Corporate failure resonates widely leaving practitioners searching for
understanding of default risk. Managers seek to steer away from trouble, credit
providers to avoid risky loans and investors to mitigate losses. Applying
Topological Data Analysis tools this paper explores whether failing firms from
the United States organise neatly along the five predictors of default proposed
by the Z-score models. Firms are represented as a point cloud in a five
dimensional space, one axis for each predictor. Visualising that cloud using
Ball Mapper reveals failing firms are not often neighbours. As new modelling
approaches vie to better predict firm failure, often using black boxes to
deliver potentially over-fitting models, a timely reminder is sounded on the
importance of evidencing the identification process. Value is added to the
understanding of where in the parameter space failure occurs, and how firms
might act to move away from financial distress. Further, lenders may find
opportunity amongst subsets of firms that are traditionally considered to be in
danger of bankruptcy but actually sit in characteristic spaces where failure
has not occurred
