Whilst it’s true that the introduction of analytical processes discovered the example above, it was an accidental discovery rather than one that specialized systems would have uncovered. For data analytics to be effective in any business, the objectives have to be clearly laid out so that the data analysts know what to look for.
Of greater concern is the fallacy that most fraud is perpetrated by external operators. This is clearly not the case, and any management team that turns a blind eye to the discovery of leakage or potential fraud must surely come into question – equally so for anyone ignoring the potential of big data analytics for more than just “improving the customer experience”.
Of course, the reasons for not investing may have valid financial grounds – like the cost exceeding the returns – but can also be exacerbated by the fear of poor business management processes being uncovered. Why take the risk if the business has been profitable for many years? Others simply believe that their processes are infallible and don’t need to be monitored.
For those in denial, it is very clear that they either “don’t know what they don’t know” or is it simply that they “don’t want others to know what they do know”!