But even those who dominate the intentions of these reports exploit their analytical capacity in a really small percentage, not for lack of knowledge or capacity but because, until recently, the conditions for it to be different had not been met.
Let’s review some characteristics of financial information, technological advances and a bit of statistics and see if putting them together we achieve a virtuous convergence.
The data contained in the financial statements are agnostic and universal; that is, regardless of the size of the company, line of business or geographic region, its meaning is the same or, in the worst case, extremely similar (assets, liabilities, capital, depreciation, income, costs, expenses, interest, and endless etceteras).
They have statistical relativity and we can do significance exercises which allows us to use analytical processes to compare entities that, at first glance, could be dramatically different.
The treatment we have given them so far makes them monolithic and rigid; namely “My data is my data and I do not share it”. In addition to having in this a mistaken sense of belonging, it is necessary to say that the technological and security conditions did not exist for it to be different and that it would be convenient and/or useful in sharing information.
The serious thing about all this is that the analytical process becomes an act of perceptions: “My current assets to current liabilities ratio is 1.2, is this bad or good?”question to which we should answer with an inexorable and useless: it depends.
Artificial intelligence (AI) is advancing by leaps and bounds, allowing us not only to enhance analytical and predictive capabilities, but also to make the data collection process downright simple and without any friction or additional work.