Wednesday, October 10th, 2018 | 8 min read
Walter Wriston, former Citibank CEO and fintech pioneer, once said, “Information about money has become almost as important as money itself.”
The observation is notable because it’s true, and because Wriston made it decades ago – well before the arrival of today’s artificial intelligence (AI) technology that can process information on a once-unimaginable scale.
When information failure occurs, however, especially on Wall Street, chaos ensues. The recent ten-year anniversary of the global financial crisis inspired a period of analysis and reflection. Although the global economy has made great progress since those dark days, there is still room to improve. AI can become the key driver of that improvement.
While use cases like transportation garner much of the headlines, finance brands are doing the most to harness tools like data analytics and deep learning. Not only do these tools transform internal processes, they create great value for customers.
Here are four notable examples.
For many people, making personal finance decisions is a necessary source of stress. But what if a company could alleviate much of that stress using artificial intelligence? Pefin, a New York fintech startup, may have the solution.
Automated financial advice is becoming more commonplace as consumers chase greater returns, yet Pefin bills itself as “the world’s first AI financial advisor.” The company uses machine learning to deliver financial planning and investment advice via a chat interface.
The company’s AI platform can create advanced models based on different variables, such as showing you how moving to a new state would affect your retirement savings. It takes into account millions of data points over the life of the user for its calculation. As the user uses the platform, it increasingly understands whether they are net savers or net spenders, and that helps the neural network to be more predictive.
Pefin’s application of AI technology has been warmly welcomed – the company received the People’s Choice Award for interactive innovation at SXSW 2018.
In late 2016, Bank of America unveiled “Erica,” a virtual assistant that helps customers make smarter financial decisions.
Erica uses artificial intelligence, predictive analytics and cognitive messaging to help customers make payments, check balances, save money and pay down debt. She can also direct people to educational videos and other content.
Customers can chat with Erica – a play on the bank’s name – via voice or text message.
Bank of America began rolling out Erica across the United States to its 25 million mobile clients in May 2018. User adoption is positive thus far – Erica surpassed one million users within two months of its phased rollout.
Meanwhile, in a move that will likely become commonplace as AI evolves, Bank of America has launched a set of online courses to train employees for new and evolving roles in the company. The new online courses – dubbed GT&O University – were introduced in late April. They stem from the bank’s desire to train employees for new, AI-era jobs and the “very real and day-to-day need for people to stay motivated about working here,” says Cathy Bessant, Bank of America’s chief operations and technology officer.
Workers can choose from classes in four “colleges” encompassing basic banking skills, technology, operations and leadership.
One of the most promising applications of AI in banking comes from automating high-volume, low-value processes. In one example, reported by McKinsey, J.P. Morgan 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. However, it is in back-end operations that J.P. Morgan’s AI investment has proved most fruitful.
In 2016, the bank introduced a Contract Intelligence (COiN) platform designed to “analyze legal documents and extract important data points and clauses.” Manual review of 12,000 commercial credit documents normally requires more than 360,000 hours annually. Results from an initial implementation of this machine learning technology showed that the same amount of agreements could be reviewed in seconds.
— J.P. Morgan (@jpmorgan) February 28, 2017
The potential for AI to streamline back-end operations has significant implications for cost savings, faster service, and the capacity to redirect staff to high-value activities that cannot currently be completed by AI-powered tools.
Amazon’s popular Super Bowl 52 commercial laid out a tongue-in-cheek crisis in the future of artificial intelligence: When Alexa loses her voice, what do you do?
Enter a series of stand-ins, including actor Anthony Hopkins, who goes into creepy Hannibal Lecter mode and unnerves the people he’s supposed to help. Thankfully, Alexa recovers her voice and restores order.
UBS is hoping that Alexa stays clear of any vocal issues going forward. The Swiss bank has partnered with Amazon to incorporate its “Ask UBS” service into Alexa-powered Echo speaker devices. Ask UBS, which is aimed at the bank’s European wealth management clients, enables users to receive wide-ranging advice and analysis on global financial markets by “asking” Alexa. Ask UBS also acts as a teaching resource, offering definitions and examples of acronyms and jargon related to the financial industry.
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. According to the Wall Street Journal, the reason is primarily security and privacy concerns. However, a UBS spokesman states that the bank’s aim is to make Ask UBS and similar tools “secure, compliant, and trustable for clients.”
Ask UBS emerged from the Swiss bank’s “Wealth Management Innovation Lab,” which was set up in 2014 to help UBS identify next-generation products and services.
Researchers and think tanks will continue to map out a trajectory for artificial intelligence, but the nature of finance is such that predictions are almost impossible. Some say that another global recession is just around the corner, while others remain bullish about the near future.
The World Economic Forum (WEF) has warned that AI could destabilize the complex financial system, as a more networked world is more vulnerable to cybersecurity risks. However, it appears that brands have measures in place for any eventualities.
Last April, Harvard Kennedy School and Bank of America announced the formation of The Council on the Responsible Use of Artificial Intelligence, a new effort to investigate how to use AI in a responsible manner across various domains. Meanwhile, IBM has launched AI Fairness 360 (AIF360), a tool that will scan for bias in AI algorithms and recommend adjustments in real time.
The boom and bust cycle of the global economy is unclear at best, but what’s clear is this: AI will reinvent the world of finance. It’s not a question of when, but how quickly.
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