Artificial Intelligence (AI) is powering rapid economic transformation in the U.S., and globally. It is fuelling historic growth in GDP, investments, and productivity thus impacting every sector of the economy. In fact, it would be difficult to imagine life without AI in the next few years or even months

The scale, magnitude, frequency and the widespread use cases of AI innovations and the consequent transformations have probably never been witnessed or experienced before by human civilization. In that sense it is a testimony to human ingenuity and collective civilizational capability.

AI has been hailed as an engine of limitless productivity and prosperity and many see the behemoth as unstoppable. AI is likely to add $4.4 trillion annually to global economy (McKinsey). The projected boost to global GDP is 14% by 2030 (PWC). Much of this is likely to be driven by banks and advanced analytics.

The impact of AI on Banking and Financial Services (BFS) is deep and transformative. It is reshaping this crucial sector of the economy in ways that few would have imagined even a few years ago.

Banks have long used AI in multiple areas. The key areas include credit risk modelling, fraud detection, mitigation of operational risks, customer management, internal forecasting etc.

According to IMF estimates, by 2027 investments in software, hardware, and services for AI systems in the financial services sector could reach $400 billion, up from $166 billion in 2023.

Many leaders – government and business – as well as influencers have shared their views on how AI may be ushering in an era of unlimited productivity and prosperity. In the same vein, others have expressed their reservations too, calling for a slowdown and / or firm regulatory guardrails on AI.

Despite all brouhaha, AI is also one of the most feared and alarming catalysts that governments and regulators all over the world are worried about. More importantly, large sections of people are apprehensive as to how it will impact their lives.

Many banking regulators around the world have raised concerns. The Financial Stability Board (FSB) has identified specific issues that have the potential to impact financial sector vulnerabilities and thereby pose risks to financial stability.

The market for third party vendors who offer cloud, specialized hardware and pre-trained models is highly concentrated and banks’ deep dependencies on this ecosystem only expose them to a range of operational / systemic risks from disruptions affecting key service providers.

The FSB points out that the widespread use of common AI models and data sources could lead to increased correlations in trading, lending, and pricing and thereby accentuate market stress, exacerbate liquidity crunches, and increase asset price vulnerabilities.

Thirdly, malicious actors could increase cyber-attacks, given the intense data usage, increased touchpoints emanating from dependence on external specialized service providers.

Increased model risk due to complexity and limited explainability of AI methods and often inability to assess data quality of widely used models. This is further heightened by the opacity of training data sources as well as inaccuracies such as hallucinations.

AI systems that are not tuned to work within the confines of legal, regulatory and ethical boundaries can pose serious risk to financial stability of the banking sector. The observations of the FSB merit attention and cannot be dismissed as alarmist.

The second biggest concern is the human cost. AI is already replacing jobs everywhere and the financial sector is no exception. Many of these are highly skilled, white-collar jobs once thought safe from automation. Consider the following.

A Goldman Sachs report (2023) estimated that up to 300 million jobs worldwide could be affected by AI, with banking and finance among the most exposed.

The World Economic Forum’s Future of Jobs Report (2023) projected that while AI will create new opportunities in data, cybersecurity, and compliance, it will also displace clerical, back-office, and customer support roles at scale.

Within U.S. banking specifically, McKinsey research suggests that 30% to 40% of current tasks could be automated by the end of the decade.

The impact on the job scene will be massive, and this could happen in the short to medium term. In other words, at current pace of AI implementation, the economy – US as well as global - could witnesses sweeping job losses, as early as in the next few years.

High unemployment, particularly loss of payroll jobs, will lead to lower consumer spending and a potential slowdown in the economy. Any amount of productivity gains in the corporate sector will not help pay the bills for millions of Americans.

This paradox is something US and other leading economies in the world must contend with. Obviously, there are no easy fixes to advocate. Unlike the wave of unemployment during the offshoring decades to reduce costs, this time around there is no retraining of the workforce.

People may neither have the resources nor the appetite to go through the grind again to re-skill. One worst case scenario could be massive social unrest just round the corner. More than likely, AI could be the harbinger of social turbulence in different parts of the world, with varying intensity in different social segments. We may not have to wait long to see for ourselves.

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