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Financial institutions are expected to double their spending on AI by 2027
Artificial intelligence tools and the people who use them are the new necessities for financial institutions and central banks around the world.
According to , in June 2023, JPMorgan Chase received 3,600 posts seeking AI support. Evident Insights Ltdis a London-based startup that tracks AI capabilities across financial services companies.
“There is a war for talent,” said Alexandra Mousavizadeh, founder of Evident Insights. “Right now, it’s really a matter of life and death to stay ahead of the curve.”
Like any technological advancement, AI brings new possibilities with new risks. The financial services industry could be one of the biggest beneficiaries of this technology, which could improve asset protection and market predictability. Or, if AI leads to theft, fraud, cybercrime, or even a financial crisis that investors cannot imagine today, this sector could stand to lose the most.
The debut of OpenAI’s ChatGPT in November 2022 is making waves in the financial industry and beyond. The number of users soon exceeded 100 million, making it the fastest growing application on the Internet. history.
The financial industry is in high demand globally for people who know how to leverage AI. Mousavizadeh, an economist and mathematician and former co-head of country risk at Morgan Stanley, said three of the top 10 cities in Evident’s talent index are in India.
economical hug
The money flowing into AI from financial and other companies is highlighting new priorities. Sales of software, hardware, and services for AI systems are expected to increase by 29% this year to $166 billion and exceed $400 billion by 2027, according to International Data Corporation. Masu. Financial sector spending is expected to increase by 29% in 2027, more than doubling he to $97 billion. According to market researchers, the annual compound growth rate is the fastest among the five major industries.
Hedge funds, which have long been pioneers in cutting-edge technology, are embracing generative AI. According to BNP Paribas, nearly half of them use their ChatGPT professionally, and more than two-thirds of them use it to create marketing texts or summarize reports and documents. I’m using ChatGPT. investigation A fund with total assets of $250 billion.
Investment businesses are harnessing and exploring the potential of AI in various business areas. Amundi SA, Europe’s largest investment company, is building its own AI infrastructure for macroeconomic and market research. The company is also using the technology in applications such as robo-advice tools for private clients.
Paris-based Amundi, which manages €2 trillion ($2.1 trillion), uses AI-based tools to ask some of its more than 100 million customers about their risk preferences and customize their portfolios. are doing. The answers help shape your portfolio and provide a real-time sentiment gauge.
AI tools are trained on historical data that may not reflect reality in an unprecedented situation, which could make the crisis worse, whatever the cause.
Aggregated view
“Using these kinds of algorithms allows us to see what our clients are doing,” says Monica Defend. Chief Strategist at Amundi Investment Institute, the company’s research strategy division. “Not only does it benefit our customers, but it also gives us a holistic view of how attitudes are changing across this user base.”
In other applications, such as institutional decision-making around investments and transactions, the use of AI could be limited by data that proves to be unreliable or by situations with unprecedented high impact, he said. said. It is also a priority to avoid abuse and ensure that AI is used within a secure, ethical and compliant framework.
“Artificial intelligence will not replace the brain,” Defend said. A fully AI-driven process can be risky, she says. “It is equally important to interpret, understand, and confirm what the algorithm provides.”
JPMorgan, the nation’s largest financial institution, spends more than $15 billion a year on technology and employs nearly a fifth of its roughly 300,000 employees in technology. His AI research group employs 200 people, and AI enables: hundreds of It is used for a variety of purposes, from research and marketing to risk management and fraud prevention. AI also runs in payment processing and funds transfer systems around the world.
CEO Jamie Dimon: “This is absolutely necessary” Said Shareholders in April.
world of money
There is much more at stake for policymakers protecting the economy. Central banks, which are slow-moving and risk-averse by nature, are learning how to leverage AI in very different contexts and considering potential risks.
AI has shown promise in a variety of central banking applications, including supervision.Brazil’s central bank builds prototype robot Download consumer complaints about financial institutions and classify them through machine learning.Reserve Bank of India this year hired Consulting firms McKinsey and Accenture will support the implementation of AI and related analytics in supervisory operations.
The Basel Committee on Banking Supervision has found that AI has the potential to improve lending efficiency in making credit decisions and preventing money laundering. The Central Banker and Banking Supervisory Board serves as one of the world’s top regulatory standard setters.Also quoted Risks such as understanding the results from opaque models to the potential for bias and greater cyber risk.
“Oversight processes that can determine what is safe and sound and distinguish between responsible and irresponsible innovation will undoubtedly be improved,” said Neil Esho, the commission’s executive director. Said last year. “For now, we still have a long way to go.”
The Bank for International Settlements (BIS), a group of global central banks with its committee secretariat in Basel, Switzerland, has been testing a variety of potential uses. BIS Innovation Hub project auroraFor example, we showed that neural networks, a type of machine learning, can help detect money laundering by sniffing out patterns and anomalies in transactions that cannot be identified using traditional methods.
signal in noise
The Bank of Canada built a machine learning tool to detect anomalies in regulatory filings. Mariam Haghighi, director of data science, said the automated daily execution captures things that humans don’t, while freeing up staff to follow up on analysis.
“This is an example of the real power of AI for central banks,” Hagighi said. “This is quite a tedious task, but AI can be trained to do it better and faster than humans.”
The European Central Bank (ECB) using AI for applications like automating the classification of data from 10 million businesses and government agencies, scraping websites to track product prices in real time, and more. We also use this technology to help bank supervisors find and analyze news articles, supervisory reports, and corporate filings.
ECB Chief Services Officer Miriam Mufakir said that as the world of data grows rapidly, making data understandable and clean is a key challenge, especially when it comes to unstructured data. AI helps humans make important distinctions. The ECB is also considering large-scale language AI models that can help people write code, test software, and even make public communications easier to understand.
financial stability
John Danielson, a researcher at the London School of Economics, the study He said he is looking at the technology’s capabilities on a continuum, from basic to advanced, to see how AI will impact the financial system. The basic aspect is chess, where there are pieces on the board and the rules are known to everyone. There, AI can easily beat humans, but that advantage diminishes as complexity increases. People caught in unexpected situations can draw on a variety of knowledge, from economics and history to ethics and philosophy, to make better-informed decisions. And for now, he said, this is where humans beat AI.
AI is already making important financial decisions, such as processing credit card applications, and is rapidly penetrating the public and private sectors. The technology will help banks prevent fraudulent activities such as taking advantage of customers and allowing fraud and money laundering, he said. At the same time, such expanded use could pose risks, he said.
“Even if you start trusting the technology, the more you use it, the more it creeps up on you,” Danielson says.
U.S. Securities and Exchange Commission Chairman Gary Gensler has said that AI could cause a financial crisis.he has a responsibility to protect someone 46 trillion dollars The stock market accounts for two-fifths of the world’s total. Financial stability risks from AI require “new thinking about system-wide or macroprudential policy interventions,” he said. Said Reporters in July. “AI has the potential to increase financial vulnerabilities because it can encourage clustering, with individual actors making similar decisions because they are receiving the same signals from underlying models and data aggregators. ”
The warning reflects Gensler’s work as a professor of global economics and management at the Massachusetts Institute of Technology, where he published a 2020 paper with Lily Bailey on deep learning. They write that that subset of AI offers “previously unseen predictive capabilities that enable significant opportunities for efficiency, financial inclusion, and risk mitigation.” But they warned that financial regulations rooted in previous eras are “likely insufficient to address the systemic risks posed by the widespread adoption of deep learning in finance.”
“Polycrisis” factors
Another danger is that AI tools are trained on historical data that may not reflect reality in an unprecedented situation, which could worsen the crisis, whatever the cause. says Anselm Küsters, Head of Digitalization and New Technologies at the European Center. Berlin policy.Custars is quoted term polycrisispopularized by fellow economic historian Adam Tooze, refers to the interaction of various shocks that add up to be worse than the sum of the parts.
Increasing use of opaque AI applications “creates new systemic risks” as negative feedback loops can rapidly amplify, Küsters said, telling the European Parliament that “algorithmic predictions that arise in times of crisis” “Focus on further risks of
Questions like these posed by rapidly evolving technology will confront central bankers and other policymakers in the coming years, as the benefits and threats become clearer.
“We are not yet at the stage where we know what makes sense for the central bank authorities,” ECB’s Mufakir said. “We’re just getting started.”
The opinions expressed in articles and other materials are those of the authors. They do not necessarily reflect IMF policy.
