The rapid advancement of artificial intelligence (AI) technologies is poised to transform numerous industries and banking is at the forefront of this seismic shift. A new report by Citigroup has highlighted AI’s significant impact on the banking sector, predicting that AI technologies could displace more than 50% of banking jobs.
OpenAI’s ChatGPT reached one million users within five days of its launch in November 2022, underscoring the fast-paced adoption of AI in various sectors. This surge in AI usage has led to widespread speculation about its impact on the workforce. Citigroup’s report provides a sobering analysis, indicating that 54% of banking roles are at risk of being replaced by AI, while AI technologies could augment an additional 12%.
“GPTs have the potential to transform entire economies, changing how we live and work,” the report states. “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.”
Other sectors identified as high-risk for AI-led job displacement include insurance (48%), energy (43%), and capital markets (40%).
Citigroup emphasizes that automation will increasingly influence the banking and finance industry, affecting market share, employment, and client experience. Citi’s chief technology officer David Griffiths remarked, “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.”
Integrating AI into financial services is a growing trend, with major investment banks leveraging automation to streamline operations. Bloomberg reported last year that Citigroup planned to roll out generative AI technology to its 40,000 developers. The bank has already used AI to analyze new capital regulations, allowing for meticulously examining 1,089 pages of complex rules.
CEO Jane Fraser outlined the bank’s strategic priorities regarding AI adoption during Citigroup’s digital money symposium. She emphasized transitioning AI technologies from research and development to practical implementation, stating, “Our focus now is to take it from the lab to the factory floor.”
Fraser highlighted two key areas where Citi aims to leverage AI: providing personalized investment recommendations tailored to clients’ needs and enhancing cybersecurity offerings.
The banking industry must proactively invest in AI adoption to adapt to the ongoing technological shift. Positions that are highly automatable include back-office functions, customer service, analysis, reporting, and relationship management. Conversely, jobs that require complex problem-solving, creativity, emotional intelligence, and human interaction, such as sales, marketing, and leadership, have less potential for full automation.
Adopting AI for regulatory compliance requires robust governance, including human oversight, ethical AI principles, data quality controls, model risk management, and audit trails to ensure transparency and accountability. AI systems can monitor transactions, communications, and trading activities in real-time to detect potential violations, fraud, money laundering, or other compliance risks, allowing for proactive risk mitigation.
Generative AI can analyze large volumes of data during client onboarding or periodic reviews to flag high-risk individuals or entities, ensuring compliance with know-your-customer and anti-money laundering requirements. Natural language processing can automate the review of new regulations, analyze their impact, and ensure adherence by scanning policies, procedures, and controls.
Machine learning models can test the effectiveness of compliance controls by simulating various scenarios and identifying gaps or weaknesses. AI can map an institution’s processes, data flows, and controls against regulatory requirements to pinpoint non-compliance areas needing remediation. AI can predict future risks by analyzing historical compliance incidents, fines, and enforcement actions, enabling firms to take preventive measures.
While AI is expected to lead to significant job losses, it also holds the potential to create new roles focused on developing, implementing, and managing AI systems. Banks will likely need specialists with AI and data science skills and will need to reskill existing employees to work alongside AI technologies.
Banking professionals must stay updated on the latest AI trends, tools, and use cases to remain relevant. They should understand AI’s current capabilities and limitations in applications such as customer service, fraud detection, and credit decisions. Providing feedback to improve AI models based on real-world usage, attending seminars and conferences, and joining professional AI communities can help professionals gain industry knowledge.
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.
