1. A method of training a fraud detection system to distinguish between legitimate users and fraudulent users, the method comprising: receiving a set of mouse movement datasets, each mouse movement dataset of the set of mouse movement datasets including mouse movement data generated by either a legitimate user or a fraudulent user; collecting the set of mouse movement datasets within a database stored on a storage device of the fraud detection system; performing a teaching operation on a risk engine of the fraud detection system using the database to train the risk engine to differentiate between mouse movement data generated by the legitimate user and mouse movement data generated by the fraudulent user; wherein performing the teaching operation on the risk engine of the fraud detection system includes: assigning a particular distance metric of a set of distance metrics to the set of mouse movement datasets, each distance metric of the set of distance metrics defining a distance between a pair of mouse movement datasets; generating distances between pairs of mouse movement datasets of the set of mouse movement datasets as defined by the particular distance metric; wherein each mouse movement dataset of the set of mouse movement datasets includes an owner parameter having a binary value, wherein the mouse movement datasets having mouse movement data generated by the legitimate user form a set of legitimate datasets, each legitimate dataset of the set of legitimate datasets having a first binary value, wherein the mouse movement datasets having mouse movement data generated by the fraudulent user form a set of fraudulent datasets, each fraudulent dataset of the set of fraudulent datasets having a second binary value, and wherein performing the teaching operation on the risk engine of the fraud detection system further includes: for each mouse movement dataset of the set of mouse movement datasets: generating an average distance from the mouse movement dataset to legitimate datasets of the set of legitimate datasets; and forming, as a training pair of a set of training pairs, the average distance and the binary value.