Featured articles of the month
Time series analysis of GSS bonds
Research article published exploring a range of neural network architectures (DNN, CNN, LSTM, GRU) and XGBoost to predict S&P Green Bond Index values.
Originally published by the British Actuarial Journal in March 2023 . © The British Actuarial Journal.
Other recent articles
All together now: modelling claims using federated learning
Read more as Małgorzata, Dylan and Claudio discuss federated learning and how to model claims anonymously using this new technique.
Originally published by The Actuary, September 2021. © The Institute and Faculty of Actuaries.
Supervised learning techniques in claims frequency modelling
Read on as Neptune Jin shares the Data Science Research Section’s work looking at the merits of different supervised learning techniques for claim frequency modelling.
Originally published by The Actuary, July 2021. © The Institute and Faculty of Actuaries.
Insurance: Collaboration without compromise
Learn more as Małgorzata Śmietanka introduces the opportunities for federated learning and privacy-preserving data access in insurance.
Originally published by The Actuary, March 2021. © The Institute and Faculty of Actuaries.
All clear: How Shapley values make opaque models more transparent
Karol Gawlowksi, Christian Richard and Dylan Liew show how Shapley values can be used to make opaque models more transparent.Originally published by The Actuary, March 2022. © The Institute and Faculty of Actuaries.
Classification of climate-related insurance claims using gradient boosting
Research article published showing the use of gradient boosting techniques, using open source LightGBM package, to classify climate-related insurance claims.
Originally published by the Instituto de Actuarios Espanioles, December 2022. © Instituto de Actuarios Espanioles.
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