How artificial intelligence is changing the role of banks
Artificial Intelligence (AI) — and its growing impact on and applicability for individuals and businesses alike — is one of today’s most widely discussed topics. From virtual assistants like Siri and Alexa, to chatbots created by Facebook and Drift, AI is having a significant impact on the lives of consumers.
A study from Statista showed that the number of consumers using virtual assistants worldwide is expected to exceed one billion in 2018.
It is readily apparent how AI-powered technology is making inroads into everyday life through DVAs and other consumer products, but AI is also having a transformative effect on an industry that impacts virtually all consumers and businesses: banking.
As 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.
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.
While Ask UBS can make a call from a UBS financial advisor to a customer’s phone upon request, it is not yet able to access individual portfolios, execute trades or perform other transactions; it can’t offer personalized advice based on a client’s holdings and goals.
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.
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.
In the banking and payments industry, personalization extends far beyond marketing and product customization, into security. A growing number of banks are utilizing biometric data, like fingerprints, to replace or augment passwords and other forms of client verification.
One of the most promising applications of AI in banking comes from automating high-volume, low-value processes. In one example, reported by McKinsey, JPMorgan began using bots to process internal IT requests, including employees’ attempts to reset their work passwords.
Up to 1.7 million requests were expected to be handled by the bots in 2017, doing the work of 40 full-time employees.
The ability of AI to sift through massive amounts of data and identify patterns that might elude human observers is one of its greatest strengths. One area where this capacity is particularly relevant is in fraud prevention.
According to McAfee, cybercrime costs the global economy $600 billion. AI and machine learning solutions are being deployed by many financial service providers to detect fraud in real time.
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.