AI-powered financial services will generate $340 billion in annual revenue by 2028, according to Boston Consulting Group, representing 28% of total global financial services revenue. The projection marks a shift from AI as a cost-reduction tool to AI as a revenue engine — not just making existing services cheaper but creating entirely new categories of financial products and experiences that were impossible without machine intelligence.
New Financial Products Enabled by AI
The most significant change AI brings to financial services is the creation of products that could not exist without it. Hyper-personalised insurance policies that adjust premiums monthly based on individual behavioural data. Lending products that evaluate creditworthiness using real-time income verification rather than historical credit scores. Investment portfolios that rebalance continuously based on tax implications, market conditions, and life events. Each of these products requires AI operating at a speed and complexity that no human-driven process can match.
According to McKinsey, 35% of financial product revenue by 2028 will come from products that did not exist in 2020. The new product creation is concentrated in three areas: embedded finance (financial products integrated into non-financial platforms), personalised financial management (AI advisors that manage an individual’s complete financial life), and real-time financial services (instant lending, instant insurance, instant payments with dynamic pricing).
Fintech startups are disproportionately driving new product creation because they face fewer constraints from legacy systems and existing product cannibalisation concerns. A neobank can launch an AI-powered financial planning tool without worrying about competing with its own human advisory services. A fintech lender can offer instant micro-loans without navigating the approval processes that slow product launches at traditional banks.
The Convergence of AI and Financial Services Infrastructure
AI is merging with financial infrastructure at every level. Payment rails are incorporating AI for fraud detection and routing optimisation. Banking core systems are being rebuilt with AI decision engines. Capital markets infrastructure is adding AI for trade surveillance and risk management. According to Accenture, 82% of financial infrastructure providers plan to embed AI capabilities into their core platforms by 2027.
The convergence means that AI capabilities will become a standard feature of financial infrastructure rather than a differentiator built by individual companies. When the payment rail itself detects fraud, when the core banking system itself personalises products, and when the settlement system itself optimises capital efficiency, the baseline level of AI capability in financial services rises for everyone. Digital banking platforms that build proprietary AI advantages today will need to continue innovating to stay ahead as infrastructure providers embed AI into commodity services.
Challenges on the Path Forward
Three challenges will shape the future of AI in financial services: regulation, trust, and talent. Regulatory frameworks for AI in finance are still developing. The EU AI Act provides the most comprehensive framework, but regulators in the US, UK, and Asia are taking different approaches. According to Bank for International Settlements, regulatory fragmentation could add 15-20% to the compliance costs of AI-powered financial services operating across multiple jurisdictions.
Trust remains a barrier to adoption. A 2025 Edelman survey found that only 42% of consumers fully trust AI-made financial decisions, compared to 67% who trust human-made decisions. The trust gap is narrowing — it was 35 percentage points in 2022 and is now 25 — but it will take years of reliable performance before consumers are fully comfortable with AI managing their money.
Talent is the most immediate constraint. According to Gartner, demand for AI talent in financial services exceeds supply by 45%. Fintech companies compete not only with banks but with technology giants for the data scientists, ML engineers, and AI researchers needed to build and maintain sophisticated financial AI systems.
Despite these challenges, the trajectory is irreversible. Venture capital continues to flow into AI-focused fintech at record rates. Financial institutions are accelerating their AI investments. And customers are increasingly choosing AI-powered services over traditional alternatives. The future of financial services is AI-powered — the only question is how quickly each company makes the transition.
