Artificial intelligence is significantly enhancing productivity at Deutsche Bank, enabling work that previously took years to now be completed within just a few months, according to a report by Reuters citing senior executives of the German lender.
The bank is leveraging AI tools to accelerate technology development and address accumulated internal work backlogs.
However, it is simultaneously keeping a close watch on rising computing and implementation costs associated with the technology.
Denis Roux, Chief Information Officer for the investment bank at Deutsche Bank, said that the improvements are already visible.
He noted that projects that earlier required around two years are now being delivered in three to six months, highlighting a substantial productivity boost. However, he did not disclose specific quantitative gains.
He further added that operational backlogs, which once took months to clear, are now being resolved in a matter of weeks.
Roux emphasised that the objective is to continue using AI tools to drive efficiency across operations.
Deutsche Bank’s technology workforce includes around 9,000 employees in India, which accounts for nearly 45% of its global tech talent base.
Global financial institutions are increasingly relying on Indian hubs not just for support roles but also for higher-value functions such as software development, financial engineering, and research and development.
At the same time, Roux highlighted that managing AI-related costs remains a priority. With AI providers moving toward usage-based pricing models, controlling expenses has become more complex.
He compared this challenge to the discipline firms had to adopt during the transition to cloud computing.
Companies like OpenAI and Anthropic are increasingly adopting token-based pricing, where users are charged based on consumption rather than fixed subscriptions.
At Deutsche Bank, engineers are assigned token usage limits and must justify additional requirements, with insights shared across teams.
Roux said the bank continuously tracks usage patterns to ensure productivity gains justify the cost.
While encouraging adoption, the bank aims to ensure a balance between efficiency and return on investment.
Deutsche Bank is also developing AI applications for automating financial data analysis and linking geopolitical or market events to portfolio risk exposure.
However, it remains cautious, using simpler models for routine tasks and evaluating traditional alternatives where appropriate.
