Executive Summary
The global banking industry entered 2026 with a paradox: record earnings and persistent investor skepticism. According to McKinsey & Company's 2026 Global Banking Annual Review, net income reached $1.3 trillion in 2025, up 7% from the previous record year. Yet the industry's price-to-book and price-to-earnings ratios remain the lowest of any sector, and return on tangible equity has begun to decline again. The review points to four converging challenges that threaten banks' most vital asset—the customer relationship: mature fintechs, high-performing neobanks, agentic AI, and digital assets such as stablecoins. These forces are accelerating at a pace that banks have never experienced, demanding a new strategic paradigm: precision with speed.
Introduction
For decades, banks enjoyed a singular advantage: they derived most of their revenues and profits from older customers who adopted technology slowly. The internet and smartphone revolutions upended other industries, but banking was able to adopt new technologies at a deliberately measured pace. That advantage has evaporated. AI adoption is the fastest in history, and both young and old are embracing it at nearly the same rate. The 2026 review, authored by senior partners Klaus Dallerup, Miklós Dietz, Pradip Patiath, and Vik Sohoni, argues that the old playbook of waiting out threats no longer works. Banks must embrace precision strategies—a granular, data-driven approach to customer segmentation, risk management, and capital allocation—and execute them with a velocity that matches AI development.
Technology Background
The technological landscape for banking is being reshaped by three interconnected developments. First, generative AI and agentic AI are moving from experimentation to production, enabling autonomous decision-making and personalized financial services. Second, mature fintechs—including neobanks like Revolut and Nubank—have broken through the growth/performance frontier, claiming an estimated 17% of industry revenues. Third, digital assets and stablecoins are maturing into infrastructure that could allow retail and corporate customers to conduct financial transactions without traditional intermediaries.
McKinsey's analysis emphasizes that these are not separate trends but a two-headed technological revolution. Agentic AI reduces the cost and friction of financial services, while stablecoins provide an alternative ledger and settlement mechanism. Together, they make it easier than ever to "bank without banks." Customer attitudes are reaching a tipping point: users now not only favor but also trust new entrants for everyday reliable services.
Main Analysis
State of the Industry: Strong Economics, New Alignments
In 2025, global banking revenues before risk costs rose from $6.1 trillion to $6.4 trillion, and balances held by banks—deposits, loans, and assets under management—increased from $381 trillion to $406 trillion. Net interest margins declined slightly globally, from 1.65% to 1.63%, but with notable regional variation: US banks improved by 9 basis points, Japanese banks by 7, and UK banks by 6, while emerging markets slipped, with Brazil seeing a dramatic decline from 3.55% to 2.93%. Costs improved, dropping from 1.31% of assets to 1.23%.
Despite these strong economics, investor sentiment remains cautious. The industry's price-to-book and price-to-earnings ratios lag all other sectors, and return on tangible equity decreased from 12.4% in 2024 to 11.8% in 2025. McKinsey suggests investors are "delighted with recent results but not buying in to a long-term vision of continued growth and profit." The memory of the global financial crisis and the lost decade of 2012–2021—when the industry did not create real shareholder value—weighs heavily.
The Four Threats to Customer Ownership
The 2026 review identifies four rising challenges to banks' most vital asset: the customer relationship.
Mature fintechs: Historically an irritant, fintechs have now claimed 17% of industry revenues by one measure. They are no longer just niche players but full-scale competitors with sophisticated technology and customer-centric business models.
Neobanks: Decacorns like Revolut and Nubank have rewritten expectations for what digital banks can achieve. They combine rapid customer acquisition with scalable technology and favorable unit economics, forcing incumbents to confront new performance benchmarks.
Agentic AI and digital assets: These technologies reduce transaction costs and eliminate intermediaries. Agentic AI can autonomously manage finances, while stablecoins offer near-instant settlement and programmability. For many customers, these capabilities reduce the need for a traditional bank relationship.
Shifting customer trust: Customers increasingly trust technology companies and fintechs for everyday financial services. This is not a preference for novelty but a rational response to reliable, fast, and transparent alternatives.
Banks have faced threats before, but the speed and scale of these converging challenges are unprecedented. The review warns that "AI adoption is the fastest in history, and young and old people are piling in at nearly the same rate."
Precision Strategies: The New Imperative
Last year's review introduced "precision strategies" as an alternative to the macro-focused, scale-driven, broad-brush approaches that have run out of steam. Precision means serving customers at granular segments—even individual level—with tailored products, pricing, and distribution. It requires advanced data infrastructure, real-time analytics, and flexible technology stacks.
This year, the review adds a new dimension: precision must be accompanied by speed. The pace of AI development is brutal, and banks that cannot execute quickly will lose relevance. McKinsey suggests that banks must evolve into "multispeed organizations"—able to run core operations reliably while simultaneously innovating at speed. This is a structural challenge, not just a technology challenge.
Innovation Impact
The findings of the 2026 Global Banking Annual Review have significant implications for innovation across the financial services ecosystem.
Technology development: AI infrastructure, data platforms, and robust APIs are becoming the battleground for banking competitiveness. Banks that invest in proprietary AI models and real-time data pipelines will outmaneuver those relying on legacy systems.
Scientific progress: The application of advanced analytics and machine learning to finance is creating new fields of research in decision science, risk modeling, and behavioral economics.
Business innovation: Precision strategies are leading to hyper-personalized products, dynamic pricing, and embedded finance opportunities. Banks that can connect data to decisions will unlock new revenue streams.
Industrial transformation: The banking industry is undergoing a structural shift from branch-based, product-centric models to digital, customer-centric platforms. This affects not just banks but also their suppliers, outsourcers, and technology partners.
Investment: Persistent low valuations may spur consolidation, divestitures, and private capital involvement. The promise of AI-driven efficiency gains could attract long-term investors who believe in the transformation story.
Research commercialization: University research in AI, cryptography, and distributed systems is increasingly being commercialized through fintech startups, accelerating the cycle from lab to market.
Entrepreneurship: The rise of neobanks and fintechs demonstrates that well-funded startups can compete effectively with incumbents. This encourages a vibrant ecosystem of entrepreneurs and venture investors.
Manufacturing: While not directly applicable to manufacturing, the precision strategies concept—data-driven segmentation and agile production—has parallels in advanced manufacturing and Industry 4.0.
Digital economy: The banking shift is a microcosm of the broader digital economy, where platform business models and AI-native operations are becoming the norm.
Workforce transformation: Banks will need fewer back-office staff and more data scientists, AI engineers, and behavioral designers. The human-AI collaboration model will redefine roles.
Global competitiveness: Regions with advanced digital infrastructure and AI-ready talent will attract banking investment. The United States, parts of Asia, and certain European hubs are likely to lead.
Innovation ecosystems: The banking industry's transformation reinforces the importance of innovation hubs—such as London's fintech cluster, Silicon Valley, and Singapore—where finance and technology converge.
Long-term technological leadership: Banks that master AI and data will shape the future of financial services. Those that don't risk becoming utilities or obsolete.
Strategic Insights
Technology Readiness
The technology for precision banking exists, but readiness varies. Many incumbents are still wrestling with legacy core systems and fragmented data. Cloud migration is incomplete, and AI models are often siloed. To become truly data-driven, banks need investments in modern data architectures, feature stores, and MLOps practices. The most advanced institutions are already using AI for marketing, risk, and fraud detection, but the step change required is systemic.
Commercial Opportunities
The shift to precision strategies opens new commercial opportunities:
- Real-time personalization: AI-driven offers and pricing that adapt to customer behavior.
- Embedded finance: Banking products integrated into non-banking platforms (e-commerce, mobility, healthcare).
- B2B services: API-based banking-as-a-service offerings for other businesses.
- Wealth management for the mass affluent: AI-powered advisory at lower cost.
Competitive Dynamics
Competition is no longer just between banks but between entire ecosystems. Big Tech companies, fintechs, and telecommunications firms are all vying for customer relationships. Banks that can build trusted digital identities and leverage data will have an edge. However, regulators are scrutinizing data privacy and antitrust implications.
Research Trends
Academic research is increasingly focused on explainable AI, fairness, and robustness of financial models. There is also growing interest in decentralized finance (DeFi) and its intersection with traditional banking. Banks that partner with universities and research institutes can stay ahead of the curve.
Investment Priorities
Venture capital is flowing into AI-enabled financial infrastructure: intelligent automation, fraud detection, personalization engines, and stablecoin compliance tools. Corporate venture arms of banks are also investing in startups to gain access to new capabilities. The most attractive investment targets are those that help banks achieve "speed and precision."
Regulatory Considerations
The new technological landscape brings regulatory complexity. AI governance, algorithmic accountability, and data protection are top priorities. Stablecoins and digital assets require clear frameworks to ensure consumer protection and financial stability. Banks that pro-actively engage with regulators and develop responsible AI practices will be better positioned.
Long-Term Strategic Implications
The DNA of banking will change. Banks are on a path to becoming technology companies with banking licenses. This means overhauling talent, remuneration, technology architecture, and risk culture. The review warns that banks have "less time to act than they are used to." The next five years will determine which institutions remain relevant.
Future Outlook
Looking ahead to 2030 and beyond, the banking industry will likely see:
AI-native banks: Most customer interactions will be mediated by AI agents. Banks will provide AI assistance for budgeting, investing, and fraud prevention.
Open and embedded finance: Banking products will be distributed through every major platform, from cars to social networks, powered by APIs.
Stablecoins and central bank digital currencies (CBDCs): Digital money will become mainstream, with banks either adapting or bypassed.
Quantum computing: Over the longer term, quantum computing could impact cryptography and risk modeling, creating both opportunities and risks for banks.
Global rebalancing: Emerging markets, especially in Asia, will see rapid growth in digital banking. The "new world map" of banking will not look like today's.
Sustainable finance: Climate technology and ESG considerations will become core to banking strategy, influenced by regulation and customer demand.
Workforce transformation: The number of traditional tellers and backend staff will decline, while demand for data ethics, AI explainability, and cybersecurity experts will soar.
Banks that embrace precision with speed—by investing in data infrastructure, fostering a culture of rapid experimentation, and adopting a business model that separates agile innovation from stable operations—will be well-equipped to navigate the uncertainty. The 2026 McKinsey report serves as a strategic wake-up call: The future belongs to those who can move with precision and speed.
Conclusion
The global banking industry enters 2026 with strong earnings but fragile market confidence. McKinsey's 2026 Global Banking Annual Review provides a clear diagnosis: The customer relationship is under threat from mature fintechs, neobanks, agentic AI, and digital assets. To counter these forces, banks must move beyond old-fashioned scale strategies and adopt precision-based, data-driven approaches—executed with unprecedented speed. The emergence of multispeed organizations, capable of balancing reliability and agility, will be a defining feature of successful banks in the coming decade. Innovation in AI, data, and digital infrastructure is not just a technology upgrade but a strategic imperative. The banks that accept this reality will lead; those that hesitate will be left behind.
Key Takeaways
Global banking net income rose to $1.3 trillion in 2025, a 7% increase, but investor skepticism persists, with the industry's P/B and P/E ratios remaining the lowest of any sector.
Four converging threats—mature fintechs, neobanks, agentic AI, and stablecoins—are undermining banks' customer ownership.
Mature fintechs now claim 17% of industry revenues, and neobanks like Revolut and Nubank have rewritten performance benchmarks.
AI adoption is the fastest technology adoption in history, and banks cannot rely on customer inertia as a shield.
Precision strategies—granular, data-driven customer segmentation—must be combined with speed to match the tempo of AI innovation.
Banks should evolve into "multispeed organizations" to balance stable core operations with rapid innovation.
The next five years are critical: Banks that fail to execute a precision-with-speed strategy risk losing relevance to tech-native competitors.
Sources
- McKinsey & Company. "Global Banking Annual Review 2026: Precision with speed." May 21, 2026. https://www.mckinsey.com/industries/financial-services/our-insights/global-banking-annual-review