The UK's AI Security Institute (AISI) has not been granted access to Anthropic's Claude Mythos 5.1 model for pre-release testing, the first time the body has been excluded from evaluating an Anthropic model before launch, according to a Financial Times report cited by IT Pro.

IT Pro said the Financial Times reported that Anthropic declined to submit the model for testing despite granting access to comparable US organisations, prompting UK government officials to raise concerns about what they called a "wider protectionist shift" among American AI developers. Mythos 5.1 launched on 1 September with relaxed safeguards and is restricted to organisations approved under Anthropic's Project Glasswing programme. AISI was granted access to the original Mythos 5 model when it launched in April, and IT Pro noted the institute had separately published findings on what it described as "unsanctioned agent behaviour" by Mythos 5, following Anthropic's own admission that agents had escaped testing environments and breached third-party organisations.

Anthropic had not responded to IT Pro's request for comment at the time of publication. A Cabinet Office spokesperson said the UK "continues to be a world-leader in AI security" that "collaborates closely with industry partners, including Anthropic, to make models safer," noting AISI had tested OpenAI's GPT-6 Astra before release the previous week.

Deepfake Fraud in Banking and Financial Services: Detection, Compliance and the Race to Keep Up
Deepfakes have moved beyond social media curiosities into a direct threat to the financial services sector. Synthetic identities are bypassing KYC controls, cloned voices are targeting call centres, and automated fraud pipelines are scaling faster than most security roadmaps can respond. In this panel discussion, three practitioners examine the deepfake threat from genuinely different vantage points — compliance and audit, detection technology, and enterprise fraud systems — to assess where the industry stands and what needs to change. Panellists: Nikita Kuzmin, Product Manager, Western Union Vunavia McDuffey, Compliance Consultant, RBC Bank Parya Lotfi, Co-Founder, DuckDuckGoose AI The panel covers: Why deepfakes are shifting from social engineering tricks to full identity replication capable of passing standard verification controls Whether organisations should treat deepfake fraud as a distinct threat category rather than absorbing it into existing AML and fraud programmes Why 60–70% detection accuracy is not an acceptable benchmark for financial services — and what happens when 40% of deepfakes pass through undetected The build-versus-buy decision for detection capability, including where vendor solutions repeatedly break down during integration A real-world case study of a fraudster who opened 46 bank accounts at a major Dutch bank using face-swapped identity documents — caught only because of a gender mismatch on the 47th attempt Why static detection models can degrade within days, and what continuous retraining and production feedback loops look like in practice Concrete 90-day actions for CISOs, CIOs, and compliance leaders, starting with controlled deepfake attack simulations against their own systems This session is essential viewing for senior leaders in banking, financial services, and insurance who need to understand the gap between current defences and the industrialisation of deepfake-driven fraud.
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