8 | Acquisition International, January 2026 Why SEO Has Become an Important Compliance Consideration for Financial Services in the Age of AI lobal investment in artificial intelligence across financial services is projected to grow from USD 38.36 billion in 2024 to USD 190.33 billion by 2030, according to a 2024 market forecast by Markets and Markets. At the same time, UK regulators report that AI adoption is already widespread across the sector. A joint 2024 survey by the Bank of England and the Financial Conduct Authority found that 75 percent of UK financial services firms are already deploying AI, with a further 10 percent planning adoption within the next three years. As AI adoption accelerates, search visibility in finance is no longer dictated by traditional rankings alone. AI overviews, gen AI assistants and zero-click results now sit between customers and brand websites, reshaping how trust, authority and compliance are interpreted online. In this environment, SEO is no longer just a growth channel. It has become a frontline control mechanism for accuracy, regulatory alignment and brand credibility. To address this shift, AccuraCast has published its definitive SEO Guide for Financial Services, outlining the structural, technical and governance frameworks required for finance brands to remain visible and compliant in an AI-first discovery landscape. The insights below come from Lourenço Caliento Gonçalves, SEO Consultant at AccuraCast, who works directly with banks, insurers and fintech firms navigating this changing search environment. 1. SEO in an AI Summary World AI Overviews and assistants now sit between users and brand sites, especially on “what/how/which account/card/loan” queries in finance. Studies on financial keywords show AI modules cite only a small set of domains per answer, so visibility is increasingly about being one of the few trusted citations rather than “position 3 vs 5”. Practical shifts for finance SEO: 1. Move from chasing every keyword to owning topic clusters where you can be the definitive, expert, frequently-updated source. 2. Design pages that both: 1. Feed AI (clear entities, schema, citations, expert authorship) and 2. Still convert in a zero click world (compelling USP, tools, calculators, comparison tables that go beyond the AI summary). 2. SEO’s Role in Accuracy and Compliance Because finance is considered a YMYL (your money, your life) category, search systems and AI models heavily weigh accuracy, disclosures and regulatory alignment. Regulators like the SEC, FCA, CFTC, BaFin, ESMA, EIOPA and EBA set rules for product communication, risk disclosure and data/privacy that directly affect how content can be written and tracked. SEO becomes a compliance ally by: • Embedding governance into content workflows: versioning, review logs, jurisdiction tagging, “last updated” labels, and mandated disclaimers on all money pages. • Hard coding technical safeguards: secure-by-default (HTTPS, HSTS), cookie and tracking consent, correct handling of PII, and robust legal/Ts & Cs/privacy internal linking so crawlers and users always see compliant context. 3. SEO Challenges When Adding AI and Automation Banks, insurers and fintechs are accelerating AI and agent use across content, but surveys show the main friction points are compliance overhead, skills gaps and governance. SEO specific pain points typically include: • Drift from brand and regulatory language: AI can introduce unapproved promises, omit mandatory risk language or hallucinate product conditions, creating both compliance and ranking risk on YMYL topics. • Inconsistent E E A T: At scale, content may lack real experts, citations and author bios, weakening trust signals for both search and AI engines that now cross check authority more strictly for finance queries. • Fragmented workflows: Legal/compliance reviews are often still manual and periodic, while AI can publish or update faster than teams can approve, which creates a backlog or the risk of rogue content going live. Mitigations that work: • Guardrailed generation: Fix templates with “non editable” compliance blocks per product/region; restrict RAG systems to source only from approved repositories. • Automated QA: AI compliance checkers that scan drafts for banned phrases, missing risk warnings and jurisdiction issues before human sign off. 4. Structured Data, Schema and Entity Optimisation As generative engines shift from keyword matching to entity and graph based retrieval, schema and entity optimisation have become core, not “nice to have”. Research from AccuraCast on GEO (SEO for AI) shows that structured data helps both classic search and RAG/AI systems understand who you are, and how qualified you are to talk about a topic. On complex, dynamic fintech websites, structured data can also help AI LLMs understand what you offer, and which pieces of content answer which intents. Key priorities for financial brands: • Implement author, organisation, financial product, FAQ, article, review and local business schema where relevant, with precise entity relationships (issuer, jurisdiction, product type, risk level, fees, eligibility). • Author schema is the most impactful for ChatGPT and AI Overviews, as it signals content authoritativeness and trustworthiness. • Build consistent entity signals across site, schema and off page: G
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