Deutsche Bank is developing a gen AI product to drive efficiency and customer satisfaction in its private bank.

A gen AI assistant will offer private banking customers suggestions about managing their investments like comparable clients along with making suggestions to help them better manage risk, according to the $1.6 trillion bank. 

Deutsche Bank is taking its “first steps in releasing a client-facing gen AI tool in our private bank to assist customers, 24/7, with common questions and topics,” a Deutsche Bank spokesperson told Bank Automation News. They did not disclose who the bank is working with to develop the tool. 

The Frankfurt, Germany-based bank last month reported net revenue from private banking at 9.1 billion euros ($9.6 billion) for the fourth quarter, up 2% year over year, with assets under management of $49 billion, up 10% YoY. 

Deutsche Bank reported noninterest expense of $6.4 billion, up 13% YoY during Q4 on the heels of continued tech expense, according to its earnings report. 

‘Focus on scaling’ gen AI 

Banks will look to implement gen AI this year for uses they have been incubating since 2023, Kevin Levitt, who leads global business development for the financial services industry at Nvidia, told BAN. 

“There’s a big movement to focus on scaling AI in production across financial enterprises,” Levitt said. Banks build many models and roll out gen AI for use cases with the best return on investment, he added. 

As the cost of gen AI falls with innovations like DeepSeek’s cheap gen AI model, adoption of the technology will also increase, Luke Penca, executive director at consultancy Capco Institute, told BAN. 

Gen AI is also being deployed by: 

• Ally Financial for code development; 

• BNY to streamline treasury management and provide hyperpersonalization to clients; 

• Goldman Sachs with an internal chatbot assistant; and 

• Payments giants Mastercard and Visa to fight fraud. 

Deutsche Bank is also looking to scale its existing live use cases of gen AI, the spokesperson told BAN, including:  

• An internal chatbot to help create research materials for clients,  

• Document processing to scan and extract information from paper documents; and 

• Automated software code development to support the productivity of its developers 

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