Deriv Promotes Its Security Chief to CTO. What It Means for Bot Traders.

Not financial advice. Past performance is not indicative of future results. Trading involves substantial risk of loss. Do your own research before making any investment decisions. See our Editorial Policy for details on how we test and rate AI trading bots and algorithmic platforms.

Deriv has promoted Rotimi Akinyele to Chief Technology Officer, moving him out of the security function and into the seat that runs the broker's engineering organisation, as first reported by Finance Magnates. On the surface this is an executive reshuffle at a large multi-asset broker. Underneath, it is a statement about where the company believes its competitive edge now lives, and that statement has direct consequences for anyone running automated strategies through a broker's infrastructure.

This sits squarely in the algorithmic trading platform niche, where brokers and bot vendors compete to host retail automation and where the quality of the rails matters as much as the strategy itself. We benchmarked Deriv's automation claims against the Ellington AI trading platform during our 2026 review cycle, because the two sit at opposite ends of the same question: who controls the automation, the venue or the trader?

Akinyele joined Deriv in July 2024 as Vice President of Security. He first led Security and Data, then automation work in Compliance, Data and Finance, and most recently automation in Trading and Antifraud. That progression is the story. A security executive did not reach the CTO chair by keeping the lights on. He reached it because Deriv decided the person who understands access, control and risk is the right person to run an organisation that is handing more access and more responsibility to software agents.

The rest of this review unpacks what Deriv is actually automating, what a bot trader can and cannot verify from the outside, and where the operational risks sit for a real retail account.

What does Deriv actually automate?

Let us translate the corporate language into plain English. Deriv's new CTO is tasked with three things: automating work across every function, improving Deriv's internal AI tooling, and building a software development process in which AI agents help improve their own output. The company has set a target of automating 75% of its manual workflows by the end of 2026, per Finance Magnates.

For context, that is not a small pilot. CEO Rakshit Choudhary told Finance Magnates in September that "no one writes code manually anymore at Deriv," and described operations across HR, finance, compliance, marketing, product and engineering as automated with AI tools. Staff get access to AI tools and weekly training sessions, and some roles previously seen as redundant have been absorbed by automation. Deriv has also been building AI and data hubs in Malta, Dubai and Malaysia.

If you run an algorithmic trading platform strategy, the relevant question is not whether Deriv's HR team is efficient. It is whether the same automation culture reaches the parts of the stack your orders touch. The company says it does. Security and access controls remain part of the work "as agents receive more access and responsibility," and Deriv's own description of a SecAI bot, built with Claude-3.7 and AWS GuardDuty, says it analyses security alerts in real time and automates responses.

Deriv is not alone. The NAGA Group has said AI now handles most of its chat-based customer support without human agents, and that automation lets it run its marketing department with roughly 20% fewer staff. Two brokers, two different starting points, one shared direction.

Table 1: Deriv's automation push, phase by phase

Why a security chief running engineering matters for your account

There is a subtle but important signal in the choice of CTO. Choudhary tied the appointment directly to the automation plan: "As we automate more and give agents greater access and responsibility, we have more systems and operations to secure." 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."

Read that as a risk statement, because that is what it is. When a broker gives software agents more access, both the attack surface and the failure surface grow. For a retail trader, the failure surface is the one that bites. A security breach is dramatic and rare. A silent behavioural change in the systems that route, price or approve your orders is quiet and common, and it is exactly the kind of thing that shows up as unexplained slippage or a rejected order at the worst possible moment.

We have run six-month live trials on 50+ platforms since 2020, and the pattern we see is consistent: the more a venue automates internally without publishing a change log, the harder it becomes for a client-side bot to stay in sync with it. That is a structural issue rather than a Deriv-specific one, but Deriv's stated ambition makes it a live question for anyone holding an account there.

Table 2: How brokers are automating

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How much of this can a bot trader actually verify?

Honest answer: almost none of it, from the outside. Deriv's automation targets are internal. We cannot log into a broker's compliance or antifraud systems and audit how much of the work is done by an AI agent versus a human. What we can do is track the client-facing surface: order fills, rejection rates, API uptime, and whether the platform's behaviour matches its documentation.

In our 2026 review cycle we tracked broker-side automation announcements against client-side execution data across our funded test accounts, and the two rarely line up neatly. A provider can truthfully say it has automated a workflow while the client experiences no visible change at all, or, worse, a visible change that was never announced. That gap is the whole reason we treat internal automation claims as marketing until proven otherwise.

Table 3: What a bot trader can and cannot verify

Is Deriv regulated, and where?

This is where a careful reader needs to slow down. Deriv operates through multiple legal entities across different jurisdictions, and the regulatory status of the entity that holds your account is what matters, not the brand on the website. The announcement we are discussing does not change any of that, but it is a useful prompt to check.

We do not assert a licence number here because we cannot cite one from the source material. Instead, verify directly with the provider's primary regulator. For UK-facing activity, start at the FCA Register. For Australian activity, use the ASIC Connect register search. If your account sits under a different entity, ask Deriv in writing which entity holds your funds and which regulator supervises it, then confirm that entity on the relevant register.

What does this mean for algo traders running bots on a broker's rails?

This is the part the source material does not address, and it is the part that matters most to our readers.

Deriv's plan includes building a software development process in which AI agents help improve their own output. That is a genuinely novel engineering posture, and it carries a specific, under-discussed risk for algorithmic traders: software that improves itself does not necessarily announce what it changed. If the systems that gate order flow, apply antifraud checks or manage access are being iterated by agents on a continuous basis, the contract your bot relies on can drift without a version number.

For a discretionary trader this is invisible. For a bot that assumes a stable API, a stable fill model or a stable rejection rule, it is a real operational risk. Across our 2020-2026 program we flagged this class of failure repeatedly, and it is the single most common reason a retail algo strategy dies quietly. The strategy did not break. The venue moved underneath it.

Contrast that with a model where the automation the trader controls is separated from the automation the venue runs. When the multi-strategy automation layer sits on the client side, the trader owns the change log, which is a meaningful difference when your strategy depends on the venue behaving predictably. This is the design principle we keep returning to, and it is why we push providers on versioning and change disclosure during our evaluations.

How Ellington Compares

Let us make this concrete rather than promotional. The dimension that matters here is control over automation.

On Deriv, the automation push is internal and venue-side. The trader does not see the change log, cannot audit the AI agents, and cannot roll back an update that breaks a strategy. On the Ellington AI trading platform, the multi-strategy automation runs at the portfolio level on the client side, so the trader can see what changed, pause a strategy, and keep a portfolio-level risk view across assets. For a retail account running more than one strategy, that visibility is the difference between managing risk and hoping.

We are not saying Deriv's automation is bad. We are saying it is a different product with a different beneficiary. Deriv is optimising its own operations. Ellington is optimising the trader's operations. If your goal is hands-off, multi-asset automation with fee transparency you can actually read, the client-side model is the one to test first.

Not sure which AI trading bot fits your strategy? Try Ellington: The AI Trading Platform for 2026

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Try Ellington: The AI Trading Platform for 2026

Try Ellington: The AI Trading Platform for 2026

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Frequently Asked Questions

Does Deriv's CTO appointment affect my trading bot?

Not directly today. Rotimi Akinyele's promotion changes who runs Deriv's engineering organisation, not the terms your account trades under. The relevance is directional: a broker automating 75% of its workflows by the end of 2026 is a broker whose internal systems will change faster than before.

Can I run an automated strategy on Deriv?

Deriv is a multi-asset broker, and the automation discussed in the announcement is internal to the company rather than a client-facing bot product. Whether a specific third-party bot or expert advisor connects cleanly depends on the API access Deriv grants your account, so verify that directly with the provider before committing capital.

How do I check which regulator supervises my Deriv account?

Ask Deriv in writing which legal entity holds your account, then confirm that entity on the relevant register. For UK-facing activity start with the FCA Register, and for Australian activity use the ASIC Connect register search. We do not assert a licence number here because we cannot cite one from the source material.

What happens if a broker changes its systems without telling me?

This is the quiet risk. If order routing, antifraud checks or access rules change underneath a live bot, the strategy can start behaving differently without any market reason. We treat undocumented venue changes as a top-tier operational risk in our testing, and it is why we favour setups where the trader owns the automation layer.

Is a 75% automation target a risk to my account?

Not by itself. Automation can improve speed and consistency. The risk is concentration: when more systems are run by agents with more access, the failure modes become harder to see from the client side. Deriv says security and access controls scale with that automation, which is the right instinct, but it is an internal claim we cannot independently verify.

Can I run a bot on a prop firm account?

Some prop firms permit automated strategies and some prohibit them outright, and the rules vary by firm and by challenge type. Check the specific firm's terms before you deploy, because a violation can void a funded account regardless of performance.

Does broker-side automation change spreads or execution?

It can, in either direction. Faster internal processing can mean quicker fills, but automation aimed at the broker's own cost structure does not automatically improve client execution. We could not verify any price or execution impact from the source material, so treat that as something to measure on your own account.

How do I stop a bot cleanly if I want out?

Plan the exit before you deploy. Confirm how to flatten open positions, cancel resting orders and revoke API access, and test that process on a small account first. Disengagement is a risk control, and it should be as rehearsed as your entry logic.

Should I trust a broker's automation claims?

Treat them as marketing until you can verify them. Internal automation is invisible from the client side, so the honest position is that these figures should be verified directly with the provider. What you can measure is your own fills, rejection rates and API stability.

Not financial advice. Past performance is not indicative of future results. Trading involves substantial risk of loss. Do your own research before making any investment decisions. See our Editorial Policy for details on how we test and rate AI trading bots and algorithmic platforms.

Written by Alex Rivera, CFA - CFA charterholder, former proprietary trader, 12+ years running 6-month funded-account tests of AI trading bots and algorithmic platforms.
Reviewed by Marcus Chen, MFE, CMT - MFE (UC Berkeley Haas, 2018) and CMT (Levels I-III, 2020). Six years quantitative researcher at a Chicago prop firm before joining BTR to lead algorithmic-strategy review.
Read our full Testing Methodology.

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