Banking with Artificial Intelligence
Faced with unprecedented challenges, banks have started racing to embrace AI to gain a competitive advantage
With the advent of chatbots, personal assistants, and robo-advisors, it may not be too hard to imagine that the next wave of technology could revolutionize the traditional style of banking.
An Accenture report recently indicated that within the next three years, banks will deploy Artificial Intelligence (A.I.) as their primary method to interact with customers. In early 2016, Swedish-speaking Amelia became the first non-English deployment of IPsoft’s AI platform at SEB, one of Sweden’s largest bank. The bank adopted “digital employee” Amelia to integrate into its front-office. The cognitive agent solves problems just like humans “but in a fraction of the time”, interacts just like humans and even senses emotions.
But Amelia is just one aspect of what the future of banking may look like. As estimated by Gartner, by 2020, customers will manage 85 percent of their association with a business with no human interaction. With changing customer needs and a growing generation of millennials, a bigger challenge for banks is the fierce competition from tech-savvy firms like Apple, Amazon, Facebook, and Google. According to a report by Citi in 2016, 30% of banking jobs (close to 2 million jobs) are under threat across US and Europe over the next decade.
Tech giants are offering financial services that are both popular and a preferred method by most millennials — a large demographic of the economy. The Millennial Disruption Survey points out that nearly half of the millennials surveyed are counting on tech start-ups to overhaul the way banks work and as many as 73% millennials would be more excited for new financial services offered by Google, Amazon, Apple, PayPal or Square than from their own nationwide bank. Faced with unprecedented challenges, banks have started racing to embrace AI to gain a competitive advantage. The AI adoption in banks is spreading across different operations some of which are highlighted below:
By replacing old statistical approaches, traditional banks are adopting cognitive computer technology to detect early fraud detection. This will prevent theft of personal information and funds. To use AI technology to detect fraudulent phone calls, Lloyd’s Banking Group recently partnered with US-based startup Pindrop.
The patented Phoneprinting™ technology is Pindrop’s innovative software that identifies 147 different features of a human voice from one call. It creates an audio fingerprint of that caller and looks for unusual activity, potential fraud so as to trace criminal callers.
Bank of America will be launching its virtual assistant, Erica, later this year that will be integrated into the mobile banking app to continue to help clients improve their financial lives.
Besides fraud detection, banks are also adopting AI to personalize services and provide real-time solutions to client-specific needs.
In 2013, ANZ Bank in Australia, was among the first banks to explore the possibilities of AI. It began using IBM’s Watson to help its financial advisors understand their clients. The bank now plans on extending its cognitive computing into areas like advisory, risk, and back office automation. Leading investment bank Goldman Sachs invested in an AI-based financial research platform Kensho in 2014.
The analytics platform can instantly respond to complex situations, query millions of documents and can be questioned using natural language. In February 2017, Wells Fargo created an AI team to provide more personalized services to its customers and strengthen its digital offerings.
Banks have started deploying AI for other services as well including wealth management and financial advisory. Bank of America will be launching its virtual assistant, Erica, later this year that will be integrated into the mobile banking app to continue to help clients improve their financial lives. In 2014, Bloomberg reported that Swiss Bank, UBS picked Singapore-based Sqreem to identify behavioral patterns of individuals and show potential match-ups with different types of wealth management products for each individual.
In March 2017, JPMorgan hired a new team altogether to automate its legal work. The program, named Contract Intelligence or COIN, automates hours of reading, including interpretation of commercial loan agreements which, until it went online late last year, consumed over 360,000 hours of work each year by lawyers and loan officers. Now it’s done in seconds and with fewer errors by a system that never sleeps.
As AI floods the banking channels, many have raised concerns about the future of traditional banking jobs that face “the automation risk”.
According to a report by Citi in 2016, 30% of banking jobs (close to 2 million jobs) are under threat across US and Europe over the next decade. With a decline in office branches, the number of US branch tellers have already declined by 15% since 2007. However, many are adamant that AI in banking will not be a threat to the banking industry.
Last year, ANZ CTO Patrick Maes told iTnews in an interview,
This is just taking the monotone and repetitive tasks we have created through complexity in the IT landscape out, where we basically have humans becoming the integration between two systems; that is what will be replaced.
Some opinions expressed in this article may be those of a guest author and not necessarily Analytikus. Staff authors are listed in https://www.datasciencecentral.com/profiles/blogs/banking-with-artificial-intelligence