Schema Markup for Financial Advisers: The Complete Technical Guide (With Code Examples)
FinancialService schema markup can improve AI citation rates by over 30%. Here's the complete guide with JSON-LD code examples any IFA can implement.
When an AI system reads your website, it does not experience it the way a human does. It does not notice your design, your photography, or the carefully chosen tone of your copy. It processes text and data. And it processes structured data — data presented in a standardised, machine-readable format — far more reliably than it processes unstructured prose.
Schema markup is the way you give AI systems (and search engines) structured, unambiguous information about your firm. For financial advisers, the relevant type is FinancialService schema. Implementing it properly can improve your AI citation rates by over 30%, according to research on structured data and AI recommendation behaviour.
This guide explains what schema markup is, which fields matter most for IFAs, and provides complete, ready-to-use code examples. It is written for practice managers and firm owners, not web developers — though you will need a developer to implement the code.
What Is Schema Markup and Why Does It Matter for AI?
Schema markup is a vocabulary of tags (technically called structured data) that you embed in your website's code to describe what your business is and what it does. It is a way of saying to AI systems and search engines: "Here is what you need to know about us, in a format you can parse without interpretation."
Without schema markup, AI systems have to infer information from your website's prose. They might find your firm name in the page title, your location in your contact page, and your services scattered across multiple pages in varying forms. They may get it right. But they may also misinterpret, miss information entirely, or develop lower confidence in their understanding of your firm.
With FinancialService schema, all of that information is presented in a single, consistent, authoritative block. The AI does not have to guess.
This matters particularly in the context of our research on AI visibility for UK IFAs. One of the consistent differences between visible firms and invisible firms was the presence of structured data on their websites. Schema markup is one of the 15 key actions on our AI visibility checklist.
The FinancialService Schema Type
The Schema.org FinancialService type is specifically designed for businesses that provide financial services. It inherits from LocalBusiness and Organization, which means you can combine all three to create a comprehensive description of your firm.
Here is what a complete, well-structured FinancialService schema looks like for a typical IFA firm:
```json
{
"@context": "https://schema.org",
"@type": ["FinancialService", "LocalBusiness"],
"name": "Smith & Partners Financial Planning Ltd",
"url": "https://www.smithpartners.co.uk",
"logo": "https://www.smithpartners.co.uk/images/logo.png",
"image": "https://www.smithpartners.co.uk/images/office.jpg",
"description": "Smith & Partners is a Chartered independent financial planning firm in Guildford, Surrey. We specialise in retirement income planning, defined benefit pension transfers, and inheritance tax strategies for professionals and business owners with investable assets above £250,000.",
"telephone": "01483 000000",
"email": "info@smithpartners.co.uk",
"address": {
"@type": "PostalAddress",
"streetAddress": "12 High Street",
"addressLocality": "Guildford",
"addressRegion": "Surrey",
"postalCode": "GU1 3AA",
"addressCountry": "GB"
},
"geo": {
"@type": "GeoCoordinates",
"latitude": 51.2362,
"longitude": -0.5704
},
"areaServed": [
{
"@type": "City",
"name": "Guildford"
},
{
"@type": "AdministrativeArea",
"name": "Surrey"
},
{
"@type": "AdministrativeArea",
"name": "South East England"
}
],
"serviceType": [
"Independent Financial Advice",
"Retirement Income Planning",
"Defined Benefit Pension Transfer Advice",
"Inheritance Tax Planning",
"Investment Management",
"Financial Planning"
],
"hasCredential": [
{
"@type": "EducationalOccupationalCredential",
"credentialCategory": "Chartered Financial Planner",
"recognizedBy": {
"@type": "Organization",
"name": "Chartered Insurance Institute"
}
}
],
"memberOf": [
{
"@type": "Organization",
"name": "Personal Finance Society"
},
{
"@type": "Organization",
"name": "Chartered Institute for Securities & Investment"
}
],
"identifier": {
"@type": "PropertyValue",
"name": "FCA Registration Number",
"value": "123456"
},
"foundingDate": "2005",
"numberOfEmployees": {
"@type": "QuantitativeValue",
"value": 8
},
"openingHoursSpecification": [
{
"@type": "OpeningHoursSpecification",
"dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
"opens": "09:00",
"closes": "17:30"
}
],
"priceRange": "££",
"sameAs": [
"https://www.linkedin.com/company/smith-partners-fp",
"https://www.vouchedfor.co.uk/financial-adviser/smith-partners",
"https://www.fca.org.uk/register/123456"
]
}
```
The Most Important Fields for AI Visibility
Not every field carries equal weight. Based on our analysis of AI recommendation patterns, these are the fields that have the greatest impact on how AI systems understand and recommend your firm:
name
Must exactly match your FCA-registered name. This is how AI systems cross-reference your schema against the FCA register, Companies House, and other authoritative sources. Any variation reduces confidence.
description
The most important text field. This should be 150–250 words that specifically describe your firm: what kind of advice you provide (independent vs restricted), who you serve, where you operate, what you specialise in, and any distinctive credentials. Write this as if explaining your firm to an intelligent stranger.
serviceType
List every service and specialism separately. "Independent Financial Advice" is too broad. "Defined Benefit Pension Transfer Advice" is specific and matches queries. Include: your primary service category, each specialist service, and any niche specialisms. This is how AI systems match your firm to specific client queries.
areaServed
Be specific about geography. Include your primary city, your county or region, and any other areas you serve. For national firms, include multiple regions. For local specialists, being specific about your geographic footprint helps AI match you to location-based queries.
identifier (FCA Registration Number)
Including your FCA registration number in structured data creates a verifiable link between your schema and the FCA register — the most authoritative source of information about UK financial advisers. This is a strong legitimacy signal.
sameAs
Link your schema to your profiles on other authoritative platforms: LinkedIn, VouchedFor, Unbiased, FTAdviser. These links help AI systems connect your schema data with the same firm on other platforms, reinforcing consistency across sources.
How to Implement Schema Markup
Schema markup is added to your website using JSON-LD (JavaScript Object Notation for Linked Data) format, embedded in a `<script>` tag in your page's `<head>` section. Here is the implementation pattern:
```html
<head>
<!-- Other head elements -->
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": ["FinancialService", "LocalBusiness"],
"name": "Your Firm Name",
... (rest of your schema)
}
</script>
</head>
```
This schema should go on your homepage at minimum. Ideally, it should also appear on your main services pages, with the `serviceType` field adjusted to reflect the specific service each page covers.
If your website is built on WordPress, plugins like RankMath and Yoast SEO have built-in schema support. For custom-built websites, you will need your developer to implement it directly in the page templates.
Testing Your Schema Markup
Before considering the work done, verify your implementation using Google's Rich Results Test (search.google.com/test/rich-results). Paste your website URL and review the extracted structured data. Errors will be flagged in red, warnings in orange.
Common errors to watch for:
- Missing required fields (name, url, and address are typically required)
- Invalid date formats (use ISO 8601: "2005-01-15" not "January 2005")
- Incorrect @type values (check schema.org for valid type names)
- Broken image URLs (test that all linked images load correctly)
Google Search Console also provides a structured data report showing which pages have schema markup and any errors detected.
Schema Markup for Individual Adviser Pages
If your website has individual pages for each adviser, add Person schema markup to each one:
```json
{
"@context": "https://schema.org",
"@type": "Person",
"name": "Sarah Chen",
"jobTitle": "Chartered Financial Planner",
"worksFor": {
"@type": "FinancialService",
"name": "Smith & Partners Financial Planning Ltd"
},
"hasCredential": [
{
"@type": "EducationalOccupationalCredential",
"credentialCategory": "Chartered Financial Planner (CFP™)",
"recognizedBy": {
"@type": "Organization",
"name": "Chartered Insurance Institute"
}
},
{
"@type": "EducationalOccupationalCredential",
"credentialCategory": "Diploma in Regulated Financial Planning",
"recognizedBy": {
"@type": "Organization",
"name": "Chartered Insurance Institute"
}
}
],
"knowsAbout": [
"Defined Benefit Pension Transfer Advice",
"Retirement Income Planning",
"Inheritance Tax Planning"
],
"description": "Sarah specialises in retirement income planning and defined benefit pension transfer advice for NHS consultants and senior medical professionals. Chartered Financial Planner with 12 years' experience."
}
```
Person schema for named advisers creates individual entity recognition — AI systems can then associate specific expertise with specific individuals at your firm, which strengthens recommendations for specialism-based queries.
How AI Reads Schema Differently From Google
Google Search primarily uses schema markup to determine eligibility for rich results (star ratings in search results, knowledge panels, etc.). The impact is visible and measurable in Google Search Console.
AI systems use schema differently. They use it as a primary data source for understanding what your firm does, which they then combine with information from your website content, directory listings, and review profiles to build a comprehensive picture. Schema markup essentially gives AI systems a verified, authoritative summary that reduces the need for inference.
This means schema markup investment has a compound effect: it not only helps AI systems understand your firm, but it also increases their confidence in the information they have gathered from other sources, because the schema confirms and corroborates it.
Schema markup is one step in a broader AI visibility strategy. For the complete picture, check where your firm currently stands with a free AI visibility score at presenzia.ai/score — it will show you exactly how AI platforms are currently interpreting your firm, and where structured data is likely to make the biggest difference.
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