Banks are under increasing pressure to deliver faster, more personalized, and technologically advanced services as client expectations continue to rise, according to Olivier Garcia, Global Corporate and Investment Banking Practice Leader at Capgemini.
“The gap between what clients expect and what banks are delivering is becoming a strategic vulnerability,” he told Traders Magazine.
According to the recently released 2026 World Corporate and Investment Banking Report by Capgemini, 82% of 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.
At the same time, competitive pressure is intensifying, with 85% of corporate clients saying they plan to work with non-bank financial institutions within the next 12 months.
Capgemini’s findings also show that many banks are struggling to meet evolving client needs. Less than one in four corporate clients believe banks are fully meeting expectations for real-time, integrated, and personalized service.
Garcia warned that inaction is becoming increasingly risky. “Choosing not to act is becoming an increasingly costly option as client relevance declines and margin compression persists,” he said.
Garcia said banks that are 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.
The transformation also changes how banks deliver value. Rather than reacting to client requests, institutions are beginning to anticipate needs through data and analytics, he said.
Garcia described this evolution as a move toward proactive engagement, where “clients get insight and access when they need it, not when the bank is ready to provide it.”
Scaling AI requires stronger foundations
Technology is accelerating this shift, Garcia said, noting that 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.
However, Garcia noted that technology itself is not the main obstacle. “From my perspective, the technology already exists,” he said. “The real challenge isn’t willingness to adopt it, but building the organizational muscle needed to evolve continuously.”
Artificial intelligence is central to many banks’ transformation strategies, but progress has been uneven, Garcia said, noting that many AI initiatives struggle to move beyond early pilots or isolated use cases.
He attributed this largely 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 said.
He added 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.
Modernizing legacy infrastructure
Legacy technology remains another major barrier to transformation in investment banking, Garcia said.
According to the report findings, 43% of IT budgets are still consumed by maintaining legacy systems, compared with only 29% allocated to innovation.
These older systems often slow integration across trading and post-trade operations while introducing risks that compound over time, Garcia said.
Garcia said banks are increasingly adopting modular, platform-led architectures built around APIs, allowing institutions to consolidate core capabilities and reduce fragmentation without replacing entire systems at once.
Post-trade operations represent a particularly promising area for innovation, he added. Automation, shared data platforms, and distributed ledger technology are already improving reconciliation processes and strengthening data integrity, Garcia said.
He pointed to initiatives such as those by BNY Mellon, including the 1Source initiative, which uses distributed ledger technology to create a single source of truth for settlement data and improve liquidity management.
New revenue opportunities emerging
Beyond operational efficiency, technological innovation is also opening new revenue streams for investment banks, according to Garcia.
He said 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, he said.
Looking further ahead, asset tokenization represents a significant opportunity. Garcia said more than half of banks are exploring tokenized products across issuance, custody, and related services.
Garcia said the appeal lies in faster settlement, improved transparency, and the potential for extended trading hours. He added that 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, according to Garcia. He said 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.
He pointed to supply-chain finance solutions developed by institutions such as JPMorgan Chase, including integrations with enterprise resource planning platforms like Oracle Fusion Cloud ERP, as examples of how embedded models can deliver both operational efficiency for clients and steady revenue for banks.
Culture and talent remain key
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.
While banks are competing heavily for external data and technology specialists, Garcia argued that hiring alone cannot solve the problem. “Banks that lean on external recruitment as their primary AI strategy are creating a dependency model that doesn’t build long-term resilience,” he said.
Garcia said institutions must focus on large-scale reskilling programs that help employees develop expertise in data, analytics, and AI-enabled workflows. He added that this includes redesigning roles, embedding AI tools into daily operations, and establishing strong human-in-the-loop models where employees collaborate with technology rather than being replaced by it.
According to Garcia, leadership commitment will determine whether transformation succeeds.
He explained that when executives actively support modernization through incentives, accountability, and sustained investment, banks can overcome legacy structures and accelerate innovation.
But when digital transformation is treated merely as another initiative, Garcia warned, even the most promising technologies struggle to deliver meaningful results. “Transformation isn’t about technology alone—it’s about people, culture, and leadership aligning to make change real,” he said.
