Regulatory compliance, strengthened.
Fraud detection, sharpened.
An AI governance and cybersecurity programme built for a multinational investment bank — aligning AI-driven systems with AML, KYC and MiFID II, hardening cyber defences, and sharpening fraud detection in real time.
brought into alignment
and prevention
and authentication
secured
Client
A multinational investment bank, operating at the centre of global financial markets.
Goal
To strengthen the resilience of a leading global financial institution by building robust AI governance and cybersecurity risk management — keeping regulatory compliance intact while safeguarding critical financial operations.
A bank moving fast on AI, with no framework to keep it safe.
A multinational investment bank was adopting AI across its operations, but oversight hadn’t kept pace. Every AI-driven system introduced a new question: did it comply with AML, KYC and MiFID II obligations? Regulators expected answers the bank couldn’t yet give with confidence.
Cybersecurity was under equal pressure. Financial systems and data faced sophisticated, evolving threats, and fraud was getting harder to catch in real time. The bank needed to keep innovating without opening new gaps for attackers or bad actors to exploit.
Three constraints were non-negotiable:
- AI systems had to satisfy AML, KYC and MiFID II before they satisfied anyone else.
- Cyber threats were evolving faster than the defences built to stop them.
- Fraud had to be caught in real time, not after the fact.
Governance, security and fraud detection, built as one system.
Head of AI built an AI governance framework from the ground up — policies and controls designed to keep AI-driven systems compliant with AML, KYC, MiFID II and the wider regulatory perimeter the bank operates within.
Governance built after the fact is just paperwork. This was built into the system before the first model went live.
Alongside it, a cybersecurity strategy was shaped specifically for AI-driven financial systems, reducing the risk surface as new models and tools came online. Fraud detection was rebuilt with advanced algorithms designed to catch fraudulent activity as it happened, and identity verification was strengthened to cut authentication-related risk.
Data protection advisory ran throughout, keeping sensitive financial data compliant and secure — and leaving the bank positioned to adopt future AI technologies securely and sustainably, rather than bolting on governance after the fact.
Compliance, cybersecurity and fraud detection — aligned, not bolted on.
The bank now has AI governance and cybersecurity working as one system, not two separate initiatives bolted together. Regulatory compliance, cyber resilience, fraud detection and identity verification were all strengthened in the same programme — leaving the institution ready to adopt further AI technologies securely and sustainably.
* Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.
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*Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.