Artificial Intelligence takes many forms in banking, but most firms have yet to begin implementing the technology. Learn where AI can add value to your bank and which specific technologies you should evaluate first.

Artificial Intelligence (AI) is extraordinarily popular when judged by today’s banking headlines, but those headlines have outpaced today’s practical banking reality. Relatively few banks have begun production or even full-blown research at this stage, so Celent seeks to provide an introduction and path forward for banks studying this hot topic. We take a pragmatic approach that defines AI in banking as technology that makes inferences and decisions that used to require direct human involvement. A series of fundamental and interrelated technologies around machine learning and natural language underpin all of AI. Crucially, AI is not just automation or better technology. It is not faster processing, bigger data sets, or even thousands of rules rigidly applied. These advances have yielded powerful results, but they’re performing old tasks better. That AI can respond to ambiguous real-world inputs probabilistically is one of its critical features. Building off the fundamental technologies to apply them in a banking context yields four main AI applications today: analytics; bots; robotic process automation (RPA); and report generation.