  Machine learning models are increasingly used in a wide variety of financial
settings. The difficulty of understanding the inner workings of these systems,
combined with their wide applicability, has the potential to lead to
significant new risks for users; these risks need to be understood and
quantified. In this sub-chapter, we will focus on a well studied application of
machine learning techniques, to pricing and hedging of financial options. Our
aim will be to highlight the various sources of risk that the introduction of
machine learning emphasises or de-emphasises, and the possible risk mitigation
and management strategies that are available.
