This module aims to introduce recent developments in the field of statistical learning, applied to the insurance and financial sectors. Statistical methods are used in the insurance industry to assess the risk profile of an insured. This profile presents two sides: one is the frequency of claims and the other is the size of the claim caused by the insured. Both aspects are studied carefully by insurers so as to propose the best price for an insurance coverage. In the financial industry, advanced statistical methods are needed to evaluate the credit risk of a lender. This module present the common tools to study these risks: generalized linear models, additive models, Regression/classification trees. Some new aspects will also be developed among them we quote shrinkage methods (Lasso, Ridge), random forests and gradient boosting methods.