Key takeaways
Profitability pressure
AI value potential
Third-party resilience
Technology modernization
Workforce transformation
Key challenges in the finance industry
The financial sector is balancing rapid AI-driven modernization with margin pressure, legacy technology constraints, workforce adaptation, and growing third-party dependencies. Capturing the value of generative AI will require stronger infrastructure, resilient operating models, workforce capabilities, and disciplined cost management.
Core systems shape AI readiness
Technology modernization is accelerating as 71% of banks and credit unions increase technology budgets while internal IT capacity struggles to keep pace with expanding requirements. Deutsche Bank’s plan to reduce its retail division from 15 core banking systems to 2, supported by around €600 million in IT investment through 2028 and expected annual savings of €300 million thereafter, illustrates the scale of consolidation required. Capturing the estimated $200–$340 billion in annual banking value from generative AI will further increase the need for resilient infrastructure, while rising cyber risk and dependence on major technology providers add complexity.
Margin compression tests bank earnings
Rising operating costs are putting pressure on profitability as lending margins remain constrained, with HSBC’s operating expenses increasing 2% to $17.4 billion in H1 2026 while its net interest margin stood at 1.61%. CBA delivered a record A$10.98 billion profit, but its net interest margin fell to 2.05% and mortgage applications declined 15%, while China’s five largest banks recorded only 3%–5.1% profit growth with average net interest margins of 1.41%, limiting further earnings improvement.
Modernizing legacy banking infrastructure
Accelerating AI adoption is pushing financial institutions to modernize legacy technology, with 71% of banks increasing technology budgets by a median 10% as they pursue new digital capabilities. Generative AI could generate $200–$340 billion in annual banking value, equivalent to 2.8–4.7% of industry revenue, but legacy systems, manual processes, AI-driven cyber risks, and growing third-party technology concentration are complicating the transformation.
Finance industry faces an AI skills shift
As AI becomes embedded across banking, workforce adaptation is becoming increasingly important, with 70% of digital leaders across 18 banks and NBFCs reporting AI already in production while 40% struggle to identify high-ROI applications. Only 42% of financial-services leaders have assessed AI’s impact on workforce capacity across their entire organisation, while nearly 80% expect their workforce to shrink by at least 20% over the next five years, increasing the need for adaptability, judgement, and stronger human skills.
Third-party technology concentration risks
Growing reliance on external providers is increasing supply-chain exposure across technology, data, cloud, operations, and customer support, with more than 75% of financial firms in the City already using AI. Dependence on a relatively small group of AI and cloud providers could amplify cyber disruptions across multiple institutions, creating broader resilience risks for the financial system.
Next steps
Financial institutions should prioritize core-system modernization, resilient infrastructure, and cybersecurity while aligning AI investment with clear value-creation and profitability objectives. Workforce reskilling, stronger AI governance, and greater diversification of critical technology providers will also be essential to scale AI while reducing operational and financial-system resilience risks.
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