s natural language processing technology evolves, consumers find it increasingly difficult to distinguish between a voice bot and a human customer service representative. This stems from improved abilities on the part of voice and chatbots to resolve customer issues without human intervention.
The benefits to banks of customer service automation are obvious: AI could lead to significant cost reductions. A recent study by Autonomous predicted that AI could lead to 1.2 million jobs being cut in the banking and lending industry, resulting in up to $450 billion in industrysavings by 2030.
Despite the potential rewards customer service automation promises, banks and other businesses need to proceed with caution in relying too heavily on voice and chatbots. The popularity of GetHuman illustrates this: It’s a website that connects consumers with human CSRs to resolve their issue. In fact, voice and chatbots often work best when augmenting rather than replacing humans. At a minimum, the option to speak to a human, if necessary, should be readily available.
Want an example of how banks are creatively employing AI to serve customers? The Swiss bank UBS, ranked number 35 globally for its volume of assets, according to Accuity’s August 2018 global bank rankings — has partnered with Amazon to incorporate its “Ask UBS” service into Alexa-powered Echo speaker devices.
Ask UBS, which is aimed at UBS’s European wealth management clients, enables users to receive wide-ranging advice and analysis on global financial markets just by “asking” Alexa. “Ask UBS” also acts as a teaching resource, offering definitions and examples of acronyms and jargon related to the financial industry.
Banks have access to a wealth of customer data, including detailed demographics, website analytics and records of online and offline transactions. By utilizing machine learning to integrate and analyze information from multiple, discrete databases to form a 360-degree customer view, banks are better positioned to personalize products, services and interactions based on the behavior of individual clients.
According to James Eardley, global director of industry marketing for enterprise software giant SAP, “The next step within the digital service model is for banks to price for the individual, and to negotiate that price in real time, taking personalization to the ultimate level.”
While personalized pricing of this kind may only become prevalent in the future, banks are already utilizing AI-processed behavioral data to advise individual clients on appropriate credit and savings products, based on their goals and habits. Santander, the world’s 14th largest bank, measured by its current assets, even hosted a competition, with a prize of $60,000, on the machine learning crowdsourcing site Kaggle, encouraging data scientists to write code that better “pairs products with people.”
The fintech revolution is still in its infancy, but alongside AI, it has already had a substantial impact on the way traditional banks do business. This presents digital entrepreneurs and investors with myriad opportunities for improvement.