Deutsche Bank partners with Publicis Sapient to further its GenAI agenda

2023 was the year of the digital dichotomy, where enterprises struggled to balance market headwinds with innovation aspirations. In 2024, preliminary HFS data suggests IT budgets are on the rise, led by emerging tech. Enterprises with long-term goals are pushing ahead with their cloud, data, and artificial intelligence (AI) agenda and making new partnerships with service providers. Deutsche Bank recently partnered with Publicis Sapient to help with its ambitious journey to digitally transform and accelerate the adoption of generative AI (GenAI). This partnership will see Deutsche Bank develop its AI agenda with the goal of driving new business models to boost revenues—and it’s a model other traditional banks should follow.

HFS recently caught up with Gil Perez, Deutsche Bank’s Chief Innovation Officer, and Sean O’Donnell, Publicis Sapient’s CTO for Financial Services International, to discuss how AI can drive real value. Here is the link to the videocast.

Exhibit 1: HFS, Deutsche Bank, and Publicis Sapient hype-bust GenAI in financial services

Deutsche Bank’s digital business transformation move aims to reduce the cost-to-income ratio

Deutsche Bank has been transforming its digital business for several years. It forged several multi-year innovation partnerships with technology companies and fintechs. It successfully laid the foundation for migrating to a hybrid cloud, which will help it speed up processes and break down data silos across the bank. The data lake and service mesh spanning front, middle, and back offices and geographies will further enhance its ability to leverage analytics, automation, and AI while ensuring these comply with regulations. Deutsche Bank is making these investments to improve its return on equity and reduce its cost-to-income ratio (CIR) to under 62.5% by the end of 2025. The World Bank pegs the average CIR for all banks across 40 developing countries at about 60%.

However, 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 by implementing operational efficiencies or reinventing them with the latest tech developments.

Deutsche Bank has taken a long-term view, focusing on creating the foundational building blocks for successfully implementing GenAI

Deutsche Bank realizes the power of co-innovating and collaborating with partners. The recent partnership with Publicis Sapient is all about solving the next wave of business problems by building out the core AI/ML platform.

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. In the next two years, it will scale these new solutions across all arms of the bank—investment, corporate, private and retail, and asset management—to generate cost savings and discover new income streams.

Gil Perez, CIO at Deutsche Bank, shared with HFS the secret sauce of creating highly functional models beyond building a great engine. He shared,

People undervalue and underestimate the interaction and knowledge of their company and employees. Organizations should, from day one, consider prompts that are unique to their company and how they capture, analyze, and harvest them. It’s a big mindset change for corporations because they need to think differently. All those interactions and the body of work will, in essence, be the key to their success in the future.

—Gil Perez, Chief Innovation Officer at Deutsche Bank

Publicis Sapient has helped build a comprehensive artificial intelligence and machine learning (AIML) product catalog for Deutsche Bank that includes the following capabilities:

• Building, scaling, and maintaining AIML infrastructure: Experimenting with data labs and on-premises infrastructure, developing containerized hybrid and private cloud platforms.
• Preparing an executable plan for data-assisted and automated data quality checks: Pre-processing, exploring, profiling, and labeling data, then ensuring data privacy engineering and building analytical data sets.
• Developing large language models (LLMs) and preparing them for production: Evaluating, developing, advising, and fine-tuning LLMs, plus on-premises and cloud model support and monitoring for LLMs.
• Creating an AI framework: Creating a responsible framework for AI governance, safeguarding advisory, and trustworthiness.
• Building core solutions: Building solutions using data science, natural language processing, entity extraction, recognition, and matching and using dark data.

However, Gil cautions banking institutions to use this powerful tool responsibly and ethically across the industry to ensure transparency and trust in the technology. He explained, “It is the banking sector’s responsibility to take the lead on responsible AI, trustworthy AI, and a lot of the other capabilities around the fair usage of AI.”

GenAI could transform portions of financial services, including software development, chatbots, and anti-money laundering

Publicis Sapient and Deutsche Bank have identified various use cases that would benefit from the latest developments in AI. Three GenAI use cases are delivering value to Deutsche Bank:

• Augmenting software code development with AI, including enhancing the documentation process and understanding old code
• Creating chatbots that work as advisers and assistants to accelerate output, helping transcribe, translate, summarize, generate research and insights, and automate reports from various sources
• Applying GenAI in anti-money laundering and regulatory compliance, such as 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 the fast-changing environment.

Regarding its impact on employees, Gil said that GenAI will not replace jobs, but it may make certain tasks less relevant, requiring employees to continuously learn and adapt to new roles and responsibilities.

Sean O’Donnell made an interesting point about repurposing the effort and redistributing those higher-value and higher-order activities to benefit the customer. He also explained that “there are efficiencies that are gained. And invariably, if you don’t pass them on to a customer, another organization is going to sweep up that market and that space and that kind of spread of profit and do it for you.”

The Bottom Line: Adopting GenAI is a matter of when, not if. Follow Deutsche Bank’s lead with foundational investments in cloud and data to move beyond GenAI hype to GenAI value.

Deutsche Bank made critical foundational investments in cloud and data to ready itself for innovation, including GenAI. For its recent AI/ML move to bear fruit, it considered the role of people: customers, leadership, employees, culture, and change management. Most importantly, it plans to realize value on both sides of the cost-to-income ratio.