Artificial Intelligence (AI) is revolutionizing banking. It’s automating processes, transforming customer experiences and making products and services more attractive. Credit card issuers are even using it to create competitive advantages. The technology is now mature enough that even technophobic organizations should be getting on board.
But how does it work?
AI personalization technology creates a virtual representation of every relevant business entity by building a profile from their actions and activities. For example, at a bank, the profiles (known as ‘smart agents’) could represent each individual cardholder, merchant and terminal.
Smart agents & chatbots
The smart agents learn in real time from every transaction, then track behaviors. There are as many smart agents as active entities in the system. For example, if there are 100 million active cards, there will be one smart agent for each card, continuously analyzing and learning the cardholder’s behavior. This enables the bank to make customized decisions specific to each cardholder, a big upgrade over historical processes that applied the same logic to all customers regardless of their individual characteristics.
The technology is now mature enough that even technophobic organizations should be getting on board.
The smart agents are self-learning and adaptive since they continuously update their individual profiles from each activity. Smart agents can predict where and when cardholders will make their next purchases with frightening accuracy. This individualized information enables more effective promotions, such as campaigns, to increase card usage. It also enables automated customer service online, via telephone and even via chatbots — computer programs that can have conversations and service customers. These chatbots have become so sophisticated that they are capable of learning to recognize voices and images.
They are even able to show empathy when servicing customers. Major banks like Wells Fargo have begun using AI-driven chatbots to communicate with customers through the Facebook Messenger platform, reducing strain on call centers and reducing servicing costs.
Flexing GuNS to fight fraud
Finally, smart agents can greatly improve risk management and fraud prevention. New fraud prevention practices include smart agents and machine-learning techniques known as ‘generative adversarial networks,’ or GANs. These GANs continuously re-train themselves to recognize patterns of fraudulent behavior by running pattern recognition algorithms against transactional data. The system then generates new, falsified transaction data, which is then entered into a separate system that uses similar pattern recognition methods, to discriminate between the real and the falsified data.