PUBLISHED DATE: 2026-09-21 01:01:52
Deutsche Banks Gen AI and Digital Transformation | Publicis Sapient
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Deutsche Bank Lays the Foundation to Scale AI Across the Enterprise
How Deutsche Bank created the AI infrastructure, governance and use cases needed to move AI into production.
Summary
Deutsche Bank built an enterprise AI/ML foundation designed to scale AI across the bank and support new sources of efficiency and growth.
- 3 AI use cases delivering value
- 5 AI/ML capability areas
- 5 businesses targeted for scale
Summary
Client Deutsche Bank
Industry Financial Services
Topic AI & Intelligence
Partner HFS
In this customer story
Intro
The Problem
The Solution
The Impact
Intro
Deutsche Bank has been transforming its digital business for several years, forging multi-year innovation partnerships with technology companies and fintechs and laying the foundation for migrating to a hybrid cloud. The bank’s partnership with Publicis Sapient is focused on enterprise AI transformation and solving the next wave of business problems by building out the bank’s core AI/ML platform.
The Problem
Deutsche Bank is making investments to improve its return on equity and reduce its cost-to-income ratio. But reducing costs shouldn’t be the only aim of any transformation plan. The roadmap should consider both sides of the cost-to-income ratio—increasing revenues by conceptualizing new business models in conjunction with lowering costs through operational efficiencies. The bank has taken a long-term view, focusing on creating the foundational building blocks for successfully implementing AI across the enterprise.
The Solution
In 2023, Publicis Sapient built and proofed an AI platform and infrastructure along with use cases, proofs of concept, operating models, and adoption and communication plans. The goal was to scale these new solutions across the bank’s investment, corporate, private and retail, and asset management businesses.
Publicis Sapient also helped build a comprehensive artificial intelligence and machine learning product catalog that includes:
- Building, scaling and maintaining AIML infrastructure, including data labs, on-premises infrastructure and containerized hybrid and private cloud platforms
- Preparing data-assisted and automated data quality checks, including pre-processing, profiling, labeling, data privacy engineering and analytical data sets
- Developing large language models and preparing them for production, including evaluation, development, fine-tuning, model support and monitoring
- Creating an AI framework for governance, safeguarding and trustworthiness
- Building core solutions using data science, natural language processing, entity extraction, recognition and matching
The Impact
Publicis Sapient and Deutsche Bank identified three AI use cases that are delivering value to the bank:
- Augmenting software code development with AI, including enhancing documentation and understanding old code
- Creating chatbots that work as advisers and assistants, helping transcribe, translate, summarize, generate research and insights, and automate reports
- Applying AI in anti-money laundering and regulatory compliance, including detecting market abuse or suspicious activity using automated transcriptions of conversations
By developing its infrastructure and range of applications, Deutsche Bank will be able to enhance customer service, boost efficiency and employee productivity, manage risk, accelerate the speed of bringing new products to market and improve its ability to react to a fast-changing environment.
Download the full HFA Research case study for more on Deutsche Bank’s AI strategy, foundational investments and approach to responsible AI.
Meet our authors
Sean O'Donnell
GVP & Chief Technology Officer for FS International
Jan-Willem Weggemans
VP/Executive Client Partner Cloud, Data and AI & Alliances Lead
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