Steven Hooghwerff
AAG
Consulting Actuary
1101 BE, NL
Steven Hooghwerff is a consulting actuary in the Amsterdam office of Milliman. He joined Milliman in 2015.
Experience
Steven has over 15 years of experience specializing in life insurance, risk management, and also advising P&C insurers. His main focus is advising insurers and other financial institutions on developing and using actuarial and risk models in strategic decision-making.
Professional Designations
- Fellow, Royal Dutch Actuarial Association (AAG)
Education
- Actuarial Practice Cycle (postgraduate education), Amsterdam Business School, University of Amsterdam, The Netherlands
- Master of Science, Quantitative Finance and Actuarial Sciences, Tilburg University, The Netherlands
- Master of Science, Econometrics and Operations Research, Erasmus University Rotterdam, The Netherlands
- Master of Laws, Financial Law, Erasmus University Rotterdam, The Netherlands
Affiliations
- Member of the examination committee at the Dutch Actuarial Institute
- Teacher of several courses at the Dutch Actuarial Institute
- Supervisor of students at the Actuarial Practice Cycle (final year before qualification) of the University of Amsterdam
Publications
Read their latest work
Article
Market insight from year-end 2021 SFCRs: Analysis of life insurers based in the Netherlands
30 December 2022 - by Lotte van Delft, Steven Hooghwerff, Bjorn Blom
This briefing note looks at the year-end 2021 Solvency and Financial Condition Reports for a sample of life insurers based in the Netherlands.
Article
Market insight from year-end 2020 SFCRs: Analysis of life insurers based in the Netherlands
01 December 2021 - by Lotte van Delft, Floris Brull, Steven Hooghwerff
We analyse the SFCRs required by Solvency II of seven Dutch life insurance entities and include key information.
Article
Judging the appropriateness of the Standard Formula under Solvency II
21 June 2017 - by Sinéad Clarke, Steven Hooghwerff, Roel van der Kamp
This article provides a short overview of the structure of the Standard Formula, presents a suggested framework and worked examples, and discusses challenges and pitfalls to be considered.