Master complexity to unlock scale: the as-a-service imperative for Wealth, Banking and Asset Management
The Wealth, Banking and Asset Management industry (WBAM) is navigating a period of compounding structural pressure. Rising client expectations, accelerating regulatory demands, and cross-border fragmentation are reshaping competitive dynamics at a pace that traditional operating models and technological configurations were simply not designed to absorb. Alongside these forces, AI and Agentic AI are emerging as a macroeconomic disruptors that further raise the competitive stakes, dramatically lowering barriers to entry and accelerating the competitive threats posed by FinTechs and technology-native challengers.
Drawing on proprietary market data, the FT Longitude 2026 Survey, and real-world evidence, this new report developed jointly by Monitor Deloitte and Objectway analyzes the key trends behind these structural forces, maps the evolving landscape of Tech & Ops sourcing strategies, and builds the case for why innovative as-a-service models are emerging as the defining strategic response to manage market complexity at scale.
Incumbent operating models are resilient, but no longer scalable
Over the last years, to remain competitive and compliant, WBAM firms had to simultaneously meet rising client expectations and navigate an increasingly demanding and fragmented regulatory environment. To handle these challenges, the industry's response has been predominantly reactive: Tech & Ops expenditure reached €173 billion globally in 2024, growing consistently even through periods of market slowdown, and projected to approach €243 billion by 2029. Yet investment alone has not translated into business scalability.
Fewer than one in three firms has achieved a truly scalable business model: cost bases continue to expand in lockstep with revenues because the operating models and technological configurations of WBAM firms are structurally designed for resilience, not scalability. Indeed, legacy systems lock WBAM firms into rigid, high-maintenance environments that consume investment capacity rather than freeing it, and the continuous evolution of regulatory requirements generates a steady flow of incremental system adaptations that absorb what little discretionary investment remains. The result is an industry that manages complexity effectively but still struggles to scale.
As-a-service models are rapidly becoming the industry's answer
Across the WBAM landscape, a fundamental shift in Tech & Ops sourcing is underway. While the incidence of as-a-service models in the Tech & Ops spending mix has already grown by 10 percentage points over the last few years and accounts today for 18% of the total, this transition still exhibits strong growth potential. Indeed, as-a-service configurations – spanning Hybrid SaaS, Pure SaaS, and SaaS/BPaaS – are gaining structural momentum at the expense of traditional sourcing strategies, with extensive adoption expected to more than double among large institutions and nearly quadruple among mid-sized and smaller players within two to three years.
As-a-service platforms are configurable to each firm's specific business logic and operating requirements, allowing institutions to tailor capabilities to their needs without the cost and rigidity of bespoke development. This configurability, combined with consumption and outcome-based pricing that scales directly with business activity, enables firms to access exactly what their business needs without large upfront capital commitments and without having to manage the underlying technological and operational complexity that, ultimately, is not their core business. For these reasons, Tech & Ops sourcing strategies can no longer be treated as purely IT decisions but strategic business choices that determine how a firm grows, competes, and scales over time.
Breaking the barriers: how as-a-service models unlock AI potential at scale
In the WBAM industry, AI and Agentic AI are rapidly transitioning from isolated pilot to enterprise-wide capability, and investment is following at scale: AI spending in Financial Services has already reached approximately €50 billion in 2025, growing at a 28% CAGR through 2033. Yet despite this momentum, the industrialization of AI at scale remains elusive. Industry-wide evidence points to four structural barriers that continue to constrain its scalable and sustainable deployment: regulatory uncertainty, investment asymmetry, technological and data fragmentation, and talent scarcity.
WBAM firms that source their technology through as-a-service models are structurally better positioned to overcome these barriers. Indeed, the nature and configuration of as-a-service platforms delivers four capabilities that directly address each challenge: compliance by design, with regulatory updates embedded in the platform and managed by the partner on behalf of all clients; de-risking through a capex to opex shift; industrialization at scale through standardized data architectures and integrated AI pipelines; and expertise on demand through elite access to specialized talent and industry-grade expertise. Empirical evidence from the FT Longitude Survey confirms the connection: firms with more extensive as-a-service adoption consistently exhibit broader AI deployment. As-a-service is not merely complementary to AI adoption, it is the critical lever to scale it.
Execution is where value is won or lost
While the strategic value of as-a-service models is clear, realizing it requires more than selecting the right platform. For firms transitioning from traditional Tech & Ops sourcing to as-a-service configurations, execution is what separates transformation from disappointment. Drawing on Monitor Deloitte and Objectway's combined market experience, through the analysis of four real cases this research identifies three factors that consistently prove decisive in unlocking the full value of the transition: a governance architecture with clear accountabilities and executive sponsorship that sustains oversight well beyond go-live; organizational alignment that treats the transition as a business transformation - and not a pure IT project - requiring strong business ownership, reconfigured incentive schemes, and change champions across the organization; and a clear value-case anchored in measurable business KPIs.
For WBAM firms committed to competing in an increasingly complex landscape, the path forward is clear: sourcing Technology & Operations through as-a-service models, and executing the transition with the discipline it demands, is a powerful lever available to manage market and regulatory complexity at scale, while simultaneously accelerating the industrialized adoption of AI and Agentic AI solutions, to build future-proof operating models and technology configurations capable of meeting the challenges of tomorrow.
