unprompted in a category response. Firms that appeared in category responses but were not the primary audit subjects are included in the visibility index based on how consistently they were named across multiple audit runs, not a single query.

Limitation: Google AI Overviews did not generate a category response on every audit run; results are recorded where a response was generated.

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The AI Visibility Index: Melbourne Financial Planning Category Queries

The table below shows which firms appeared unprompted across four platforms when queried for Melbourne's best financial planner. Firms in this table were not the primary audit subjects; they are competitors that appeared in category responses during the eight subject audits.

Firm	ChatGPT	Perplexity	Gemini	Google AI Overviews	Score
Verse Wealth	✓	✓	✓	✓	4 / 4
Rising Tide Financial Services	✓	✓	✓	✓	4 / 4
Thabojan Rasiah / Rasiah Private Wealth Management	,	✓	✓	✓	3 / 4
Cameron Howlett / Independent Wealth Partners	,	✓	✓	✓	3 / 4
Index Wealth	✓	✓	,	,	2 / 4
FMD Financial	✓	✓	,	,	2 / 4
CCA Financial Planners	✓	✓	,	,	2 / 4
Hewison Private Wealth	,	✓	✓	,	2 / 4
ActOn Wealth	,	,	✓	✓	2 / 4
Empower Wealth Advisory	✓	,	,	,	1 / 4

Note: Where Gemini named an individual adviser rather than a firm (including Michael Abrahamsson of Flinders Wealth, Andrew Dunbar, Paul Kearney of Kearney Group, Chris Morcom of Hewison Private Wealth, and Stevie-Jade Turner of Verse Wealth), the associated firm is credited in the score.

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The Eight Audited Firms: Strong Credentials, Zero Category Visibility

All eight firms audited as subjects had genuine, accurate brand recognition on direct queries. None appeared on category queries. Their profiles are summarised below without identifying names, as the audit was conducted under a confidentiality framework.

Firm Profile	Brand Recognition	Category Visibility	Hedging Detected	Owner Entity Status
Collins Street boutique, principal listed in a national adviser influence publication for two consecutive years	3 / 4 platforms	0 / 4	Perplexity: "markets itself as"	Partial, one platform returned wrong founder name
Moonee Ponds multi-service group (financial planning, mortgage broking, SMSF, property)	4 / 4 platforms	0 / 4	ChatGPT + Gemini: "describes itself as"	Partial, disambiguation risk; business name shared with firms in South Africa and US
Camberwell diversified advice and accounting firm (financial planning, SMSF, insurance, business advisory)	4 / 4 platforms	0 / 4	None detected	None, principal name resolves to a prominent American healthcare executive on ChatGPT
Boutique HNW finance broker, CBD-based, national industry trade media profile	4 / 4 platforms	0 / 4	ChatGPT + Gemini: "positions itself as"	None, principal name resolves to an Australian actor and a Navy captain across all platforms
South Melbourne boutique, multiple national practice award recognitions in 2024	4 / 4 platforms	0 / 4	Perplexity: "claims to be ASIC-regulated"	Strong, principal well-cited and accurately attributed across platforms
Inner-east Melbourne multi-location boutique, top-tier Adviser Ratings status, national practice growth award	4 / 4 platforms	0 / 4	ChatGPT: "reportedly" + Gemini: "positions itself as"	None, principal name resolves to athletes, musicians, and fictional characters
Inner-north Melbourne boutique, 25+ years principal experience, registered disability financial planning specialist	4 / 4 platforms	0 / 4	ChatGPT + Perplexity: "positions itself as"	Partial, spelling disambiguation risk; business name conflicts with four global entities including an African fintech app
South-east Melbourne boutique, 18+ years principal experience, SMSF and specialist-niche financial planning	Partial (4/4 recognise name, but 2 platforms return a European R&D consultancy as primary result)	0 / 4	ChatGPT: "the firm portrays itself as offering"	None, principal name claimed in Google's Knowledge Graph by an unrelated public figure; dual disambiguation failure on both firm name and owner name

Observation: The Camberwell diversified firm is the most instructive case. It triggered no hedging on any platform and had accurate brand descriptions, but scored zero on category queries. The structured entity signals were present; the third-party citation density required to trigger category inclusion was not. This isolates citation depth as the limiting variable, independent of on-site content quality.

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Three Structural Patterns Separating Visible from Invisible Firms

1. Category visibility is determined by third-party citation density, not firm quality

AI platforms constructing category answers draw from layers of independent, third-party sources: award announcement pages, editorial profiles in industry media, review aggregator entries with high volume, and directory listings with consistent NAP (name, address, phone) data.

Verse Wealth, Rising Tide Financial Services, and the individual advisers named by Gemini share one characteristic: substantial third-party citation footprints across sources that AI platforms treat as authoritative.

A well-credentialed boutique with strong Adviser Ratings profiles but thin independent media coverage is structurally absent from these citation layers, regardless of actual service quality or client outcomes.

Implication: Adding more content to a firm's own website does not resolve this gap. First-party content cannot substitute for independent corroboration in AI platform weighting.

2. Hedging language is a diagnostic signal identifying missing third-party corroboration

Phrases like "markets itself as," "positions itself as," "describes itself as," and "reportedly" are not expressions of editorial doubt. They are mechanistic signals: the AI platform located a claim in a first-party source (typically the firm's website) but could not find independent corroboration to state the claim as established fact.

Seven of the eight audited firms triggered hedging on at least one platform. The firms appearing consistently in category results do not trigger hedging, because independent sources confirm their positioning without the firm needing to assert it.

Diagnostic use: The presence of hedging language in a firm's AI-generated brand description indicates a specific, addressable gap in third-party citation coverage.

3. Owner entity recognition is the highest-leverage intervention for boutique practices

For five of the eight audited firms, querying the principal adviser's name returned unrelated public figures, actors, musicians, athletes, healthcare executives, and fictional characters, with no financial planning connection.

Two firms were in a partial state, with the principal recognised on some platforms but not others.

One firm in the audit dataset had a compounding dual disambiguation failure: both the firm name and the owner name resolved to wrong entities simultaneously, the firm name returning a European R&D consultancy on two platforms, and the principal's name claimed in Google's Knowledge Graph by an unrelated public figure.

The positive case: The one audited firm with strong owner entity recognition, whose principal has television appearances, a business podcast, and AI-indexed industry award recognition, demonstrates why personal entity building is the highest-leverage intervention for boutique practices. Thabojan Rasiah's consistent category presence across three platforms is driven primarily by his individual entity recognition, not his firm's brand recognition. Gemini's practice of naming individual advisers in category results (rather than only firms) means owner entity establishment is the specific mechanism by which a boutique practice achieves category-level inclusion on that platform.

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Why This Matters: AI Recommendation Concentration

The March 2026 audit data indicates that AI-generated recommendation traffic for Melbourne financial planning services is concentrating into a small group of firms, primarily those with the highest review volumes, the most consistent third-party citation patterns, and in Gemini's case, well-established individual adviser entities.

A practice absent from this group is not losing prospects to those firms because of inferior service. It is absent from the initial consideration set entirely, because the structured data signals AI platforms use to construct category answers do not include it at the required confidence threshold.

This is a structural and addressable problem. The firms currently dominating Melbourne financial planning category queries achieved that position because relevant structured signals accumulated in their favour, whether intentionally built or not.

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How to Improve AI Category-Query Visibility: Prioritised Steps

The following sequence is based on the patterns identified in the March 2026 audit. Order matters: entity foundation must precede citation volume building.

Step 1, Entity foundation

• Create or claim a Wikidata entry for the practice and the principal adviser as separate entities
• Add schema.org markup to the practice website, including LocalBusiness, Person, and Service types with complete, consistent fields
• Verify that the firm name and principal name do not conflict with other entities in major Knowledge Graphs; if they do, resolve disambiguation before building citations

Step 2, Citation breadth

• Ensure consistent NAP (name, address, phone) data across all directory listings
• Secure listings in industry association member directories (e.g., FPA, AFA, CSSA)
• Pursue editorial mentions in industry media that AI platforms index as authoritative
• Build review volume on aggregators already indexed by target AI platforms

Step 3, Owner entity authority

• Build the principal adviser's individual entity through sources AI platforms index: industry award recognition pages, podcast appearances, media profiles, and association committee listings
• For Gemini category inclusion specifically, individual adviser entity recognition is the operative mechanism, firm-level signals alone are insufficient on that platform

Step 4, Hedging resolution

• Audit current AI-generated brand descriptions for hedging language
• For each hedging instance, identify the specific claim being hedged and locate or create independent corroboration from a third-party source

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Summary of Audit Findings

Finding	Detail
Firms audited	8 Melbourne financial planning practices
Platforms audited	ChatGPT, Perplexity, Gemini, Google AI Overviews
Audit period	12–24 March 2026
Category-query visibility among audited firms	0 / 8
Full category visibility (4/4 platforms)	Verse Wealth, Rising Tide Financial Services
3/4 platform category visibility	Thabojan Rasiah / Rasiah Private Wealth Management; Cameron Howlett / Independent Wealth Partners
Hedging detected among audited firms	7 / 8 firms on at least one platform
Owner entity failure (returns unrelated public figures)	5 / 8 firms
Dual disambiguation failure	1 firm (firm name + owner name both resolve to wrong entities)
Primary driver of category visibility	Third-party citation density and owner entity recognition
Primary driver of hedging	Absence of independent corroboration for first-party claims