Are we in the era of actuarial data science modelling?
A huge increase in data generation, data capture and data storage combined with significantly increased computing power is providing insurers with a unique opportunity to re-evaluate the value that their data can provide; and the technologies available to do that.
Enabling actuaries to embrace modern day data science tools and to work closely with data scientists is an important link that could give strategic advantages to insurers in the further development of actuarial modelling software.
The current economic & pandemic situation is causing insurers to assess the impact quicker and to use modern day tools available to respond and adapt.
Looking forward, the actuary will continue to evaluate key sources of data and need to find ways to incorporate data science that uses state of the art machine- learning and data technologies together with the actuary’s business insights. We need to refresh our methods and make use of emerging technological advances.
Some are turning to programming languages like Julia, Python and R; among other. With the rise of open-source execution environments computational notebooks, programming is becoming more accessible and easy to use.
This provides an interesting alternative for actuaries to execute large amounts of statistical calculations and see the results with the latest data visualisation techniques.
Join us for an exploration session on the use of data science in insurance companies today.
During this presentation we will be exploring among other:
Methods used in non-life pricing are evolving at a fast pace and more advanced actuarial and statistical techniques are being used in pricing, competition analysis and profitability analysis.
How can life insurers address low persistency? How can data and analytics help? Join our webinar on Friday 12 March 12pm as we discuss how the full cycle of actuarial analysis is evolving
A huge increase in data generation, data capture and data storage combined with significantly increased computing power is providing insurers with a unique opportunity to re-evaluate the value that their data can provide.
Improvements in computational power has given rise to the use of data science and artificial intelligence techniques in a wide variety of areas, including finance, driverless cars, image detection, speech recognition etc. This is directly impacting business practices within the financial services through its application within banking, insurance and asset management.
In the current economic climate, insurers need to improve their processes continually – making them more efficient and cost-effective while maintaining the agility to deal with new requirements. At the same time, technological change is providing new ways of achieving these objectives. In particular, the term ‘robotics’ appears to be used everywhere, and it is important to grasp the impact and potential use of these new technologies.
Listen to Valerie du Preez, founder and Managing Director of Actuartech, on the panel for Legerity's IFRS 17 webinar discussing, "Can IFRS17 help deliver digital transformation?".
In a world of high volume and varied datasets, data science techniques can add valuable tools to an actuary’s toolkit to provide actionable insights from data.
Sophisticated machine learning models have the potential for high predictive accuracy but their complexity may sometimes result in black box models, which, in some cases, may appear to be a trade-off between accuracy and interpretability.
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