Backbase 2027 Predictions: Why AI Will Force Banks to Rebuild Their Operating Models

Banking leaders are being urged to move beyond isolated AI experiments to avoid obsolescence as macroeconomic pressures and regulatory scrutiny intensify. Backbase’s latest industry report identifies a critical shift toward "agentic AI," where governed autonomous agents are integrated directly into core operating models to scale revenue and service capacity by 2027.

What was announced

Backbase has released its "Banking Predictions 2027" report, identifying ten major trends that will shape the financial services industry over the coming year. The report, featuring insights from McKinsey & Company, Endava, and Jet Bank, argues that the industry is entering a phase where AI must justify its existence through clear financial baselines. By 2027, every AI-related budget item will require a demonstrated return on investment, moving away from the "pilot-itis" that has characterized recent years.

The report outlines a three-step strategy for implementation: identifying a single high-friction customer journey, measuring it against financial baselines, and establishing reusable data and governance foundations. This approach is designed to move AI from a peripheral tool to a core component of the banking operating model. It also highlights the rise of conversational banking, noting that consumer comfort with AI agents is already high across generations. However, the report warns that while banks can utilize external AI models, they must retain full accountability for the decisions made by these agents. This requires a fundamental change in how banks manage risk, security, and regulatory discipline, ensuring that human oversight remains central even as agents take on more colleague-like roles within the organization.

"Banks can rent AI models, but they have to own the accountability for what those agents do. That changes the operating model itself, as agents become colleagues and people stay accountable for the decisions that matter."

Jouk Pleiter, founder and CEO of Backbase.

The companies involved

Backbase is a major player in the engagement banking space, providing a platform designed to replace legacy silos and modernize the customer experience. The company has a significant global footprint and focuses on unifying the customer journey across various touchpoints, a strategy that increasingly relies on the data and governance frameworks highlighted in their 2027 predictions. Endava is a technology services provider that assists financial institutions with digital transformation and the integration of emerging technologies like conversational AI. Judo Bank, an Australian challenger bank founded to serve the small and medium-sized enterprise (SME) market, has positioned itself as a "relationship bank" that leverages technology to enhance human-led service. Jet Bank is a newer entrant in the digital banking space, led by founder and CEO Fatbardha Rino. These organizations represent a cross-section of the modern banking ecosystem, from established platform providers to agile challengers, all navigating the transition toward production-stage AI deployment.

What FF News has reported before

FF News has tracked Backbase’s aggressive push into AI-native infrastructure, recently reporting on how Wahda Bank Partners with Backbase to Launch AI-Native Banking OS Across Libya. This move aligns with the company’s broader strategy to accelerate deployment, as seen when Backbase Launches AI-Powered Delivery Factory to Double Banking Software Implementation Speed. The firm’s innovation in specific sectors was also recognized when Backbase Wins 2026 Wealth Management Impact Award for Advisor Desktop Innovation. Furthermore, the company continues to bolster its global leadership, having recently Appointed Nikhil Gujral to Accelerate APAC Growth Strategy. These developments underscore a consistent focus on scaling digital transformation through both technological advancement and regional expansion.

What this means

The transition from "generative AI" to "agentic AI" represents a hardening of the fintech market. The industry is moving past the novelty of chatbots toward a reality where AI agents possess the agency to execute transactions and make decisions. This puts immense pressure on legacy institutions that lack the clean data foundations required for such autonomy. For the sector, the open question is no longer about the capability of the models, but the maturity of the governance. Banks that cannot bridge the gap between experimental pilots and production-stage deployment face a future of diminishing margins and lost market share to more agile, AI-native competitors.