From that perspective, surely you can draw no conclusion of causality from this data, or any conclusion you can draw has little predictive power about the direction of effect for a given sample.

Poor people are more likely to take high-interest loans/advances, and people who take high-interest loans are more likely to be poor. You can suggest causation both ways if say, you study a group of middle-class people who took high-interest loans and find them more likely to be poor years later.

If A causes B but B also causes A is it wrong to say causality goes both ways?

A is both cause and effect. B is both cause and effect. I think this is nearly as common as causality going one way (like if we found that smoking causes cancer, but cancer causes people to be less likely to smoke).

> In life there can be multiple causes and multiple effects, but causality itself has one direction, doesn't it?

Causality is an inherently parameterized description of reality. I'm saying that the terms people are using to describe this complex effect are too few and each far too high grained to draw any firm conclusions.