AI will account for 45% of all technology spending by digital banks by 2027, up from 22% in 2024, according to Gartner’s latest banking technology forecast. The projection reflects a consensus among banking executives that AI is not a feature to be added to digital banking — it is the architecture on which the next generation of banking platforms will be built. The banks that invest early and deeply in AI capabilities will define what banking looks like for the 3.6 billion digital banking customers expected by 2028.
How AI Is Reshaping Core Banking Functions
Digital banks have already deployed AI across customer-facing functions: chatbots handle routine inquiries, recommendation engines suggest relevant products, and personalisation algorithms adjust the user experience based on individual behaviour. The next phase of AI integration targets core banking functions that have historically required manual oversight: credit decisioning, treasury management, regulatory reporting, and capital allocation.
According to McKinsey, digital banks that automate credit decisioning with AI models approve loans 80% faster and with 22% lower default rates than those using traditional underwriting. The speed advantage is particularly relevant for digital banking platforms competing on customer experience — a borrower who receives an instant approval is unlikely to wait three days for a competing offer from a traditional bank.
Treasury management is the next frontier. AI systems that predict cash flow patterns, optimise liquidity positions, and manage interest rate exposure in real time can improve net interest margins by 15-25 basis points, according to Oliver Wyman. For digital banks managing billions in deposits, those basis points translate into tens of millions in additional annual revenue.
Generative AI and the Banking Experience
Generative AI is opening new possibilities for how customers interact with their banks. Large language models can understand complex financial questions posed in natural language, analyse a customer’s complete financial picture, and provide personalised guidance that was previously available only from human financial advisors. A 2025 Accenture survey found that 48% of digital banking customers said they would trust AI-generated financial advice if it was based on their actual transaction data and financial history.
The implications for product design are significant. Digital banks are building AI financial assistants that can answer questions like “Can I afford to buy a house next year?” by analysing income patterns, spending trends, savings rates, and local housing market data. These assistants can also identify optimisation opportunities — recommending balance transfers, subscription cancellations, or savings strategies — that are specific to each customer’s situation.
According to Forrester Research, digital banks that deploy generative AI assistants see 35% higher daily active usage and 28% higher customer retention than those without. The engagement improvement matters because digital banking profitability depends on active usage — a dormant account generates minimal revenue regardless of how many customers a bank has acquired.
AI-Native Banking Architecture
The most forward-looking digital banks are designing AI-native architectures where every system component is built to generate, process, and learn from data. Unlike bolted-on AI features, AI-native architecture means that the core banking system, risk engine, compliance monitoring, customer service, and product recommendation systems share a unified data layer and continuously improve each other’s performance.
According to Boston Consulting Group, AI-native digital banks operate at 45% lower cost-to-income ratios than digital banks with traditional architectures augmented by AI features. The efficiency gap exists because AI-native systems eliminate the integration overhead and data silos that reduce the effectiveness of add-on AI solutions.
For fintech startups building new banking platforms, the AI-native approach offers a structural advantage over both traditional banks and earlier-generation neobanks. Venture investors are increasingly directing capital toward AI-native banking platforms, with CB Insights reporting that AI-native banking startups raised $3.8 billion in 2024, a 67% increase from the prior year. The investment thesis is straightforward: as fintech revenue continues its rapid growth trajectory, the platforms with the most advanced AI capabilities will capture the largest share.
