Senior Associate Dr. Anil Donmez is an economist specializing in digital assets, market manipulation, white-collar investigations, and complex financial instruments. With expertise in financial economics, forensic analysis of financial and transactional data, and damages assessment, Dr. Donmez assists clients and their counsel in navigating complex disputes and enforcement matters.

In this Q&A, Dr. Donmez discusses his approach to challenging economic questions, his philosophy on leading and mentoring project teams, and his insights into emerging trends shaping financial markets and economic analysis.

What analytical issues tend to be most consequential in your matters, and how do you approach them?

The most consequential issue is often the counterfactual: What would reasonably have happened under different conduct or market conditions? An analysis can be technically sophisticated and still be unhelpful if that starting point is poorly defined. I begin by identifying the economic question the evidence must answer, then examining which comparisons and data can inform it.

I also test whether the conclusion holds across reasonable assumptions. If a modest change in the benchmark or time period produces a very different result, that is something we need to understand and explain. My goal is to develop opinions grounded in the evidence and supported by analyses and assumptions that I can explain clearly and defend under scrutiny.

What risks or questions do clients sometimes underestimate early in an engagement, and how do you help bring them into focus?

One question that deserves attention early is how well a proposed conclusion will hold up as the evidence develops and its assumptions are tested. In a damages analysis, for example, there can be a natural inclination to focus on the highest supportable estimate, but that estimate is not always the most useful if it depends on assumptions that are difficult to defend or changes substantially under reasonable alternatives. I try to bring those issues into focus early by asking what the evidence supports, what data we still need, and how sensitive the result is to our analytical choices. This approach helps clients understand both the potential value of an analysis and the strength of the foundation beneath it.

What is your approach to leading and mentoring project teams to produce rigorous, high-impact results for clients?

I want team members to understand the question behind an assignment, not just the steps needed to complete it. When people see how their work fits into the broader economic argument, they are better positioned to spot problems, suggest improvements, and take ownership of the result. I try to set a clear analytical direction while making room for colleagues to challenge assumptions and bring their own ideas forward. Rigorous review is part of that process, but so is explaining why a change matters. The best outcome is a stronger piece of work and a team that has grown through producing it.

What emerging trends are you seeing that are reshaping how clients think about this type of analysis?

Financial activity is taking new forms, from tokenized assets to contracts tied to real-world events. These developments are changing how transactions are structured, how markets operate, and what information is available for economic analysis.

They also raise familiar questions in new settings: How should a product be valued? What incentives does its design create? How does a market function in practice, and what would have happened under different conditions? Clients increasingly need analyses that combine an understanding of these emerging markets with established principles of financial economics. I find that intersection of financial theory, data analysis, and evolving market structure particularly compelling.

What initially drew you to economic consulting, and what continues to motivate you today?

What first appealed to me about economic consulting was the opportunity to combine economic and financial theory with advanced data analysis to answer real-world questions. Data can reveal patterns that are difficult to see at first glance, but finding a pattern is only the beginning.

The more interesting challenge is understanding what produced it, whether it holds up to careful testing, and what conclusions the evidence can support. I enjoy applying that approach in different settings, from established financial markets to newer products and technologies. What continues to motivate me is that each matter requires both analytical discipline and curiosity: the tools may carry over, but the questions are rarely quite the same.

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