How AI is transforming financial services
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In today's digital landscape, banks are facing increasing regulatory demands and customer expectations regarding what they should provide. But disconnected data and systems are preventing financial services organisations from meeting those expectations.
AI offers a way for banks to manage their business end to end, across front, middle, and back offices. In fact, 84% of banks worldwide—including 274 in the UK—expect to increase their investment in AI throughout the next fiscal year, according to new banking research from ServiceNow.
AI is already transforming the financial services industry, giving bank workers the tools they need to meet—and exceed—customer expectations.
Table of contents
- What is AI in financial services?
- How can AI be used in financial services?
- The rise of agentic AI in financial services
- How AI is changing jobs in financial services
- How to use AI in financial services
- The financial AI maturity imperative
What is AI in financial services?
AI in financial services is the application of artificial intelligence technologies such as machine learning, natural language processing, and advanced analytics to transform raw financial data into actions that can lead to strategic business value.
Financial institutions that harness AI are doing much more than simply automating tasks. They're unlocking capabilities to predict market trends, personalise customer experiences, and make risk-informed decisions with remarkable speed and accuracy—ultimately increasing their bottom line.
Our research found that 8.4% of banks globally are already seeing a boost in gross margin from increased AI usage over the previous year.
How can AI be used in financial services?
Forward-thinking financial institutions are deploying AI across their entire value chain, creating seamless experiences that were unimaginable just a few years ago. Our research found that 57% of banks worldwide have rolled out 100 or more AI use cases across the enterprise, including:
Front office
- Customer behavior analysis: Transforming vast customer data sets into actionable insights that predict needs before they arise
- Hyper-personalisation: Delivering tailored financial recommendations that resonate with each customer's unique financial journey
- Dynamic pricing: Implementing demand-based pricing models that maximise value for both customers and institutions
Middle office
- Enhanced security: Deploying advanced cyber security systems that identify threats in real time so that you can stay ahead of sophisticated attacks
- Fraud prevention: Dramatically reducing false positives; HSBC, for example, cut fraud alert false positives by 60%, saving millions of dollars annually while strengthening customer trust
- Risk management: Processing complex risk factors instantaneously to safeguard assets and optimise portfolios
Back office
- Streamlined operations: Automating routine processes while enhancing accuracy and compliance
- IT infrastructure optimisation: Automatically predicting and resolving technology issues before they affect customer experience
- Financial reporting: Generating real-time financial insights that drive strategic decision-making
The rise of agentic AI in financial services
The most significant development transforming financial services is agentic AI—autonomous systems that can understand, reason, and act on behalf of a financial institution and its customers. Our research reveals that 22% of banks globally are already using agentic AI solutions and 41% are considering adopting agentic AI within a year.
Commonwealth Bank of Australia is using agentic AI to manage credit card payment disputes. Its solution processes natural language customer queries through a large language model (LLM). An AI agent then assesses and addresses issues in minutes rather than days—increasing customer satisfaction while reducing operational costs.
How AI is changing jobs in financial services
AI is taking over repetitive work, freeing humans to focus on higher-value activities that drive business outcomes. Examples include:
- Strategic advisors: Customer-facing roles are evolving from transaction processors to trusted financial advisors empowered by AI-driven insights.
- Risk innovators: Risk management professionals now focus on developing novel approaches to emerging challenges rather than conducting manual compliance checks.
- Digital experience designers: New roles center on creating seamless, intuitive digital journeys powered by AI.
- AI ethics specialists: These emerging positions are dedicated to helping to ensure responsible AI deployment that maintains customer trust.
Financial services organisations leading in AI prioritise training and upskilling. The vast majority have invested in talent development programs that prepare their workforce for an AI-powered future. More than half (56%) believe they have the right mix of talent and skills to carry out their AI strategy.
How to use AI in financial services
Organisations in our banking study that scored highest in AI maturity are called Pacesetters, including 18% of survey respondents in the UK. Based on the research findings, we developed a Pacesetter roadmap for financial institutions looking to maximise the transformative potential of AI:
- Embrace an innovation mindset: More than half (52%) of Pacesetters have launched AI innovation centers to stay at the forefront of innovation.
- Adopt a platform approach: Nearly two-thirds (63%) of Pacesetters prefer comprehensive, AI-powered platforms over point solutions. They understand that AI's true power comes from connecting previously siloed data and processes across the enterprise.
- Prioritise data governance: Pacesetters recognise that without clean, accessible data, even the most sophisticated AI models will underperform. Almost three-quarters (73%) of Pacesetters have implemented formal data governance and compliance programs.
- Build cross-functional AI teams: AI success requires getting leadership buy-in and cascading that down to staff. Nearly two-thirds (65%) of Pacesetters are operating with a clear, shared AI vision across the wider organisation.
- Start with high-impact use cases: Begin your AI journey with focused applications that deliver measurable value, then scale systematically across the organisation.
The financial AI maturity imperative
In financial services, the AI race is on. Financial institutions that have embraced AI are seeing margin growth of 10.9% from their AI investments—substantially outperforming the study average of 7.8%, according to our research.
These leaders are achieving 2.13 times greater efficiency and productivity from their AI initiatives compared to other organisations. In doing so, they’re creating a competitive gap that widens with each passing quarter.
The message is clear: Financial institutions that fail to harness AI risk falling behind. By building on a foundation of clean data, adopting a platform approach, and fostering an innovation culture, you can position your organisation at the forefront of the AI-powered future of finance—where unprecedented efficiency meets unparalleled customer experience.
Find out how ServiceNow can help you put AI to work for banking.