Deriv’s Security-to-CTO Move Signals AI Broker Shift

TL;DR: Deriv has moved its VP of Security into the CTO seat and set a target of automating 75% of manual workflows by year-end. The broker’s CEO stated no one writes code manually anymore at Deriv, and AI agents now operate across HR, finance, compliance, marketing, and engineering. For forex and CFD operators, this is the clearest signal yet that AI-native brokerage infrastructure requires security leadership at the engineering table from day one.

The Appointment and What Drove It

Deriv named Rotimi Akinyele as its Chief Technology Officer in October 2026, pulling him directly from the security function he had led since joining the broker in July 2024. Before becoming CTO, Akinyele progressed through Security and Data, then automation work in Compliance, Data and Finance, and most recently in Trading and Antifraud. That breadth was not accidental. Deriv’s CEO, Rakshit Choudhary, framed the move plainly: “As we automate more and give agents greater access and responsibility, we have more systems and operations to secure.”

Akinyele’s pre-Deriv background reinforces why that logic holds. He served as Director in the Group Information Security Department at Dubai Holding, covering cybersecurity across hospitality, real estate, ICT, media, and education. Before that, he was Head of Information Security and Business Continuity for a government authority in Ras Al Khaimah. This is not a technology generalist stepping into a security-adjacent CTO role. It is a security specialist being handed engineering leadership because the engineering work has become inseparable from security risk.

Akinyele’s stated aim is to hold the current pace of engineering change “while making sure security and controls grow with every system we automate.” That sentence is worth noting carefully. Growth in automation and growth in controls are being treated as a single deliverable, not sequential phases.

What 75% Workflow Automation Looks Like in Practice

Deriv’s 75% manual workflow automation target by end-2026 is not aspirational language. Choudhary described in a September interview the functions already running on AI tools: HR, finance, compliance, marketing, product, and engineering. He said explicitly that no one writes code manually anymore at Deriv and that some roles previously flagged as redundant have been absorbed by automation rather than eliminated outright.

The broker has also been building dedicated AI and data hubs in Malta, Dubai, and Malaysia. These are not shared infrastructure plays. They indicate Deriv is treating AI capability as a geographic asset, distributing it across regulatory jurisdictions where it operates. That matters for a broker with a global retail client base spanning dozens of markets.

On the security automation side, Deriv has detailed a SecAI bot built with Claude-3.7 and AWS GuardDuty. The system analyses security alerts in real time and automates responses, reducing the alert-to-action window that creates exposure in high-volume trading environments. For forex acquisition teams running campaign spend at scale, the ability to keep trading infrastructure stable under load is directly tied to lead conversion rates. A platform that degrades during peak traffic loses depositing traders, not just sessions.

Why a Security Background Makes Sense in an AI-Native Org

The conventional CTO profile at a broker is an engineering leader who manages build velocity and platform reliability. That profile assumes humans write and review code, and that security is a separate governance layer. When AI agents are writing, reviewing, and iterating on their own output, that separation breaks down.

Deriv’s structure now treats security as the constraint that shapes engineering decisions from the start, not a compliance checkpoint at the end. Akinyele’s mandate includes building a software development process in which AI agents help improve their own output, with security and access controls scaling as agents gain more responsibility. This is an acknowledgment that agentic systems create attack surfaces that grow non-linearly with capability.

Operators relying on AI agents for lead qualification and customer engagement face a version of the same problem. As agents gain access to CRM data, deal status, and client history, the blast radius of a compromised or misconfigured agent expands. Deriv is building the org structure to address that problem at the engineering level. Most operators are not.

What This Means for Forex Operators

Deriv’s restructuring is a case study for any forex or CFD operator running AI tools across their stack. A few concrete implications worth tracking:

Security and engineering cannot be siloed when agents have system access. If your AI tools touch client data, compliance workflows, or trading system integrations, the person accountable for engineering velocity also needs to own the risk profile of those systems. Running them as separate departments creates a gap that agents will eventually expose.

Automation targets require governance frameworks, not just tooling. Saying 75% of workflows will be automated means nothing without a corresponding answer to who audits the agents, what access controls gate their operations, and how incidents are logged and remediated. Before scaling any automation program, a full marketing and operations audit is the baseline step most operators skip.

NAGA Group’s example adds industry context. NAGA has said AI now handles most of its chat-based customer support without human agents and has cut marketing department headcount by roughly 20% through automation. Two major brokers restructuring around automation in the same cycle is not a coincidence. It is the direction of the competitive landscape for regulated retail brokers. Operators who have not yet mapped which of their workflows are automation candidates are already running behind.

For operators managing paid acquisition programs alongside AI-driven workflows, the question is not whether to automate. It is whether the controls around your automated systems are built to the same standard as the systems themselves. Deriv’s answer is to put a security leader in charge of both.

The Broader Competitive Signal

Broker leadership appointments rarely matter to operators outside the named firm. This one does, for a specific reason: Deriv is using a structural org decision to signal where it believes the technical risk in AI deployment actually lives. The message is that AI-native brokerage operations require security architecture as a foundational layer, not a retrofit.

For operators in regulated verticals beyond forex, the pattern translates directly. iGaming operators running AI-driven player segmentation and fraud detection face the same agent-access risk profile Deriv is building around. Law firm marketing teams using AI to qualify mass tort leads are handling sensitive intake data inside systems that most firms have not formally secured at the agent level.

The surface-level story here is a CTO promotion. The operational story is that one of the more technically advanced retail brokers has decided the person best qualified to lead engineering at scale is someone whose career was built on understanding how systems fail under adversarial conditions. That is the frame operators should apply to their own AI deployments.

Whether you are scaling precision targeting programs for a CFD book or running automated onboarding for a crypto exchange, the moment AI agents touch regulated workflows, the engineering and security questions are the same question. Deriv just put that principle on an org chart.

Originally reported by Finance Magnates, October 2026.