Investment banks face a critical paradox: they're investing heavily in innovation, yet most initiatives fail to generate meaningful revenue or cost savings. According to the 2026 World Corporate and Investment Banking Report by Capgemini, 82% of corporate and investment banking (CIB) executives said current innovation programs are not generating improved revenue through new products, while 51% said these initiatives have failed to deliver the expected cost savings. Meanwhile, 85% of corporate clients plan to work with non-bank financial institutions within the next 12 months, signaling that traditional banks are losing relevance in a rapidly evolving financial landscape. What's Creating the Innovation Gap at Banks? The disconnect between bank capabilities and client expectations is widening. Less than one in four corporate clients believe banks are fully meeting expectations for real-time, integrated, and personalized service. Olivier Garcia, Global Corporate and Investment Banking Practice Leader at Capgemini, explained the stakes clearly: "The gap between what clients expect and what banks are delivering is becoming a strategic vulnerability." He added that "choosing not to act is becoming an increasingly costly option as client relevance declines and margin compression persists". The problem isn't a lack of available technology. Rather, it's a combination of organizational, cultural, and structural barriers that prevent banks from scaling innovation effectively. Garcia noted that "the technology already exists. The real challenge isn't willingness to adopt it, but building the organizational muscle needed to evolve continuously". Why Is Legacy Technology Still Consuming Bank Budgets? One of the most significant obstacles to innovation is the burden of maintaining outdated systems. According to Capgemini's findings, 43% of IT budgets are still consumed by maintaining legacy systems, compared with only 29% allocated to innovation. This imbalance starves transformation initiatives of resources while older systems continue to slow integration across trading and post-trade operations, introducing compounding risks over time. Banks are increasingly adopting modular, platform-led architectures built around APIs (application programming interfaces), which allow institutions to consolidate core capabilities and reduce fragmentation without replacing entire systems at once. This approach offers a more pragmatic path forward than attempting wholesale system replacements, which would be prohibitively expensive and disruptive. How Are Banks Overcoming Fragmentation and Scaling Innovation? - Unified Digital Platforms: Banks making meaningful progress are shifting away from fragmented, product-led engagement models toward integrated digital platforms that unify data, execution, and reporting across asset classes, enabling a more seamless client experience. - Proactive Data and Analytics: Rather than reacting to client requests, institutions are beginning to anticipate needs through data and analytics, delivering insights and access when clients need them, not when the bank is ready to provide them. - AI-Driven Personalization at Scale: Algorithmic execution, AI-driven research, and advanced analytics tools are enabling banks to personalize trading strategies and insights at scale, capabilities that were far less developed five years ago. - Post-Trade Automation: Automation, shared data platforms, and distributed ledger technology are improving reconciliation processes and strengthening data integrity in post-trade operations. Why Are AI Governance Gaps Undermining Bank Transformation? Artificial intelligence is central to many banks' transformation strategies, but progress has been uneven. Many AI initiatives struggle to move beyond early pilots or isolated use cases, largely due to governance gaps. According to Garcia, fewer than one in three banks have centralized AI governance structures, leading to fragmented implementations that are difficult to scale and hard for regulators or clients to trust. Strong data management must come first. "AI delivers value only when data quality, lineage, and permissioning are properly established," Garcia explained. He emphasized that governance must be embedded directly into AI design rather than added later, with traceability, explainability, and human oversight built into the workflow from the outset. Without those safeguards, banks risk creating what Garcia described as "AI debt," where poorly integrated initiatives accumulate technical complexity and weaken operational agility. What New Revenue Opportunities Are Emerging for Banks? Beyond operational efficiency, technological innovation is opening new revenue streams for investment banks. Many institutions are prioritizing advanced trading tools and analytics-driven services that clients are willing to pay a premium for. Algorithmic execution, AI-driven hedging, and research analytics are already generating near-term fee income by supporting more sophisticated risk management and trading decisions. Looking further ahead, asset tokenization represents a significant opportunity. More than half of banks are exploring tokenized products across issuance, custody, and related services. The appeal lies in faster settlement, improved transparency, and the potential for extended trading hours. One particularly compelling application is collateral mobility, allowing assets to move in real time across jurisdictions and entities, improving intraday liquidity management and reducing the need for large capital buffers. Embedded financial services are also gaining traction. Integrating trading and financing capabilities directly into corporate workflows can create recurring, fee-based revenue streams that are more predictable than traditional transaction-based income. JPMorgan Chase has developed supply-chain finance solutions with integrations into enterprise resource planning platforms like Oracle Fusion Cloud ERP, demonstrating how embedded models can deliver both operational efficiency for clients and steady revenue for banks. What's the Human Capital Challenge Holding Banks Back? Despite the availability of advanced technology, cultural resistance and talent shortages continue to slow transformation. The Capgemini report found that 41% of banks are experiencing shortages of skilled technology and data talent, underscoring the human capital challenge facing the industry. This shortage makes it difficult for banks to build the internal expertise needed to design, implement, and maintain sophisticated AI and data systems at scale. The path forward requires banks to move beyond viewing technology as a standalone solution. Success depends on aligning organizational structure, governance frameworks, talent strategies, and cultural mindsets around continuous innovation. Banks that can address these interconnected challenges while managing the burden of legacy systems will be better positioned to meet evolving client expectations and compete with emerging fintech competitors and non-bank financial institutions.
