Douglas Elliott

Partner, Oliver Wyman

Mr. Elliott is a Partner at Oliver Wyman. He focuses on public policy and its implications for the financial sector, globally. In recent years, he has devoted considerable time to analyzing, writing, and speaking about digital assets, particularly the public policy issues surrounding them. He is the author of “Central Bank Digital Currencies: 7 Policy Mistakes to Avoid”.

He frequently appears on panels or as a speaker for the Bank of England, Fed, IMF, World Bank, ECB, ESRB, European Commission, Basel Committee, JFSA, Asian Development Bank, US Treasury, OCC, and others. In 2020, he co-authored a report for the Group of Thirty on corporate solvency problems stemming from the pandemic. The project co-chairs were Mario Draghi and Raghuram Rajan, former heads of the ECB and the Indian central bank.

Prior to Oliver Wyman, he was a scholar at The Brookings Institution for seven years, where he wrote and spoke extensively on financial regulation. He has twice been a Visiting Scholar at the International Monetary Fund, as well as a consultant for the IMF, the World Bank, and the Asian Development Bank. While at Brookings, he wrote Uncle Sam in Pinstripes: Evaluating US Federal Credit Programs, a comprehensive book on the topic.

Prior to Brookings, he was a financial institutions investment banker for two decades, principally at J.P. Morgan. He worked across the range of financial institutions clients, including banks, insurers, and asset managers. He was primarily an M&A investment banker, but also worked as an equities analyst and in capital markets.

He has testified multiple times before both houses of Congress and participated in numerous speaking engagements, as well as appearing widely in the major media outlets. The New York Times has described his analyses as “refreshingly understandable” and “without a hint of dogma or advocacy”.

Mr. Elliott graduated from Harvard College magna cum laude with an A.B. in Sociology in 1981. In 1984, he graduated from Duke University with an M.A. in Computer Science.