At BestX we are continuing to research methods for enhancing measurement of expected costs within the OTC markets. A parametric based model provides a good approximation, but runs the risk of becoming increasingly complex to try to model all edge cases, especially for less liquid currency pairs, or times of day or larger sizes. We have been conducting research in parallel to develop a new framework, which is purely data driven using machine learning methods. More work needs to be done but this paper provides results for this framework when applied to the measurement of the forward component of FX transaction costs, a notoriously difficult part of the market to model given the voice driven, OTC nature of this part of the market. For a copy of the paper please email us at email@example.com.