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OpenAI’s ChatGPT acquired one million users five days after its launch in November 2022, igniting a gold rush in the artificial intelligence and digital transformation of the workplace. Since then, the ascendancy of AI has led to public speculation about the impact that the fast-emerging technology will have on jobs.
In a chilling, new report by Citigroup, the global investment firm concluded that the banking industry will be the hardest-hit by the deployment of AI, with $54% of roles at risk for AI-led job displacement. Additionally, another 12% of banking jobs could be potentially augmented by AI.
“GPTs have the potential to transform entire economies, changing the way we live and work. They create new opportunities for growth and innovation, often improving our overall quality of life. They also destroy existing ways of doing things. And as such they also create losers. Especially in the short term,” the report stated.
Other high-risk sectors for job displacement include insurance (48%), energy (43%) and capital market (40%).
According to Citi, automation will play an increasing role in banking and finance and will be the catalyst for changes within the industry, impacting market share, employment and client experience.
“The pace of adoption and impact of Gen AI across industries has been astounding as it becomes clear that it has the potential to revolutionize the banking industry and improve profitability,” said David Griffiths, chief technology officer at Citi.
The financial firm estimates that the global banking sector’s profit pool could grow 9%—or $170 billion—from the adoption of AI, increasing from around $1.7 trillion to about $2 trillion.
How Citigroup Is Deploying AI
The convergence of financial services and technology continues to be a growing trend, as investment banks are increasingly using automation in their operations.
Bloomberg reported last year that Citi planned to rollout generative AI technology to its 40,000 developers.
The world’s biggest bank had already harnessed the power of automation to analyze an extensive set of new capital regulations, enabling it to meticulously examine 1,089 pages of these intricate rules.
Citi’s risk management and compliance team were then able evaluate the potential ramifications of the proposed regulatory changes.
During the bank’s digital money symposium on Thursday, CEO Jane Fraser outlined the banking giant’s strategic priorities regarding AI adoption. Fraser emphasized that its current focal point is on transitioning AI technologies from the research and development phase to practical implementation across various operational domains, stating, “Our focus now is to taking it from the lab to the factory floor.”
She highlighted two key areas where Citi aims to leverage AI capabilities. The bank is exploring the potential of AI to provide personalized investment recommendations tailored to the unique needs and preferences of its wealth management clients.
Additionally, the CEO underscored Citi’s commitment to bolstering its cybersecurity offerings through the integration of AI solutions.
AI Disruptions
Banks must proactively invest in AI adoption to adapt to the current technological shift happening in the job market.
Highly automatable positions within banking and finance include back-office functions, customer service, analysis, reporting and relationship managers. On the other hand, jobs requiring complex problem-solving, creativity, emotional intelligence and human interaction, such as sales, marketing and leadership, have less potential for full automation.
AI And Regulatory Compliance
AI adoption for compliance requires robust governance, including human oversight, ethical AI principles, data quality controls, model risk management and audit trails to ensure transparency and accountability in AI-driven decisions.
AI systems can continuously monitor transactions, communications and trading activities to detect potential violations, fraud, money laundering or other compliance risks in real-time. This allows for proactive risk mitigation.
Generative AI can rapidly analyze large volumes of data from multiple sources during client onboarding or periodic reviews to flag high-risk individuals or entities and satisfy know-your-customer and anti-money laundering requirements more efficiently.
Natural language processing can help automate the process of reviewing new regulations, analyzing their impact and ensuring adherence by scanning policies, procedures and controls.
Machine learning models can be used to test the effectiveness of compliance controls by simulating various scenarios and identifying gaps or weaknesses in the existing framework.
The technology can map an institution’s processes, data flows and controls against regulatory requirements to pinpoint areas of non-compliance that require remediation.
By analyzing historical data on compliance incidents, fines, and enforcement actions, AI can predict future compliance risks and allow firms to take preventive measures.
Newly Created Jobs And Reskilling
While AI could lead to significant job losses, it also has the potential to create new types of roles focused on developing, implementing and managing AI systems. Banks will likely need to hire specialists with AI and data science skills, as well as reskill existing employees to work alongside AI technologies.
In times of change, workers must stay up-to-date on the latest AI trends, tools and use cases impacting the banking industry.
To remain relevant, they should accumulate knowledge about the current capabilities and limitations of AI in banking applications like customer service, fraud detection and credit decisions. Provide feedback to improve AI-model performances based on real-world usage. Attend seminars, conferences and join professional AI communities to gain industry knowledge. Develop a growth mindset to adapt to the changing job landscape as AI continues to evolve.
By proactively reskilling, exploring new AI roles, understanding AI capabilities and committing to lifelong learning, banking professionals can future-proof their careers and increase their value as AI becomes more pervasive in the industry.