Founder & principal
Quantitative finance. Independent model judgment. Applied AI.
Adam’s experience spans trading analytics, derivatives, mortgage and receivables investing, the development of financial models, and independent challenge as a bank’s Chief Model Risk Officer.
Today, his work extends into generative and agentic AI: building workflows, developing practical instruction and applying the discipline of financial analysis and model risk to new systems.
AgentX Experts brings these disciplines together for expert witness consulting, model development and independent validation.
North America Rates and Credit Bookrunner at Deutsche Bank, covering trade capture, risk and P&L for rates and credit products. Equity Derivatives Analyst at RBC, with valuation work across equity, commodity and FX structured products. Earlier equities and ETF experience on the New York Stock Exchange.
Pricing, structuring and loan-performance modeling for a lending and securitization business at Colony American Finance, subsequently CoreVest. Mortgage and MBS analytics, and mortgage-servicing-rights valuation and modeling work.
Director of Analytics at Ophrys, with portfolio valuation, pricing and acquisition analysis. Experience across consumer credit, residential whole loans, litigation-related and bankruptcy receivables, and secured and unsecured loans.
Head of Model Risk and Chief Model Risk Officer at Investors Bank. Model review across treasury, liquidity, interest-rate risk, credit, capital planning, provisioning, stress testing, portfolio valuation, customer risk, fraud and financial crime.
Experience at McKinsey Risk Dynamics, Deloitte and Alvarez & Marsal. Work includes bank model validation, wholesale-loan machine learning, macroeconomic scenario validation, and financial-planning and collateral models.
Generative and agentic AI advisory, practical workflow development and hands-on curriculum. Previously taught a Columbia University FinTech Bootcamp covering Python financial analytics, portfolio theory, Monte Carlo simulation, machine learning, forecasting and algorithmic trading.
Formal quantitative training, professional designations and applied technical study.
Quantitative Finance, with study in valuation, derivatives, fixed income, portfolio management and investment strategies.
Chartered Financial Analyst and Financial Risk Manager designations.
Specialty certification in machine learning, alongside continuing study and application of statistical learning, deep learning and data science.
Development of practical materials on tool-using agents, evidence-based verification, memory, orchestration and human review.
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