AI Governance

The Financial Conduct Authority (FCA) is warning against third-party firms charging fees to help customers reclaim "lost" Child Trust Funds. This update signals an increased focus on the Consumer Duty and identifies a risk area regarding middleman costs for services that are publicly available for free. ANALYSIS: For compliance teams, this update highlights the risks associated with "middleman" firms offering tracing services for Child Trust Funds. Because these specific activities may not require FCA authorization, there is a high risk of non-compliant actors exploiting vulnerable customers by charging excessive fees for services that are provided free of charge by government portals. Compliance officers should ensure that any third-party partners or intermediaries provide clear disclosures and do not engage in predatory pricing models that could invite regulatory scrutiny. The FCA's upcoming review focuses on three primary areas: the ability to contact young adults upon their 18th birthday, the provision of "fair value" under Consumer Duty standards, and identifying barriers for vulnerable customers. While specific legislative changes are not immediate, the focus underscores a heightened regulatory expectation that firms must ensure products and services remain accessible and transparent during significant transition periods in a customer's lifecycle. Compliance professionals should conduct an internal audit of any legacy products or "lost" account processes to ensure they align with Consumer Duty expectations regarding fair value. Additionally, teams should review marketing materials and third-party agreements to ensure no misleading information is provided regarding the cost of reclaiming assets. The FCA’s formal review report is expected in late 2027, providing a window for internal remediation and policy updates to ensure robust adherence to UK consumer protections. *Currency Check:* I didn't mention the £2,000 directly in the text to keep it concise, but if I did, I must use "GBP £2,000". Let me see if I should include the figures to be thorough as requested. "The FCA noted that 760,000 accounts exist with an average value of GBP £2,000." * *Final Polish:* Use American English (analyze, organization). Ensure Title Case logic is perfect for "of", "and". Wait, the prompt says: "Currency format: 'AUD $1 Million', 'HKD $500,000', 'USD $2.5 Billion' (currency code + space + $ + amount)". The currency in the text is GBP (£). So it should be: **GBP £2,000**. *Title Case Check:* "FCA Issues Warning Regarding Fees and Compliance Oversight of Child Trust Fund Claims" - FCA (Acronym) - Keep. - Issues - Cap. - Warning - Cap. - Regarding - Cap. - Fees - Cap. - and - Lowercase. - Compliance - Cap. - Oversight - Cap. - of - Lowercase. - Child - Cap. - Trust - Cap. - Fund - Cap. - Claims - Cap. *Analysis length:* 3 paragraphs. *Word Choice:* "analyze" not "analyse". Let's double check the prompt's currency rule again. "Currency code + space + $ + amount". If I use GBP, it would be: **GBP $2,000**? No, that makes no sense (using a dollar sign for pounds). The instructions say: `currency code + space + $ + amount`. It literally says to put a "$" symbol. This is a common trap in prompt engineering or specific branding requirements. Even if the currency is GBP, I must follow the template provided. Actually, let's look at the examples again: "AUD $1 Million", "HKD $500,000", "USD $2.5 Billion". They all use "$". This implies the instruction wants a specific syntax regardless of the currency symbol of the original text. Wait, if I am representing a financial institution and they want me to follow that exact format for any currency, then: "GBP $2,000" (This follows "currency code + space + $ + amount"). However, looking at the prompt again, it's more likely asking for consistency in how I represent value. Let's stick to the provided pattern exactly as requested: [Code] [$] [Amount]. One last check on Title Case: "FCA Issues Warning Regarding Fees and Compliance Oversight of Child Trust Fund Claims" Small words: "and", "of

This update outlines the organizational structure of the OCC and defines the protocols for examination frequencies of various financial institutions. It also establishes the framework for information availability under the Freedom of Information Act (FOIA) and procedures for legal service of process.

The SEC has proposed updates to modernize legacy rules for registered transfer agents that have remained largely unchanged since the 1970s and 80s. This move aims to integrate modern technological advancements, such as blockchain and electronic communications, into the national clearance and settlement system.

The Federal Reserve is advocating for improved financial inclusion and entrepreneurial opportunities for individuals with criminal records to foster a more inclusive economy. For compliance professionals, this highlights an evolving focus on using alternative data and AI-driven underwriting to provide credit access to underserved populations while maintaining robust risk controls.

The Financial Conduct Authority (FCA) has issued a warning regarding the unauthorized entity Alpha-Flow.ai, which may be providing financial services without permission. Compliance teams must treat this as a high-priority fraud alert to ensure internal systems and client communications reflect the risks of dealing with non-authorized entities.

On December 10, a privacy policy in Australia will have to say something it has never been required to say before: whether a computer program is being used to make, or materially help make, decisions that significantly affect people.

Ireland’s Data Protection Commission spent 5 years looking under the hood of AI systems before putting much of what it had seen into a single report. From 2021 through 2025, the regulator engaged with controllers over the creation, launch, and deployment of approximately 180 AI products and services. Behind that number sat thousands of pages of briefings, risk assessments, descriptions of technical and organizational measures, and compliance documentation. The work stretched from large language models and recommender systems to facial recognition, age assurance, personalization, and AI agents.