Founded by Alex Levkov, Ph.D. — Brown University economist and former Head of Model Risk Management.
AI-Native Econometrics Intelligence
I am a Ph.D. econometrician who has led model risk at the Federal Reserve and three global banks. When a number has to survive a regulator, a board, or cross-examination, I design it, estimate it, and defend it.
Services
01 Custom Research & Advisory
Ongoing research partnerships for organizations that need a senior econometrician on call, on a project or retainer basis. I conduct bespoke analyses across range of areas and industries. Click here for an example.
02 Litigation and Expert Testimony
Rigorous economic and statistical analysis for legal proceedings, regulatory disputes, and antitrust matters. Independent, defensible quantitative expertise and clear expert reports for any forum or jurisdiction. Click here of an example.
Apex Econometrics was built on a single conviction: the questions with the highest stakes deserve the most rigorous methods. I design and estimate the full range of causal econometric models — instrumental variables, difference-in-differences, regression discontinuity, and panel data methods — with the identification standards of peer-reviewed research. My work isolates true causal effects where others measure correlation. I integrate machine learning with classical econometrics, combining predictive power with causal interpretability. The result is analysis precise enough for the witness stand and clear enough for the C-suite.
03 Model Risk
Independent model risk assessment and validation services across all models. My work includes model review, benchmarking, back-testing, stress testing, performance evaluation, and governance support designed to strengthen transparency, reliability, and regulatory readiness. Click here for a sample validation report.
The Founder
Alex Levkov, Ph.D
FounderAlex Levkov holds a Ph.D. in Economics from Brown University. His research in the Journal of Finance and the Journal of Monetary Economics has been cited more than 4,500 times. He began his career as an economist and stress-testing model developer at the Federal Reserve Bank of Boston, then spent more than a decade leading quantitative and model-risk functions across the financial system: Head of Model Risk Management at Deutsche Bank, Head of Modeling for the Chief Investment Office at BNY, Head of Modeling for Treasury at U.S. Bancorp, and Head of Quantitative Analytics at The Clearing House. He works at the rare intersection of frontier academic research and senior industry practice, and every engagement is delivered by him directly.
Your Questions, Answered
Will your analysis hold up to scrutiny?
Every conclusion is built on identified causal methods and documented assumptions, designed from the outset to withstand opposing experts, regulators, and the court.
Do you specialize in certain industries?
Apex Econometrics serves a broad range of clients: corporations, law firms, government agencies, financial institutions, and private equity firms across broad set of industries including antitrust and regulation, healthcare, energy, technology, labor and employment, and real estate, among others. Engagements are available on a project basis or through ongoing advisory retainers.
How Apex Econometrics differs from its competitors?
Apex Econometrics applies rigorous causal inference methods, including instrumental variables, difference-in-differences, regression discontinuity design, and structural econometric modeling, to isolate true cause-and-effect relationships. This distinction is critical when findings must withstand legal, regulatory, or board-level scrutiny. These methods are not theoretical for us. Apex's founder developed and validated exactly these models inside the Federal Reserve and at three global banks, and his published research applying them has been cited over 4,500 times. You can find an overview of various econometric techniques in my toolkit here.
Let's Work Together
Schedule a confidential consultation. We will discuss your question, whether I am the right expert for it, and how I would approach the analysis.
