Global banks are rapidly deploying generative AI, navigating ethical risks, hallucinations, and new regulations to drive trusted innovation.
· Leading banks like JPMorgan, UBS, HSBC, and DBS are actively rolling out generative AI across customer service, trading, fraud detection, and more.
· This rapid launch of AI tools comes with real hurdles: bias, factual errors, data privacy, and stricter oversight under new regulations globally.
· What banks are doing, challenges faced, and how collaboration with regulators speeds up innovation without risking trust.
When people think of AI in banking, they often imagine futuristic technology, but as of mid-2025, global banks are already heavily deploying generative AI — the same tech behind chatbots and automated content to transform everyday operations.
Institutions like JP Morgan, HSBC, UBS and DBS are already using AI for everything from smarter customer service to faster fraud detection and advanced trading. AI is no longer in pilot mode; it is being rolled out at enterprise scale. However, even as banks embrace AI innovation, they must also manage security concerns around hallucinations and privacy.
AI leaders in banking deployment
JP Morgan Chase is known for its internal generative AI tool, EVEE, a question-answering system that helps support staff respond quickly client queries. The bank is also exploring AI for fraud detection and payment optimisation. Its strategy focuses on internal deployment first, followed by external applications with strong governance.UBS is leveraging AI for staff productivity, aiming to automate research and client inquiry resolution. It is also using AI to analyse market trends and support investment insights, viewing AI as a key competitive enabler for its global client base. HSBC is using long-standing ethical AI principles to guide its usage. It uses AI for financial crime detection and internal market analysis tools. To reinforce responsible usage, HSBC publishes regular transparency reports outlining its AI deployment framework.
DBS Bank has deployed more than 1,500 AI models across 370 use cases, as of May 2025. These include its CSO Assistant, which reduces call times and improves response accuracy. DBS also uses AI for content generation, employee code support and other enterprise solutions.
Major challenges
AI can replicate historical discrimination, prompting regulators to mandate audits and fairness checks. Banks are mitigating this by using broader datasets and conducting periodic model reviews.
Generative AI may also invent incorrect but plausible outputs, a serious concern in banking, where a wrong credit decision or misread financial data can erode trust.
Banks are processing sensitive financial information through AI models, raising concerns about data leakage and cybersecurity threats.
The US currently lacks unified AI legislation, but states like New York have begun implementing stringent oversight.
Regulatory shifts
Regulatory goal Implication Examples (as of July 2025)
Risk-based
regulation More oversight for high-risk AI systems EU’s high-risk list, US credit/insurance rules, APAC guidance
Transparency &
explainable AI AI must explain its decisions EU demands XAI; UK talks about sandbox disclosure rules
Accountability &
governance Banks must show who’s responsible for AI outcomes FCA’s individual accountability rules
Data quality &
governance Training data must be high-quality and unbiased Annual audits, using fresh, diverse datasets
Human-in-the-
loop
requirements Humans must validate key AI decisions Mandatory checks in credit scoring, compliance
AI is no longer a distant future, it’s embedded in banking operations today, from JP Morgan’s EVEE to HSBC's ethical AI framework. The challenge now is not just about using AI, it's about using it responsibly, under intensifying regulatory pressure.
Success will hinge on how well regulators, banks and technologists work together to build trustworthy, secure and inclusive systems. The next few years will be critical in shaping how AI in banking evolves, with trust and transparency at its core. To understand how AI in finance is shaping customer trust and global markets, visit BankQuality today.