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HSBC is using artificial intelligence in customer advice, financial-crime controls and employee support while moving more experiments into production. Its quantum-computing work is narrower but measurable: on 25 September 2025, HSBC and IBM reported up to a 34% improvement in predicting whether European corporate-bond inquiries would be filled, using a hybrid quantum-classical workflow on production-scale data.
That result is a real HSBC-reported test of one trading prediction task—not proof that quantum computers outperform classical systems across finance. HSBC is also testing quantum-secure communications and developing its technology through partnerships with Google, IBM, Mistral AI, BT, Toshiba, AWS and academic institutions.
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How HSBC is using AI
Personalised wealth advice
HSBC lists personalised wealth advice as an early business priority for generative and predictive AI. The objective is to give customers more relevant guidance in real time and at scale, while advisers remain responsible for judgement and recommendations.
Financial-crime risk management
AI is being applied to financial-crime risk management, including the analysis and prioritisation of activity that may require investigation. HSBC presents these systems as decision support for trained teams, not as an autonomous replacement for compliance controls.
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Support for frontline employees
Another priority is AI assistance for frontline teams. Internal tools can help staff find information and handle routine work more quickly, leaving employees to deal with situations that require context, discretion or customer conversation.
Human oversight is part of the design
HSBC’s published AI principles emphasise ethical and responsible use. Human judgement, decision-making and accountability remain in the process. Group Chief Executive Georges Elhedery described the aim as delivering personalised experiences while keeping “human judgement, decision-making and accountability at the core.”
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What HSBC’s Google Cloud programme is expected to deliver
In 2026, HSBC said its Google Cloud programme had more than 200 additional AI use cases planned over two years, with an estimated benefit value above $100 million. These are programme expectations, not audited savings already realised. The announcement signals a shift from isolated proofs of concept toward a portfolio of deployments across the bank.
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| Reported measure | What it means | Evidence status |
|---|---|---|
| More than 200 additional AI use cases | Use cases planned over a two-year period under HSBC’s Google Cloud programme | Forward-looking HSBC estimate from 2026 |
| Above $100 million in estimated benefit value | Expected value associated with the planned use-case portfolio | Forward-looking HSBC estimate, not reported realised profit |
| Initial priorities | Wealth advice, financial-crime risk management and frontline support | Stated business focus |
What HSBC actually achieved with quantum computing
The corporate-bond prediction trial
On 25 September 2025, HSBC and IBM reported a hybrid quantum-classical workflow for predicting whether inquiries about European corporate bonds would be filled. The test used real, production-scale data and reported an improvement of up to 34% in prediction performance.
Philip Intallura, HSBC’s Group Head of Quantum Technologies, summarised the result as “up to 34% improvement in predicting whether an order will be fulfilled.” HSBC called it a “ground-breaking world-first in bond trading.”
Why the workflow was hybrid
The calculation combined conventional computing with quantum processing rather than handing the entire trading system to a quantum computer. Classical systems handled parts of the data and workflow, while the quantum component was used for a specific modelling task. This approach reflects the current state of quantum finance: targeted experiments integrated with established infrastructure.
Is the 34% result real?
It is a result HSBC reported for a defined European corporate-bond inquiry task, using production-scale data. The figure should be read with those qualifications attached. The available evidence does not establish that quantum computers broadly beat classical systems in every financial application, nor does it provide an independent comparative benchmark across other banks or datasets.
HSBC’s own quantum-finance positioning—that it is among the top two global leaders—is a company claim. The bank’s quantum chief has acknowledged the exploratory nature of the work: “We’re trying to forge a path that there is no blueprint for.”
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HSBC’s quantum-security work
Quantum-key-distribution trial
In December 2023, HSBC ran a quantum-key-distribution (QKD) trial to protect a €30 million euro-to-dollar foreign-exchange scenario on its AI Markets terminal. The trial used technology from BT, Toshiba and AWS.
QKD is a communications-security technique designed to reveal interception attempts during the exchange of encryption keys. In HSBC’s test, the technology protected a specific FX transaction scenario; it was not a claim that all of the bank’s communications had been converted to QKD.
Why security is separate from quantum trading
The bond-prediction project used quantum computation to address a modelling problem. The QKD project used quantum effects for secure key exchange. Both are called “quantum” initiatives, but they solve different problems and have different evidence: one measured a trading-prediction improvement, while the other demonstrated protection of a defined transaction scenario.
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| Partner or institution | Documented connection | Area |
|---|---|---|
| Google Cloud | Cloud programme supporting more than 200 planned AI use cases | Enterprise AI deployment |
| Google DeepMind | Named in HSBC’s AI partnership work | AI research and capabilities |
| Mistral AI | Named as an AI partner | Generative-AI ecosystem |
| IBM | Co-developed and reported the 2025 hybrid quantum-classical bond-prediction workflow | Quantum computing and trading analytics |
| BT and Toshiba | Provided technology used in the December 2023 QKD trial | Quantum-secure communications |
| AWS | Technology provider in the QKD trial | Quantum-security infrastructure |
| Fudan University and HKUST | Academic links covering generative AI, large language models, quantum computing, fraud detection and talent development | Research and skills |
| MAS-related initiatives | Public-sector collaborations involving AI, fraud detection, quantum computing and talent development | Industry coordination and research |
How mature are the initiatives?
| Initiative | Business problem | Computing model | Evidence and maturity |
|---|---|---|---|
| Wealth advice, crime risk and frontline assistance | Customer personalisation, compliance analysis and employee productivity | Classical AI and generative AI | Deployment priorities; HSBC is scaling a broader portfolio |
| Google Cloud use-case programme | Multiple banking processes | Cloud-based AI | More than 200 use cases and above $100 million estimated benefit, both forward-looking |
| European corporate-bond inquiry prediction | Predicting whether an inquiry will be filled | Hybrid quantum-classical | HSBC and IBM reported up to 34% improvement on production-scale data in September 2025 |
| FX QKD trial | Protecting a €30 million euro-to-dollar scenario | Quantum key distribution | Trial conducted in December 2023 |
What customers and investors should take from this
HSBC’s AI story is primarily about scaling practical automation and decision support under human governance. The quantum story is more experimental: one narrowly defined trading result and one security demonstration show potential, but neither establishes a general-purpose quantum advantage or a consumer product.
The clearest near-term impact is likely to come from conventional AI deployed across many banking processes. Quantum computing remains a research and engineering programme aimed at finding tasks where a hybrid approach can produce a useful advantage, while quantum-security trials prepare the bank for future communications threats.
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