Between 1940 and 1950, we started to invent Artificial Intelligence (AI) and the myth of the human robot.
Today, most actuarial work (from underwriting to reserving and capital adequacy) uses statistical learning methods related to data science and Machine Learning.
The challenge for the actuary - data scientist is to simultaneously use his or her business knowledge and expertise in data science to develop innovative approaches with traditional models augmented by machine learning models.
In this document, we want to establish a brief overview of the new practices linked to the growing use of data science in the insurance sector.
First of all, we provide a brief historical overview of certain terms that have become "buzzwords": Big Data, Artificial Intelligence, Machine Learning, Deep Learning and Statistical Learning.
We will then explain why and how to apply these methods to the insurance world in order to propose innovative solutions.
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