Jan Thiemen Postema
MSC
Consultant
1101 BE, NL
Jan Thiemen Postema works as a consultant in the Amsterdam office of Milliman.
Experience
Jan Thiemen joined Milliman in 2020, and has five years of experience working in the realm of data science. Before joining Milliman, he worked in a similar role at Ortec Finance. At Milliman, he focusses mainly on the application of data science and machine learning techniques in the insurance sector, as well as data engineering and visualization projects.
Education
- Master of Science in Computer Science, specialization Data Science, University of Twente, the Netherlands
- Bachelor of Science in Business & IT, University of Twente, the Netherlands
Publications
Read their latest work
Article
Flood risk modelling in Europe
02 May 2024 - by Jan Thiemen Postema, Daniël van Dam, Menno van Wijk, Niels Van der Laan, Antoine Rainaud, Eve Titon
We present a framework and tools for projecting insured flood losses in the Netherlands and France, which can be used for insurance portfolios across Europe.
Article
Impact of COVID-19 on best estimate mortality assumptions
08 September 2023 - by Flora Auter, Amal Elfassihi, Salima el Khababi, Jan Thiemen Postema, Eve Titon, Raymond van Es
Using mortality data adjustment methods for COVID-19 helps avoid double counting and derives long-term trends without instabilities from a one-off experience.
Article
FICO® Score 10 and FICO® Score 10 T model assessment
25 July 2023 - by Kenneth A. Bjurstrom, Raymond van Es, Ryan Huff, Jan Thiemen Postema
FICO 10 and FICO 10 T mark a meaningful advancement in assessing credit in mortgage lending, powered by trended data and cutting-edge analytical techniques.
Article
Anomaly detection techniques in fraud detection, performance optimization, and data quality
08 March 2023 - by Bjorn Blom, Jan Thiemen Postema, Rens IJsendijk, Judith Houtepen, Job Prince
Methods to detect anomalies can be used to find fraudulent claims in insurance, especially in products with a large frequency of payments, such as in healthcare.
Article
Explainable AI in fraud detection
22 December 2022 - by Inès Zitouni, Jan Thiemen Postema, Raymond van Es
Techniques in explainable artificial intelligence can indicate the reasons why a model expects a claim to be truly fraudulent, saving time for investigators.
Article
Improved mortality rate forecasting using machine learning and open data
23 November 2022 - by Jan Thiemen Postema, Raymond van Es
Compared with traditional techniques, state-of-the-art machine learning algorithms can substantially improve the forecasts of mortality rates.
Article
Developing fair models in an imperfect world: How to deal with bias in AI
23 December 2021 - by Daniël van Dam, Raymond van Es, Jan Thiemen Postema
We need to start training models that reflect the world we want to live in.
Article
Explainable AI in practice: Build trust and encourage adoption
02 March 2021 - by Jan Thiemen Postema, Raymond van Es
Explainable AI in practice: Build trust and encourage adoption.