The equal risk pricing methodology for financial derivatives pricing is introduced. The associated deep reinforcement learning implementation is discussed. Numerical experiments results are presented, along with an analysis of the choice of the objective function and of the hedging instruments. The approach is also benchmarked against traditional pricing methods. Bio: Frédéric Godin is an Associate Professor at Concordia University (Montreal, Canada) in the Department of Mathematics and Statistics. His areas of research are financial engineering, risk management, machine learning, actuarial science and energy markets. He also holds the Fellow of the Society of Actuaries (FSA) and Fellow of the Canadian Institute of Actuaries (FCIA) designations.