A Tidal Shift for AI in Banking

In a galaxy [not at all] far, far away… was a commonly accepted idea that the bigger banks could hire the best talent, implement state of the art technologies, and ultimately enhance bottom line revenues via improved risk modeling, novel product offerings, etc. This concept is the proverbial'black box' of large banking institutions and how their success has been perceived for many years, which in broad strokes, is fairly accurate. But what has changed in the recent years and why are smaller institutions so keen on getting their hands on this sexy new tech? For starters, those huge banks have made extraordinarily large investments over the past decade in order to continue validation of their claim to the top rungs of industry and to service the largest clients available. However, thanks to their valiant efforts of progressivism, and some well-placed IPO funding rounds of promising AI unicorns, they managed to provide an industry fresh off its second'AI winter' with the funding necessary to inspire entirely new solutions applicable to the broader public. The other important aspect of this boom in a large bank's successful employment of data science applications is attributed to the vast quantities of data amassed at a scale that's exponentially larger than that of smaller banks.