Datapoints

We use several dozen data points, including financial (e.g. EBITDA) and non-financial (e.g. Web presence growth); also, data models that are either numeric or semantic in nature. This last point is relevant because when mapping the competitive space of companies, the description of services provided is usually a key aspect in the definition of an entity.  The similarity score uses semantics to find companies that are similar, and it is the central metric to compare within non-bank institutions types, and across adjacent types.

Risk profile

Companies that have a history of having completed previous rounds of due diligence are inherently less risky. From the data set we learn the distinct levels of risk for each entity, these are presented to the user by utilizing a common colored-flag metaphor.