The shortest explanation: performing Kolmogorov-Smirnov tests does not guarantee reliability without strict conditions.
The validity of the analysis depends entirely on the quality and nature of the data.
A realization is not reliable if the test assumptions are violated, hiding real risks.
For example, KS tests on non-stationary market data in Singapore could show an apparent similarity while ignoring significant tail risks for the local currency.