Contact Us


Michael Rees

Director and Founder of Financial Modelling in Practice Limited

Biography

Dr. Michael Rees is an independent expert in quantitative decision-support and risk modelling. He provides quantitative decision-support to senior executives who are facing major decisions on strategy, financing, business structure, transactions, valuation and portfolio optimisation. He also leads training courses in financial modelling, risk modelling and related topics for client staff of all levels, and is Europe’s most experienced trainer and consultant in @RISK® and other Palisade products, having – since 2003 – trained or consulted with over 2000 people in the use of simulation and related tools to support decision-making through risk modelling and optimisation.

Michael has over 20 years business and finance experience, including 10 years as an independent consultant. As a Principal at Mercer Management Consulting (now Oliver Wyman) until 2000 he led major projects in the area of strategy, organization and change (such as market and competitive analysis, partner and acquisition assessments, performance measurement and improvement, cost reduction, outsourcing, process redesign, restructuring and change management). He later worked as a Vice-President at J.P. Morgan, where he was involved in the development of financial forecasts, conducting valuations, publishing reports and advising fund managers and hedge funds. He was ranked as a top City analyst by all the companies under his direct coverage and received a vote in the Institutional Investor 2002 survey.

Much of his work is focussed in the oil and gas, energy, resources and engineering sectors, but he is also frequently asked to assist clients in private equity, finance, insurance, as well as health care and other industries.

Michael has a Doctorate in Mathematical Modelling and Numerical Algorithms, and a B.A. with First Class Honours in Mathematics, both from Oxford University in the UK. He also has an MBA with Distinction from INSEAD in France. He has studied for the Certificate of Quantitative Finance, graduating top of the course for on-going class work and also receiving the Wilmott Award for the highest final exam mark.



Achievement

- Over 20 years business and finance experience across oil and gas, energy, resources, engineering and other sectors
- Previously a Vice-President at J.P. Morgan, Principal at Mercer Management Consulting (now Oliver Wyman) and European Director of Training and Consulting for Palisade Corporation
- Europe’s most experienced trainer and consultant in @RISK® and other Palisade products, having trained or consulted over 2000 people in the use of simulation and related tools to support decision-making through risk modelling and optimisation.
- Delivered training courses and consulted for many oil and gas companies in Europe, North America and Asia, in financial modelling, risk modelling and related topics.

- Past clients include Shell, Statoil, BG, Cairn, Dong, Dana, Addax, Talisman, Oxy, Petrofac, Tullow and others.
- Author of “ Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level ”

Summary of his professional achievement:

- Michael has a Doctorate in Mathematical Modelling and Numerical Algorithms, and a B.A. with First Class Honours in Mathematics, both from Oxford University in the UK.

- He also has an MBA with Distinction from INSEAD in France.

- He has studied for the Certificate of Quantitative Finance, graduating top of the course for on-going class work and also receiving the Wilmott Award for the highest final exam mark.

Michael’s Latest Publication

He is the author of “Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level ” (John Wiley & Sons, 2008), which is a practical, comprehensive and in-depth guide designed to cover Excel modelling, financial statement modelling, valuation, risk analysis, real options, and VBA coding for practical applications in business, economic analysis and finance that are relevant to facilitate the construction of robust and readily understandable models.