A newly announced, multi-year partnership between HSBC and Google Cloud will enable the financial institution to work with engineering teams from Google Cloud and DeepMind to develop new AI-powered tools and capabilities. The partnership will allow HSBC to benefit from access to Google’s latest agentic AI capabilities including Gemini and the Gemini Enterprise Agent Platform.
The agreement will enable more than 200 new AI use cases for HSBC over the next two years, with a focus on the highest value initiatives for investment and delivery. HSBC estimates each of these could return more than $100 million in either direct revenue gains or broader efficiency improvements.
“AI is becoming one of the defining technologies of our time, allowing us to create a personalized experience for each customer, delivered in real time and at scale, while keeping human judgment, decision-making, and accountability at the core,” HSBC Group CEO Georges Elhedery said. “A partnership like this one with Google Cloud helps us empower our colleagues with the tools they need to be future-ready, and supports our work in building a simple, agile, faster, and more personal HSBC.”
These new opportunities fall into three main categories: wealth management, fraud and financial crime, and support for frontline/relationship manager client service. Here is a closer look at each element of the new partnership and its implications for AI in banking and financial services.
Hyper-personalized wealth management
The partnership will enable HSBC to combine smarter, AI-driven insights with the expertise of relationship managers. This will transform the way the bank serves its wealth management clients and empower thousands of relationship managers to provide proactive, customized financial support and real-time advice to customers at every stage of the client journey.
What this says about AI: The ability to achieve hyper-personalization is increasingly regarded as the Holy Grail of customer engagement. AI enables banks and other financial institutions to leverage their data to better understand the unique needs of individual customers, businesses, and enterprises. This allows them to not only develop customized solutions and services that directly respond to each client, but also to respond quickly to shifting preferences and even anticipate emerging trends and circumstances that customers might not immediately recognize.
What this says about banks: More and more banks are realizing the opportunities in delivering wealth management services. This is driven by a number of factors, from the so-called Great Wealth Transfer and the growing number of high-net-worth households to the democratization of wealth management brought about by fintechs and robo-advisors.
Wealth management is also an area where more banks and financial institutions can provide greater value, especially for mid-tier and non-HNW customers for whom bespoke, concierge-level wealth management services are typically out of reach. AI plays a key role here, helping translate client data—from financial records to conversations with advisors—into actionable insights that lead to better and more accurate financial guidance. The fact that AI is able to provide this at a competitive cost means that these higher-value, higher-margin services can be offered to a wider range of customers.
Stronger financial crime risk management
HSBC will leverage its relationship with Google Cloud to deploy both generative and agentic AI to build a financial crime architecture that identifies fraud risk as early as possible. The bank’s goal is to detect and intervene twice as quickly once risk is detected across the nearly one billion transactions monitored by the bank every month for financial crime and fraud.
What this says about AI: Helping financial institutions detect fraud faster, including real-time monitoring, is one of the most broadly accepted use cases for AI technology. AI is able to analyze vast amounts of data in real time to detect suspicious patterns and activities that traditional, rules-based systems can miss, while also providing predictive analytics that can enable institutions to anticipate potential financial crime risks before they materialize.
What this says about banks: For banks and other financial institutions, financial crime risks have only grown larger in recent years. The Nasdaq Verafin 2026 Global Financial Crime report indicated that the economic impact of financial crime internationally has grown by $1.3 trillion in the past two years from 2023 to 2025. With regard to fraud-specific losses, fraud scams were the fastest-growing category costing $62 billion in 2025 alone. In the face of this, moves like HSBC’s to embrace AI-powered solutions for fighting fraud have become increasingly common. The 2026 Global Financial Crime report noted that 75% of financial institutions said they planned to boost their use of AI for financial crime detection.
Enhanced client service for frontline and relationship managers
Courtesy of the partnership, HSBC’s frontline staff and relationship managers will have expanded access to an AI-powered decision assistant that has already proven capable of reducing administrative and client meeting prep times from hours to minutes for thousands of users. HSBC will also codify regulatory procedures into an AI structure to give bankers consistently structured options and analysis to enhance decision-making and provide faster insights without losing human judgment and oversight.
What this says about AI: One of the great promises of automation and AI is freeing human labor and talent from mundane, often tedious, and inefficient manual processes. The fact that so much of AI innovation is being designed for in-house use by frontline workers and employees to enable them to better serve their clients underscores that AI, in its best light, actually creates space for more human connections between customers and service providers.
What this says about banks: Empowering frontline workers and relationship managers with AI-powered tools is helping a growing number of banks boost efficiency and reduce costs. From enhancing underwriting analysis to streamlining workflows, financial institutions are increasingly comfortable with AI-powered tools. This is especially the case when institutions deploy these solutions as complements to existing systems rather than as replacements for them.
Photo by Kit Suman on Unsplash
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David Penn
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