However, a common concern among finance professionals, who usually make money by having access to privileged knowledge and special relationships, is how is it possible to do business when information asymmetries are close to zero — in shared distributed ledgers and blockchains, data is either public or available given proper authentication. By using examples from actual economic activity (in international trade and digital commerce) we can illustrate how the intuition of a trust imbalance may serve as starting point in the analysis. We define the concept of "trust asymmetry" in terms of dissimilarities in metric entropy (e.g. Kolmogorov Entropy) or as in this case, using symbolic regression complexity -- which can be described in terms of the shape of a data space, and, the dynamics of vector fields.