While early methods required a training dictionary to find the initial alignment (Mikolov et al., 2013) , fully unsupervised methods have managed to obtain comparable results based on either adversarial training or selflearning<cite> (Artetxe et al., 2018b)</cite> . A prominent application of these methods is Bilingual Lexicon Induction (BLI), that is, using the resulting cross-lingual embeddings to build a bilingual dictionary. In this paper, we go one step further and, rather than directly inducing the bilingual dictionary from the cross-lingual word embeddings, we use them to build an unsupervised machine translation system, and extract a bilingual dictionary from a synthetic parallel corpus generated with it.