What picture does your mind envision when you hear ‘Trading floors’? Probably one in which a bunch of flamboyant men is frantically gesticulating and incessantly cursing while working in a chaotic environment or a similar scene from The wolf of wall street. Well, these ubiquitous floor brokers have now slowly surrendered to fully automated or assisted technologies. In 2019, the founder of a large algorithm-based hedge fund, Renaissance Technologies, earned $1.6 billion in profits and was placed as the highest-paid hedge fund manager of the year.
With only about 40 people on the trading floor, Citadel Securities trades more than 8 million securities in a day. The fintech industry raised nearly $30 billion in the year 2019. To say it out loud, the disruption of the financial industry by the emerging technological developments is inevitable. Namely, artificial intelligence is at the forefront of spearheading this change.
Automating the tasks that typically require human intelligence, this interdisciplinary branch of science with multiple approaches has allowed financial firms to handle non-routine tasks and processes requiring essential employee judgment and problem-solving qualities with greater ease. AI holds the power to metamorphosize the affairs of processing, analyzing and forecasting faster with increased accuracy. It facilitates workers to spend more time on higher-level tasks that necessitate the application of brainpower and others that these AI-enabled systems can’t handle, yet!
According to PWC’s AI survey conducted in 2019, financial executives expect their AI endeavors to yield an increase of 50% in revenues and 42% in innovative products. Simple AI solutions such as advanced analytics, process automation, robot advisors, and self-learning programs are becoming paramount especially for banks and credit lenders in redesigning their fraud detection and anti-money laundering contrivances. Investment banking companies are also harnessing AI to execute trades, manage portfolios, and dispense personalized services to their clients. Insurance organizations have been turning to machine learning– the application of AI that allows systems to automatically learn and improve from the experience without being manually programmed, to improve their products and pricing, strengthen the customer services and billings and develop more on their fraud predicting and preventing mechanisms.
Forbes predicts that “by 2020, accounting tasks including tax, payroll, audits, and banking will be fully automated using AI-based technologies, which will disrupt the accounting industry in a way it never was for the last 500 years, bringing both huge opportunities and serious challenges.”
In order to effectively capitalize on the power of AI, companies in the financial services industry took a step back to understand the fundamental relationship between employees and machines in an internal as well external environment with their value chain partners. Instead of taking a siloed approach and having to reinvent the wheel with each new initiative, financial services executives now prefer to consider using AI tools systematically across their organizations, encompassing every business process and function. Leveraging on the digitization of the financial products, AI allows more transparent and accessible services, within the context of a digital society.
Forward-thinking companies are actively exploring the world of AI and its uses in finance in order to gain a competitive edge in the market. So much so that they aren’t shying away from spending millions and billions of dollars to acquire the tech companies. It seems that the financial ecosystem is completely smitten with the potential that AI carries. February’20 witnessed the biggest acquisition by a major Wall Street bank since the financial crises of the late 2000s.
The international investment banking giant, Morgan Stanley spent a whopping amount of $13 billion dollars to acquire the internet investing pioneer, E-Trade which is an electronic trading platform recognizing trading decisions by informed machine learning. Morgan Stanley chief executive and chairman James Gorman said acquiring E-Trade would continue a tradition for the bank embracing more solid ways of bringing in revenue. Similar testimonials were received from Crest Financial, an American leasing company, who observed paramount improvements in their risk analysis workings after they employed artificial intelligence on Amazon Wed Service platforms.
As the financial service sector around the world now runs the AI leg of the digital marathon, one of the completely indispensable questions that come to our mind needs to be answered. What makes the frontrunners stay ahead of their peers? How do they integrate AI into their business?
Well, a study conducted on nearly 200 US companies to understand how they’re using AI and the impact that they’ve witnessed, concluded that all the frontrunners were able to lead when they embedded artificial intelligence in their strategic planning and decision-making processes and ensured its organization-wide implementation. Other than this they also focussed on applying AI as much as possible in customer and revenue engagement opportunities. It was also found that they were acquiring or developing AI in multiple ways what usually is referred to as the portfolio approach. This approach likely enabled them to accelerate the development of AI solutions through options such as AI-as-a-service and automated machine learning. At the same time, through crowdsourced development communities, they were able to tap into a wider pool of talent from around the world.
But the frontrunners are also struggling with the same technology which is promising a large number of boons. In all, it may seem to you that using AI is a total win-win situation for financial institutions. But is it really? In reality, with all the rewards that AI offers, comes huge risks that can cost the companies and its clients a great deal. Starters and followers should probably take a page out of the frontrunners’ book as they have a more realistic grasp on what comes with AI as they scale upon its merits.
Incorporating a biased data set resulting in biased results, privacy risks- misuse of financial data, market abuse-risk that AI is used to further financial crime, including the testing of algorithms to assess the impact they may have on market integrity, alongside post-trade monitoring are some of the concerns that big names in the science and tech family-like Stephan Hawking, Elon Musk and Steve Wozniak have recently expressed, joined by many leading AI researchers around the globe.
But should we let these concerns lift the spotlight that AI has been receiving in the financial industry? Certainly not. With the adoption of AI and other game-changers like cryptocurrency and blockchain, the financial ecosystem is rapidly transforming with each passing day. Predictions for the soon to come AI applications in financial services with high transactional and account security are expected to bring in a new level of transparency which stems from more comprehensive and accurate cognitive processes. Altogether AI has a shining future ahead, we need to hang in there and let technology do wonder in front of our eyes.
Written By: Neha Haldia
(Neha is a second-year BCom Honors student at Shri Ram College of Commerce)