Innovation vs. Operations: The Strategic Imperative for Corporate Banking Transformation.

Corporate banks across the globe are confronting a fundamental paradox: while innovation represents their most critical success factor for sustainable competitive advantage, the overwhelming majority of their IT budgets—often 80-90%—remains trapped in “Keep the Lights On” (KTLO) activities. This comprehensive analysis reveals that for 2024, banks are expected to allocate approximately 67% of their IT budget to maintaining current infrastructure, 22% to expanding capabilities, and only 11% to innovation. This allocation imbalance threatens banks’ ability to compete with agile fintech disruptors and meet evolving customer expectations.

The data paints a stark picture: despite a global total of approximately $600 billion being spent by banks on technology, labor productivity in major markets like the United States is declining. Meanwhile, 89% of IT leaders believe their organization should allocate more resources to innovation, while 77% cite excessive KTLO spending as a major obstacle. This report provides financial services executives with a strategic framework for rebalancing this equation and achieving sustainable competitive advantage through disciplined innovation investment.

The KTLO Trap: Understanding the Budget Allocation Challenge

Defining the Challenge

Keep the Lights On (KTLO) activities encompass the fundamental maintenance tasks required to ensure banking systems remain operational and compliant. KTLO refers to everything that comes between your product and your customers receiving its promised value, including system maintenance, security patches, regulatory compliance, and basic infrastructure management.

The challenge is not that KTLO activities lack importance—they are essential for business continuity. The problem lies in their exponential growth and the resulting crowding out of innovation investments. Executives spend up to 85% of their IT budget just “keeping the lights on” and report that their businesses are being held back as a result.

The Scope of the Problem

Current industry data reveals the magnitude of this challenge:

• For 2024, banks are expected to allocate about 67% of their IT budget to maintain current infrastructure, 22% to grow capabilities, and only 11% to innovate
• In 2020, almost half (44%) of IT and cloud operations teams’ time went to manual, routine work
• According to a previous McKinsey survey of CIOs, companies pay an additional 10 to 20 percent to address tech debt on top of the costs of any project.
• A 2020 Vanson Bourne survey found that 77% of IT leaders cite KTLO as a major obstacle to innovation, and 89% agree that their organization needs to allocate more resources to innovation.

This budget allocation creates a vicious cycle: as legacy systems age and regulatory requirements increase, KTLO demands grow, leaving even less room for innovation that could modernize infrastructure and reduce future maintenance burdens.

The Competitive Context

The stakes have never been higher. Corporate banks face a unique set of challenges going into 2024, with revenue growth likely to be challenged, especially in the United States. Simultaneously, they confront intensifying competition from fintech startups that operate with modern, cloud-native architectures requiring minimal KTLO overhead.

Banks are struggling to get their costs under control, and the imperative to bring down expenses should only intensify as revenue growth is expected to remain elusive in 2025. This cost pressure makes it even more critical that banks optimize their technology spending allocation.

The Innovation Imperative: Why Corporate Banks Must Act

Market Pressure and Customer Expectations

The competitive landscape has fundamentally shifted. Traditional banks face intensified competition from agile fintech startups offering innovative solutions like AI-powered personalized banking, decentralized finance (DeFi) services, and seamless mobile experiences. Customer expectations have evolved accordingly, with 55% of U.S. consumers making mobile banking their primary choice for account access.

Corporate banking customers, in particular, demand increasingly sophisticated digital capabilities. Corporate banking has long trailed behind retail and SME segments in digital innovation, largely due to the complexity of its core systems and the interdependence on outdated, monolithic architectures. This lag creates both vulnerability and opportunity for institutions willing to invest in innovation.

Regulatory and Operational Drivers

The regulatory environment continues to evolve, creating additional pressure for innovation:

• Changes to bank capital and liquidity rules may impact cost structures, while non-financial risks such as operational resilience, cybersecurity, third-party risk management, financial crime, and AI are expected to remain priorities
• ISO 20022 continues to be the burning platform in the U.S., as this move to a single common global business language for financial messaging is a mandate for all financial institutions

These regulatory requirements often drive technology investments, but banks that approach them strategically can leverage compliance initiatives as innovation opportunities rather than pure cost centers.

The Value of Innovation Investment

Research demonstrates clear returns on innovation investment in banking:

• Strategic application of machine learning and data analytics has led to a 40% reduction in fraud cases for innovative banks like Revolut
• The agile approach to product development has enhanced adaptability and accelerated entry into new markets, with a 50% increase in global users year-over-year.
• Metro Commercial Bank’s ability to onboard new clients quickly and accurately provided a competitive advantage, leading to a 30% increase in new client acquisitions.

The Strategic Framework for Rebalancing Innovation and Operations

Phase 1: Assessment and Rationalization

The first step in breaking free from the KTLO trap involves a comprehensive assessment of current spending patterns and identification of optimization opportunities.

Technology Audit and Rationalization: The highest return on investment activity for organizations is often deleting features and code that no longer add value. Banks should conduct systematic reviews of their application portfolios to identify:

• Legacy systems that can be decommissioned or consolidated
• Features that consume disproportionate maintenance resources relative to business value
• Redundant processes that can be eliminated rather than automated

Process Optimization: The first part is eliminating unnecessary work to get out of the Keep the Lights On mentality. Don’t automate or improve processes if you can get rid of them completely. This principle should guide initial rationalization efforts.

Benchmarking and Target Setting: Banks that want to be more aggressive with innovation and technology can show they are investing more than their peers by benchmarking against industry standards. Establish clear targets for the innovation/operation spending ratio based on institutional strategic objectives.

Phase 2: Strategic Automation and Modernization

Cloud-First Infrastructure Strategy: Technologies like Kubernetes enable containers that can run across AWS, Azure, or Oracle without modification, providing operational flexibility while reducing maintenance overhead. This approach significantly reduces KTLO requirements while enabling scalability.

Robotic Process Automation (RPA): Robotic Process Automation represents significant automation opportunities that didn’t exist a couple of years ago. Strategic RPA implementation can eliminate routine manual processes, freeing resources for higher-value activities.

DevOps and Continuous Integration: True Agile product development, when done right, creates significant efficiency gains for reducing KTLO through automated testing and deployment pipelines. This enables faster, more reliable delivery while reducing operational overhead.

Phase 3: Innovation Investment Strategy

Focused Innovation Allocation: Rather than spreading innovation investment thinly across multiple initiatives, successful banks concentrate resources on strategic priorities that align with their competitive positioning. As of June 2024, more than three-quarters of banks plan to increase investments in data management and cloud consumption to advance their enterprise-wide generative AI strategy.

Partnership and Ecosystem Strategy: Banks are exploring collaborations with fintech firms, leveraging digital transformation to enhance customer experiences and streamline operations. Strategic partnerships can accelerate innovation while sharing development costs and risks.

Artificial Intelligence and Machine Learning: Many banks are actively exploring GenAI for cybersecurity (67%), fraud detection (51%), and compliance and risk management (41%). These applications directly support operational excellence while reducing KTLO burden.

Case Studies in Successful Innovation Investment

Capital One: Digital-First Strategy

Capital One was early in the digital transformation game and didn’t face the challenge of catching up to industry peers. They recognized the need to sustain their leadership position in the face of aggressive competition. The bank’s strategy included:

• Aggressive enhancement of mobile banking services
• Voice-activated banking capabilities
• AI learning applications for improved service delivery, security, and productivity
• Comprehensive data analytics capabilities

The results demonstrate the power of sustained innovation investment in maintaining competitive advantage.

BBVA: Comprehensive Digital Transformation

BBVA’s comprehensive digital transformation has solidified its position as a leader in digital banking across Europe through innovative mobile banking services, real-time processing capabilities, and strategic partnerships with fintech companies. Key elements included:

• Mobile-first banking platform development
• Real-time payment processing infrastructure
• Strategic fintech partnerships
• Data-driven customer experience optimization

Regional Bank Innovations

TreasurUp has created the first excess-liquidity front end for banks, designed from the clients’ point of view—bridging the gap between identifying liquidity needs and products, ranging from basic trade to advanced optimization. This innovation demonstrates how focused investment in specific corporate banking pain points can create a significant competitive advantage.

The Role of Artificial Intelligence in Rebalancing the Equation

AI as an Operational Efficiency Driver

Artificial Intelligence represents a unique opportunity to simultaneously reduce KTLO requirements while enabling innovation. Some leading banks that have been first movers have publicly announced efficiencies from AI, for some of them in the billions of dollars, already worth as much as a point of efficiency ratio.

Automated Operations: AI can automate routine monitoring, patch management, and basic troubleshooting activities that traditionally consume significant IT resources. This automation directly reduces KTLO requirements while improving system reliability.

Predictive Maintenance: Machine learning algorithms can predict system failures before they occur, enabling proactive maintenance that prevents costly outages while reducing overall maintenance overhead.

Intelligent Resource Allocation: AI-driven analytics can optimize infrastructure utilization, automatically scaling resources based on demand patterns and reducing both operational costs and management complexity.

AI-Driven Innovation Opportunities

Customer Experience Enhancement: AI technologies are being used for analyzing significant datasets, automating processes, and improving user experience through personalized services, including online assistants and chatbots.

Risk Management Innovation: Machine learning makes it easier to track changes in user behavior and detect fraudulent activity faster, directly supporting both operational excellence and customer protection.

Regulatory Compliance Automation: Brazil’s Banco Bradesco is using generative AI to analyze and summarize minutes and announcements from the Monetary Policy Committee of Brazil’s central bank, demonstrating how AI can transform compliance from a cost center into a competitive advantage.

Measuring Success: Key Performance Indicators

Financial Metrics

IT Spending Ratio Optimization: Track the evolution of KTLO versus innovation spending ratios. Technology-forward banks spend as much as 16.4% of revenue on technology, while non-tech banks spend as little as 3.9%. The key is ensuring that increased technology spending translates into improved innovation allocation.

Return on Technology Investment: Measure the business impact of innovation investments through metrics such as:

• Time-to-market for new products and services
• Customer acquisition and retention rates
• Revenue from new digital channels
• Operational cost reduction from automation

Technical Debt Reduction: About 30% of CIOs believe that more than 20% of their technical budget allocated to new products is actually diverted to resolving issues related to tech debt. Track the reduction in technical debt as infrastructure modernization progresses.

Operational Metrics

System Reliability and Performance: While reducing KTLO spending, banks must maintain or improve:

• System uptime and availability
• Transaction processing speeds
• Security incident frequency and response times
• Regulatory compliance metrics

Innovation Velocity:

• Number of new features or services launched per quarter
• Time from concept to market for new initiatives
• Employee satisfaction with technology tools and capabilities
• Customer satisfaction with digital services

Overcoming Implementation Challenges

Cultural and Organizational Barriers

Change Management: Innovation is the ability to see change as an opportunity, not a threat. Organizations must foster a culture that embraces innovation while maintaining operational discipline.

Skill Development: Banks are no longer seen automatically by top talent as the most desirable, rewarding, or stimulating destinations. More innovative solutions are needed, such as dropping the requirement for university education and adding benefits such as lifetime retraining.

Leadership Alignment: The program improved participants’ leadership abilities, gave them a deeper understanding of the bank’s strategy, and empowered them to execute on the company’s digital transformation strategy. Investing in leadership development ensures that innovation initiatives have proper organizational support.

Technical and Risk Management Considerations

Legacy System Modernization: In a 2023 Forbes Insights report, nearly six out of 10 banking leaders consider legacy infrastructure to be the top challenge impeding their organization’s business growth. Organizations must balance the cost and risk of modernization against the escalating burden of maintaining aging systems.

Security and Compliance: Successful digital banking transformation hinges on a holistic approach that includes proactive risk assessment, continuous monitoring, and the incorporation of advanced cybersecurity measures. Innovation initiatives must incorporate security by design rather than treating it as an afterthought.

Vendor Management: 70% believe their tech providers fail to support innovation, while 63% feel stuck in restrictive vendor relationships. Banks must strategically evaluate vendor relationships to ensure they support innovation rather than perpetuate KTLO dependency.

Strategic Recommendations for Financial Services Executives

Immediate Actions (0-6 Months)

Conduct Comprehensive Spending Analysis:

• Audit current IT spending allocation across KTLO, growth, and innovation categories
• Identify quick wins for cost optimization and resource reallocation
• Establish baseline metrics for tracking progress

Implement Governance Framework:

• Create a dedicated innovation investment committee with clear accountability
• Establish stage-gate processes for innovation initiatives
• Define success metrics and regular review cadences

Rationalize Legacy Infrastructure:

• Identify applications and systems for retirement or consolidation
• Develop business cases for cloud migration initiatives
• Begin planning for major system modernization efforts

Medium-Term Initiatives (6-18 Months)

Launch Strategic Automation Program:

• Implement RPA for high-volume, routine processes
• Deploy AI-driven monitoring and maintenance capabilities
• Establish DevOps practices for faster, more reliable deployments

Develop Innovation Capabilities:

• Create innovation labs or centers of excellence
• Establish a fintech partnership framework
• Begin pilot programs for emerging technologies

Modernize Core Infrastructure:

• Execute cloud migration strategies
• Implement modern data architecture and analytics capabilities
• Upgrade network and security infrastructure

Long-Term Transformation (18+ Months)

Achieve Optimal Resource Allocation:

• Target 60% operations, 25% growth, 15% innovation spending ratio
• Demonstrate measurable business impact from innovation investments
• Establish sustainable competitive advantages through technology

Build Innovation-Driven Culture:

• Implement continuous learning and development programs
• Create incentive structures that reward innovation and calculated risk-taking
• Establish metrics that balance operational excellence with innovation success

Establish Market Leadership:

• Launch differentiated products and services enabled by technology investment
• Achieve recognition as an innovation leader in corporate banking
• Build ecosystem partnerships that create a sustained competitive advantage

Future Outlook and Strategic Implications

The Evolving Competitive Landscape

The banking industry continues to face unprecedented change. Value is migrating steadily away from banks and toward nonbank financial institutions and digital attacker banks, and in many cases, competitors are generating new revenue pools. This trend will accelerate, making innovation investment not just advantageous but essential for survival.

Agentic AI has the potential to radically change the banking model—but it also contains the seeds of further disruption. Banks that fail to invest in innovation will find themselves increasingly unable to compete with more agile, technology-enabled competitors.

Regulatory and Market Drivers

Despite a shift in administrations, the banking industry will likely remain focused on addressing outstanding supervisory issues and demonstrating sustainable remediation in 2025. This creates both challenge and opportunity—banks that can leverage technology to improve compliance efficiency will achieve a competitive advantage while meeting regulatory expectations.

Bankers recognize AI’s transformational potential—but also realize they must strengthen operations before scaling AI enterprise-wide. This reinforces the need for a balanced approach that optimizes operations while building innovation capabilities.

Technology Evolution and Opportunities

2025 will see an intensified focus on consumer protection, emphasizing enhanced transparency, fair treatment, and robust data security measures to build trust. Robust AI governance will also be a key regulatory trend. Banks that invest early in these capabilities will be better positioned for regulatory compliance and competitive advantage.

The convergence of technologies creates unprecedented opportunities for banks willing to invest in innovation. The convergence of generative AI and technology migration offers a promising solution—one that can streamline the transition to more efficient, real-time, and customer-focused banking platforms.

The Strategic Imperative for Change

The data is unambiguous: corporate banks that continue to allocate 80-90% of their technology budgets to maintaining operational stability will find themselves increasingly unable to compete in the digital economy. The solution requires more than incremental optimization—it demands fundamental rethinking of how banks approach technology investment and operational excellence.

The path forward involves three critical elements:

Systematic KTLO Reduction: Banks must aggressively rationalize legacy systems, eliminate unnecessary complexity, and automate routine operations. This creates the budgetary space for innovation investment while improving operational efficiency.

Strategic Innovation Investment: Rather than spreading resources across numerous small initiatives, banks must concentrate investment on strategic priorities that create a sustainable competitive advantage. This includes AI and machine learning, cloud infrastructure, and customer experience platforms.

Cultural Transformation: Technology transformation alone is insufficient. Banks must foster cultures that embrace innovation, accept calculated risks, and measure success through both operational excellence and the impact of innovation.

The stakes have never been higher. Global banking is valued at a price-to-book ratio of 0.9, the lowest of all industries, which suggests the market expects the industry will erode economic value as a whole. Banks that successfully rebalance their innovation and operations investments will not only survive but thrive in the digital economy. Those that fail to act will find themselves relegated to commodity providers in an increasingly competitive marketplace.

The time for incremental change has passed. The future belongs to banks bold enough to break free from the KTLO trap and invest decisively in innovation that creates a lasting competitive advantage. The question is not whether banks can afford to make this transformation—it is whether they can afford not to.