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AI and ethics in insurance: a new solution to mitigate proxy discrimination in risk modeling
The development of Machine Learning is experiencing growing interest from the general public, and in recent years there have been numerous press articles questioning its objectivity: racism, sexism, \dots Driven by the growing attention of regulators on the ethical use of data in insurance, the actuarial community must rethink pricing and risk selection practices for fairer insurance.
Applying Machine Learning to Life Insurance: some knowledge sharing to master it
Focusing on the modification of the life insurance industry over time highlights the stake of using Machine Learning for insurers and benefits that it can bring by unleashing data value.
Model Transparency and Interpretability : Survey and Application to the Insurance Industry
The use of models, even if efficient, must be accompanied by an understanding at all levels of the process that transforms data (upstream and downstream).
A survey on natural language processing (nlp) and applications in insurance
It brings today, many opportunities for the insurance industry. Understanding those methods and, above all, knowing how to apply them is a major challenge and key to unleash the value of text data that have been stored for many years.
Interpretabilité des modèles : état des lieux des méthodes et application à l'assurance
Models users must ensure that models do not discriminate against and that it is also possible to explain its result.
