Are robots taking over financial jobs around the world?
The year is 2030. You are in a conference room at a business school, where only a handful of students are taking a finance course.
The dismal attendance has nothing to do with the style of the teacher, the ranking of the school or the subject. Students are simply not enrolled because there are no jobs for finance majors.
Today, finance, accounting, management and economics are among the most popular subjects in universities around the world, especially at the graduate level, due to their high employability. But that is changing.
According to consultancy firm Opimas, in the years to come, it will become increasingly difficult for universities to sell their business-related degrees. Research shows that 230,000 jobs in the sector could disappear by 2025, completed by “artificial intelligence agents”.
Are robo-advisers the future of finance?
A new generation of AI
Many market analysts believe this.
Investments in automated wallets increased 210% between 2014 and 2015, according to research firm Aite Group.
Robots have already taken control of Wall Street, as hundreds of financial analysts replaced by software or robo-advisers.
In the United States, claims a 2013 paper According to two Oxford academics, 47% of jobs are at “high risk” of being automated over the next 20 years – 54% of jobs lost will be in finance.
It’s not just an American phenomenon. Indian banks have also reported a 7% downsizing for two consecutive quarters due to the introduction of robots in the workplace.
It is perhaps not surprising. After all, the banking and financial industry relies primarily on information processing, and some of its key operations, like updating the passbook or depositing cash, are already heavily digitized.
Today, banks and financial institutions are rapidly adopting a new generation of artificial intelligence (AI) -based technology to automate financial tasks typically performed by humans, such as operations, wealth management, algorithmic trading and risk management.
For example, JP Morgan’s Contractual Intelligence Program, or COIN,, which runs on a machine-learning system, has helped the bank reduce the time it takes to review loan documents and reduce the number of loan service errors.
Such is the growing dominance of AI in the banking industry which, Accenture predicts, over the next three years, it will become the primary means by which banks interact with their customers. AI would allow simpler user interfaces, their 2017 report notes, which would help banks create a more human customer experience.
Meanwhile, HDFC, one of the largest private sector banks in India, has launched Eva. India’s first AI-powered banking chatbot can assimilate knowledge from thousands of sources and provide answers in plain language in less than 0.4 seconds. At HFDC, Eva joins Ira, the bank’s first humanoid assistant.
AI has also made inroads into the investment industry, where many financial analysts believe a sophisticated trading machine capable of learning and thinking will eventually make the most advanced investment algorithms look primitive. and the most complex today.
Advisory bots allow companies to assess transactions, investments, and strategy in a fraction of the time it takes today’s quantitative analysts to do so using traditional statistical tools.
Former Barclays boss Antony Jenkins, who called disruptive banking automation an “Uber moment,” predicted this technology will lay off half of all bank branches and financial services employees around the world within ten years.
Goodbye, human fund managers.
FinTech graduates of the future
Universities are now revising their educational master plan to adapt to this technological breakthrough in the finance job market.
The two Stanford University and Georgetown University business schools plan to offer what is called “fintech” in their MBA programs, hoping to teach students how to become masters in financial technology.
And Wales-based Wrexham Glyndwr University announced the launch of the UK’s first undergraduate degree in fintech.
But fintech is so new and diverse that academics are struggling to craft a curriculum for Financial Technology 101, let alone more advanced topics on AI. The lack of academic textbooks and expert teachers is an additional challenge.
Robots gone mad
Still, it’s not clear whether AI and automation will actually prove to be beneficial for banks.
Too much reliance on AI could backfire on financial institutions if they lose the human touch that most customers prefer.
There are also other risks. Robo-advisers are inexpensive and save time when building a simple investment portfolio, but they can struggle to take the proper precautionary measures when markets become volatile, especially when thousands. , even millions of machines all try to do the same thing while running at high speed.
High expectations about the performance of these well-programmed robot traders could also cause chaos in major malls around the world.
There is no single algorithm that can combine multiple volatile variables with a functioning multidimensional economic forecasting model. for all investors. Expecting this could turn out to be a potentially fatal mistake for financial markets.
And how will investors be protected when bots make the wrong decision? According to the decisions of the United States Securities and Exchange Commission (SEC), robo-advisers must be registered in the same way as human investment advisers. They are also subject to the rules of Investment Advisers Act.
But it is difficult to apply financial regulations designed to govern human behavior to robots.
SEC rules, created to protect investors, require advisors to adhere to a fiduciary standard that unconditionally puts the client’s best interests ahead of their own. Concerned US regulators asked if it was practical for robots follow the rules when their decisions and recommendations are generated not by ratiocinations but by algorithms.
This riddle clearly demonstrates one fact: it is difficult to completely replace humans. There will always be a demand for a real person to check when and if our robots are going rogue.