Technology Transformation

Redefining banking through intelligent and effective technology

Technology Transformation

Technology continues to disrupt and shape financial services. Processes are quicker, insights are sharper and new ideas are formed. At Deutsche Bank, we have focused on three major pillars as part of our technology strategy: Cloud, AI and Talent. The three factors are closely linked and underpinned by the vast amounts of data that flow through the bank every day.

Cloud

Moving to the cloud is the foundation of the bank’s technology transformation. It provides benefits across various dimensions:

Scalability: Capability to scale elastically, delivering the right amount of IT resources when it is needed, at the right geographic location.
Reduced maintenance effort: Cloud providers manage all administrative tasks (e.g. patching of servers) and deliver an up-to-date, fully compliant environment including back-ups, replication, and disaster recovery.
Cost effectiveness: Flexible price structures – you pay for what you use.
Developer productivity: Public cloud provides pre-engineered, standardised services ready for consumption e.g. for compute, database and application hosting. Automation and self-service are built in by default.

Strategic and business-critical applications now benefitting from the cloud

We have made good progress in our cloud transformation and are seeing clear business benefits. Several of our strategic and business-critical applications are now running in the cloud.

One example is the migration of our SAP S4/HANA finance platforms to Google Cloud – one of the most complex migrations in financial history

Involved the migration of 17 financial reporting systems, including the bank's strategic general ledger, planning, and forecasting systems
Benefits include data processing improvements of up to 50%, and a reduced recovery time by a factor 16-20.

In collaboration with Google Cloud, we have also developed solutions that allow classic on-premise applications, such as our Autobahn FX electronic trading platform, to benefit from a hybrid-cloud solution. Read more about in this blog post.

Cloud sets the stage for generative AI at Deutsche Bank

The cloud delivers scalable computing resources essential for sophisticated AI models and experimentation with the latest AI/ML tools. Our partnership with Google Cloud gives us access to the latest AI capabilities and we can directly access AI models integrated into the cloud-platform.

Read more about how our cloud journey and how it has set the stage for gen AI at Deutsche Bank in this blog post by our Chief Technology, Data and Innovation Officer.

Artificial Intelligence

The rise of AI, especially Generative AI, is a key technology trend transforming financial services. It promises greater efficiency, deeper data insights, and enhanced/new products for clients. Deutsche Bank embraces AI's transformative power and is committed to its widespread adoption across almost all aspects of its business operations in the future – from internal processes to interaction with customers.

Our focus and approach

The bank’s Technology, Data and Innovation (TDI) division has been running a central programme to lay the foundation for safe and value-generating adoption and scaling. This includes the definition of technical and operational standards, guardrails, as well as the creation of an AI platform with scalable shared services – to offer all areas across the bank the same opportunities across common use cases and prevent different areas implementing similar solutions.

On that foundation, the bank’s business and infrastructure divisions are driving the integration, development and implementation of specific AI use case in their respective areas – in close partnership with the respective TDI CIO teams. Multiple AI use cases are already in production and a robust pipeline of initiatives in experimentation or development.

We build on strong partnerships and make targeted investments

We are building on our strong technology partnerships. Working with Google Cloud gives us access to the latest AI capabilities and we can directly access AI models integrated into the cloud-platform.

We place great emphasis on remaining independent from individual providers or models and work with numerous technology partners and are also making targeted investments in this sector. For example, end of 2024 we took an equity stake in Aleph Alpha, Germany’s largest start-up in AI.

Our commitment to Responsible AI

The use of artificial intelligence in the financial industry requires special care. We must ensure that we use its enormous potential responsibly, safely and prudently. The bank’s Artificial Intelligence & Data Ethics Principles are designed to guide responsible innovation with AI.

Principle	Description
Security, Safety & Technical Robustness	Design, build, and manage AI solutions with a robust approach to avoid potential risks and issues around safety and abuse. Additionally, proactively prevent Information Security risks and threats, having corrective measures in place.
Privacy	To protect the interests, rights and freedoms of natural persons in relation to processing of their personal data, by: a. complying with applicable data protection laws, and b. implementing appropriate technical and organisational measures to protect the fundamental rights of the individuals.
Accountability	Establish clear accountability and ownership for AI solutions at all points in the lifecycle.
Fairness & Bias	Strive to make AI solutions fair to ensure groups or individuals are not unnecessarily deprived of the benefits or opportunities provided by the service. This includes the intention to innovate responsibly and inclusively and to consider accessibility. Strive to avoid unintended bias in our AI solutions.
Education & Training	Build awareness of appropriate AI use across the organisation and ensure that practitioners have the appropriate qualifications and access to continuous training.
Alignment	Use of data in, and design of, AI solutions is aligned at all times with Deutsche Bank’s values, code of conduct, and applicable policies.
Transparency & Explainability	Strive to achieve an appropriate level of transparency and Explainability of AI Models and workflows.
Human Oversight & Monitoring	Be committed to engraining an appropriate level of human oversight in all lifecycle stages, from initial conception to design, build and operation. Deem it good practice to implement automated monitoring of the AI decision-making to ensure alignment.

AI talent and learning

Our AI talent and learning resources cater to all levels—from beginners to advanced users. Over 11,000 colleagues across the bank have already completed our AI Foundations training course which is ideal for anyone looking to understand the basics and apply GenAI in business, with no technical background required. Additional training is available for business leaders and technical practitioners.

Talent

Digital skills will continue to be essential as organizations transform and integrate technologies like artificial intelligence. To keep pace, we are developing our in-house technology expertise by offering interesting career paths and learning opportunities.

Our Technology, Data & Innovation (TDI) function requires a balance of technical expertise, client-focus and collaboration across global teams. In particular, we are building highly skilled teams in Technology hubs across the world in key global centres such as Berlin and Cary. We are building key capabilities in partnership with major technology companies, for example cloud skills in collaboration with Google Cloud.

We also continue to support the careers of our Women in Technology via dedicated training initiatives, networking platforms and showcasing of employees that are making a difference in driving greater gender balance.

Explore our careers site.

Artificial intelligence in action

Selected artificial intelligence use cases that are driving greater efficiency, providing deeper data insights, ensuring enhanced security and augmenting our service to clients.

dbLumina digital assistant

dbLumina is a Generative AI-powered assistant, designed to streamline repetitive analytical tasks. It offers a conversational interface that can be used for brainstorming, analysing and generating content. Through simple prompts, users can extract insights from complex documents like market data and regulatory filings and use pre-defined templates for recurring tasks. Each response from dbLumina includes clickable citations for easy fact-checking.

It is currently deployed as a shared service for nearly 5,000 employees across Deutsche Bank Research, FIC and Origination & Advisory teams. Further rollouts are planned in the coming months for more users in the bank’s business divisions and infrastructure functions.
Paula chatbot

Paula is a secure, generative AI-powered chatbot integrated into the Postbank Mobile Banking App. Powered by a large language model (LLM), Paula understands and responds to user queries with high accuracy. It can be used round-the-clock, to handle general service requests, reducing the need for emails and calls.

To protect sensitive data, the chatbot anonymises personal information and blocks inappropriate content, ensuring a safe and efficient user experience. Currently in phased rollout Paula is expected to achieve a 25% call deflection rate by independently handling common queries and basic banking tasks. Future enhancements include expanding to more app areas, integrating with personal finance tools, and continuously improving performance based on user feedback.
Software coding assistants

Software coding assistants such as Google Gemini Code Assist and GitHub Copilot are used by over 6,000 developers to enhance productivity. These tools contribute to code generation and are especially useful for repetitive tasks, refactoring, test generation, and script writing, helping developers save 1.5 to 2.5 hours weekly. They also support learning by aiding navigation through unfamiliar codebases and legacy systems.

In keeping with the bank’s emphasis on responsible AI usage, developers remain accountable for all committed code. Engineers undergo mandatory refresher training on the safe use of AI prior to using these assistants.
Voice Surveillance

Voice Surveillance, a compliance technology initiative, leverages Google Speech-to-Text to convert voice communications into text, significantly enhancing the detection of market misconduct. By expanding its lexicon coverage by ~10x, the system now captures a broader spectrum of risk indicators. This transformation has enabled the decommissioning of legacy phonetic surveillance solutions, resulting in a 65% cost reduction.

The enhanced system reduces false positives, allowing surveillance teams to focus on genuine risks rather than investigating benign alerts. By freeing up time and resources, the bank can prioritize client engagement and regulatory integrity, reinforcing trust and operational excellence.