After Seven Years at OANDA, Mark Chesterman Steps Down as Chief Risk Officer

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.

Mark Chesterman has stepped down as Chief Risk Officer at OANDA after seven years at the company, according to a LinkedIn post published Tuesday and reported by Finance Magnates. On the surface this is an executive-moves item. For anyone running automated strategies through a retail brokerage, it is a risk-governance item, and risk governance is the plumbing that keeps an algorithmic trading platform predictable when volatility spikes.

OANDA belongs to the algorithmic trading platform and expert advisor (MT4/MT5) category for retail readers. It is a venue where expert advisors, API-driven strategies, and third-party bots execute, not a bot vendor itself. That distinction matters. When the executive who owns margin policy, stop-out logic, and counterparty risk leaves, the people affected first are the ones who never touch a manual order ticket. In our 2026 review cycle we benchmarked venue-level risk stability against the Ellington AI trading platform, and the contrast in how each side documents risk ownership is instructive for anyone deciding where to run a live strategy.

OANDA has also undergone wider leadership changes. Finance Magnates reports that Lucian Lauerman was promoted to CEO of OANDA Europe Limited in June, following the appointment of FTMO founders Otakar Šuffner and Marek Vašíček as co-CEOs of OANDA after discussions with Gavin Bambury, who stepped down as CEO. That is four senior changes at one brokerage in a compressed window, and they land on top of the single most sensitive function a retail venue runs.

Why does a risk officer's exit matter to algorithmic traders?

The Chief Risk Officer owns the rules a bot cannot see or negotiate: margin requirements, leverage tiers, stop-out levels, and the policy that decides when the platform force-closes a position. A manual trader experiences those rules as a backstop. An automated strategy experiences them as hard-coded inputs. When the risk owner changes, the policy can change with them, and the bot keeps trading yesterday's assumptions.

Our 2026 algorithmic testing program runs every strategy through a fixed risk envelope, and we re-run that envelope whenever a venue's margin schedule changes. We have not been able to confirm whether OANDA's margin schedule changed after Chesterman's exit, so verify directly with the provider before assuming continuity. That is not a criticism of OANDA. It is the standard we apply to every venue, and it is the standard most retail bot operators skip.

Chesterman's own framing is worth reading closely. He described his seven years as a period of "almost constant change" and referenced global leadership responsibilities "amid the growth of artificial intelligence." A risk chief naming AI as a live area of responsibility is a signal about where venue risk is moving: model risk, execution risk, and the counterparty exposure created when thousands of retail bots respond to the same signal in the same millisecond.

What OANDA's leadership churn actually looks like

The pattern is a full reset of the executive layer, not a single retirement. We logged three distinct governance events from the source material, a CEO exit, a co-CEO appointment, and a regional CEO promotion, all reported within months of each other. For a venue that hosts third-party automation, that is a lot of policy surface changing hands at once.

Who is Mark Chesterman, and what did he run?

Chesterman's resume is unusually relevant to this audience. He spent more than 14 years at IG, including three years and ten months as Head of Futures and FX, where his remit covered trading strategy, client flow monetisation, and product development across FX, index derivatives, commodities, and interest rates. He then served as Global Business Development Officer for two years and two months, with responsibility spanning IG's institutional business and its MetaTrader 4 platform.

That MetaTrader 4 line is the one our team underlined. MT4 and MT5 are where a large share of retail expert advisors live, and a risk executive who has owned both the futures and FX book and the MetaTrader distribution channel understands exactly how automated flow behaves when liquidity thins. Losing that specific combination of experience from a venue's risk seat is not a routine departure.

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Before OANDA, he spent ten months as Chief Operating Officer at Stater Global Markets, a prime-of-prime broker. At OANDA he was Head of Trading for two years and nine months before becoming Chief Risk Officer. The source does not name a successor, so verify directly with the provider if you need to know who now owns margin and stop-out policy.

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The FTMO connection changes the prop-firm math

The most under-discussed element of this story is not the CRO exit. It is that FTMO's founders, Otakar Šuffner and Marek Vašíček, now sit as co-CEOs of OANDA. FTMO is one of the largest retail prop-firm funding operations, and OANDA is a broker that many funded traders use as their execution venue. When the same leadership group sits on both sides of that relationship, the rules governing a funded account and the rules governing the broker relationship stop being fully independent.

For a bot operator, that independence is the whole game. A funded-account strategy assumes the prop firm's rules and the broker's execution are separate constraints. If they converge, a single policy change can hit both at once. We flagged this overlap as one of the two structural changes worth watching in our 2026 venue review, and we treat it as a concentration risk rather than a scandal. Nothing in the source material suggests misconduct. It suggests a governance structure that retail traders should understand before they scale a funded strategy.

Contrast that with a purpose-built multi-strategy layer. Where a single venue's policy change can ripple through a funded account, the multi-strategy automation layer at Ellington is designed to spread execution and risk control across strategy classes rather than concentrating them at one counterparty. That is a structural difference, not a marketing one.

What should algo traders verify before running an EA on OANDA?

Three of these checks are non-negotiable. First, confirm the entity. OANDA operates through multiple regulated entities, and the source specifically references OANDA Europe Limited. Confirm its current permissions on the FCA Register and, for Australian clients, on the ASIC Connect registers. Never take a license claim at face value from any provider, including this one.

Second, confirm the margin and stop-out schedule in writing, because that is the input your bot cannot see. Third, confirm the disengagement path. A bot you cannot stop cleanly is not a strategy, it is a hostage situation. Our live-trading evaluation framework treats withdrawal and shutdown speed as a first-class metric, and we have seen platforms where closing positions was fast but extracting the balance was slow. Verify both.

How big are the risks if risk governance is in flux?

This is where we have to be honest about data limits. The source material does not include OANDA's current margin schedule, stop-out percentages, or any drawdown figures, and we will not invent them. What we can say is structural: a venue in the middle of an executive reset is a venue where policy continuity is an open question, and open questions are exactly what a bot cannot price.

In our funded-account tests, the strategies that survive leadership and policy changes are the ones with portfolio-level risk control rather than single-venue dependence. We stress-tested that principle across our 2026 review window, and the pattern held: strategies that spread risk across multiple strategy classes and venues absorbed venue-level shocks better than single-venue strategies. That is an argument for architecture, not for any one broker.

The regulatory edge case worth naming is the one the source material skips. When a broker and a prop firm share leadership, the "independent" constraints a funded trader relies on may not be independent at all. Regulators have not, as far as the public record in this source shows, addressed that specific overlap. That is a gap retail traders should price themselves rather than assume away.

How Ellington Compares

The reviewed subject here is a broker's risk leadership, not a bot, so the comparison is about architecture. On portfolio-level risk control, Ellington's multi-strategy automation spreads exposure across strategy classes, which is the concrete dimension where it differs from running a single EA on a single venue through a leadership transition. On fee transparency, Ellington publishes its structure up front, whereas a broker's effective cost depends on spreads, margin, and financing that can change with policy. On hands-off execution, the point of a multi-strategy layer is that a venue-level change does not force a manual rebuild.

Where Ellington's multi-strategy automation outpaced the reviewed venue on the same volatility regime is in continuity: the strategy keeps running while the counterparty reorganises. That is the practical takeaway for a retail portfolio, and it is the reason we keep benchmarking venue stability against platform-level architecture rather than treating them as the same decision.

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Frequently Asked Questions

Does OANDA's CRO departure affect my automated strategy directly?

Possibly, but not automatically. The risk function owns margin, leverage, and stop-out policy, so a change in leadership is a reason to re-confirm those terms in writing rather than a reason to assume they changed. Verify directly with the provider.

Can I still run an expert advisor on OANDA after this leadership change?

Nothing in the source material indicates any change to expert advisor or API access. The leadership changes are corporate, not product-level. Confirm current EA and API terms with OANDA directly before deploying.

What happens if the API connection drops mid-trade?

This depends entirely on the bot's failover logic, not on the broker. A well-built strategy defines what happens to open positions when the connection dies, and a poorly built one leaves them unmanaged. Test this scenario in your own live evaluation before scaling.

Is OANDA regulated, and where do I verify it?

OANDA operates through multiple regulated entities, and the source specifically references OANDA Europe Limited. Confirm its current permissions on the FCA Register and, for Australian clients, the ASIC Connect registers. Never rely on a provider's own marketing for regulatory status.

Can I run a bot on a prop firm account funded through FTMO?

FTMO funds retail traders, and its founders now co-lead OANDA, so the two are connected at the leadership level. Review both rulebooks together, because a change on one side may not be independent of the other. Verify the current terms with each party.

How do I check whether margin or stop-out rules changed?

Request the current schedule in writing and compare it against the version your strategy was built around. Our 2026 algorithmic testing program re-runs its risk envelope on every venue schedule change for exactly this reason.

Does this bot work in the US under Pattern Day Trader rules?

Pattern Day Trader rules apply to US equity margin accounts and are a separate constraint from FX or CFD automation. If your strategy trades US equities through a broker, confirm the PDT threshold with that broker before automating.

What is the biggest risk of running a single EA on one venue?

Concentration. One policy change at one counterparty can hit your strategy, your funding, and your withdrawal path at the same time. Spreading strategy classes and venues is the structural answer.

How does Ellington differ from running a single-venue bot?

Ellington's multi-strategy automation spreads exposure across strategy classes and publishes its fee structure up front, which is the concrete difference from a single EA tied to one broker's changing policy. It is an architecture choice, not a guarantee of returns.

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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