Banking On AI: Accelerating Industry Transformation
Artificial Intelligence (AI) has been a contentious issue attracting much public discourse recently, particularly in its broader implications on business and society.
Coverage in the media has ranged from sensationalist depictions of AI set in dystopian futures, to widespread news coverage detailing some unwelcome possibilities of greater use of AI in society. A recent example from the UK is the controversy surrounding the use of AI to predict the grade level outcomes for students who could not sit their A-Level exams due to COVID-19. Some students were upgraded and some downgraded by “the machine” – causing the expected outcry when the stakes are as high as coveted access to preferred universities.
The stakes are also high for global banks, who are increasing their investments in AI and remodelling workflow processes for integration into their businesses. “After years of incremental change, banks must plan for a major rethink of their operations to succeed in a rapidly digitizing and data-driven world,” said Colin Reid, Chief Technology Officer of Vox. “This was true before the COVID-19 pandemic, but has accelerated with the changes to where we work and how we conduct business,” he continued.
The investment banking industry is at the helm of the rise of AI within the workplace, just as it was a vanguard for digitization in decades past. Front offices within banks have integrated AI applications in order to deliver more efficient workflows and to capitalise on the variety of opportunities promised by the incorporation of AI into banking. “By harnessing the power of AI and machine learning, banks have the potential not just to remove cost, but also to improve control and enhance client service,” Reid said.
On the trading side, AI has had a transformative impact on the customer experience, with chatbots now offering instant responses to clients for tailored quote requests on the most complex products. Meanwhile, sophisticated algorithms analyse real-time risk and market data to optimize pricing and hedging.
Integrating advanced AI technology into traditionally manual client-facing processes also offers tremendous upside. Some firms have seen a dramatic reduction in time to onboard new clients through to automating Anti-Money Laundering (AML) and Know Your Customer (KYC) processes to better verify the identity, suitability, and risk involved in maintaining business relationships. (FinTechs are active in driving innovation in this area.)
Brexit, Initial Margin, and Benchmark Reform have required a massive amount of contract review; many banks have successfully used ML tools to analyse thousands of complex trading agreements (e.g. ISDAs) to pull out key terms, highlight risks, and determine how to update contracts in line with new regulations. Our friends at Logical Construct offer one such tool, Lynx, tailored to financial markets use cases.
But as AI continues to reform banking, it is important to look beyond what’s happening now and consider what an AI-enabled future will look like. “AI and Machine Learning have quickly altered some very complex and sensitive areas of the industry, dealing not just with internal processes but client-facing activities,” Reid said. “No area is sacrosanct.” Large banking and financial institutions need to prioritise investments in technology and AI in a bid to remain competitive.
Artificial Intelligence provides benefits to client service, control, and the bottom line, but we can also expect a reduction in team sizes and some jobs being rendered obsolete. But while traditional roles are lost, new jobs are being created in software and data fields to facilitate greater integration of AI in the day to day workings of the banking industry. This is creating a shift in the demand for certain skillsets rather than outright job losses (overall headcount continues to increase).
“The robots aren’t replacing us yet, but current employees in finance do need to adapt to work alongside new technology,” Reid said. “Someone has to run the machines! Data literacy will be in greater demand than ever, along with the ability to learn new skills as the technology evolves.”
We have seen many waves of technological upheaval before, perhaps starting when the industrial revolution resulted in an overhaul of employment structures and forced industries to readjust. Economies and employment landscapes always exist in a certain state of flux and react to changes wrought by technology.
The impact of AI on banking and almost every other area of employment is likely to mirror that shift. Perhaps increasing the use of AI in the workforce will not lead to mass job losses and loss of control to robot overlords, but instead will spell a fascinating new era in the banking industry.