×
AI boosts bank productivity but monetization remains challenging
Written by
Published on
Join our daily newsletter for breaking news, product launches and deals, research breakdowns, and other industry-leading AI coverage
Join Now

The financial services industry is rapidly adopting artificial intelligence technologies, though the path to monetization remains unclear despite significant productivity improvements.

Current state of AI adoption: Major financial institutions are implementing AI across multiple business functions, with a primary focus on operational efficiency and internal processes.

  • Goldman Sachs reports potential coding productivity improvements of 20-30% among their 11,000 engineers through AI implementation
  • BNY Mellon has democratized AI access, enabling thousands of employees to build and deploy AI agents for daily tasks
  • Banks are successfully using AI for virtual client assistants and supporting functions in human resources, risk management, compliance, and finance

Productivity gains vs revenue generation: While AI is delivering measurable efficiency improvements, financial institutions are still struggling to translate these advances into direct revenue growth.

  • Equity research teams have seen report production time cut from over 4 hours to less than 1 hour per day
  • BMO Financial Group’s Chief AI Officer Kristin Milchanowski acknowledges that revenue-generating AI applications remain elusive
  • The technology has proven most valuable in streamlining internal operations and reducing time-intensive manual tasks

Implementation challenges: Financial institutions are navigating the complexities of integrating AI while managing expectations and identifying practical applications.

  • Banks are actively seeking specific use cases that can demonstrate clear return on investment
  • Future applications being explored include trade optimization and client generation systems
  • The initial enthusiasm around AI’s potential impact on revenue and cost reduction has been tempered by implementation realities

Looking ahead: The banking sector’s experience with AI highlights the gap between technological potential and practical business application, suggesting that monetization strategies may require longer-term perspective and more targeted approaches.

AI a productivity boost to banks but making money from it is a challenge

Recent News

How the rise of small AI models is redefining the AI race

Purpose-built, smaller AI models deliver similar results to their larger counterparts while using a fraction of the computing power and cost.

London Book Fair to focus on AI integration and declining literacy rates

Publishing industry convenes to address AI integration and youth readership challenges amid strong international rights trading.

AI takes center stage at HPA Tech Retreat as entertainment execs ponder future of industry

Studios race to buy AI companies and integrate machine learning into film production, despite concerns over creative control and job security.