In The AI Era, Banks Need Dynamic Platforms — Results From The Forrester Wave™: Digital Banking Engagement Platforms, Q2 2026

Why It Matters

Banks that adopt dynamic, AI‑native DBEPs can accelerate innovation, improve customer experiences, and protect margins, while those stuck with brittle APIs risk falling behind competitors.

Key Takeaways

• DBEPs stay mission‑critical, enabling rapid product experimentation.
• Low‑code tools now embed generative AI for faster development.
• API‑first claims often mask integration challenges.
• Vendors like Backbase offer agentic low‑code workflow studios.
• Infosys Finacle uses proprietary genAI for end‑to‑end customer journeys.

Pulse Analysis

The digital banking engagement platform market is at a crossroads as artificial intelligence reshapes customer expectations. Forrester’s latest Wave underscores that banks can no longer rely on legacy core systems alone; they need modular, AI‑ready layers that can be reconfigured on demand. This shift is driven by the need to deliver personalized experiences, reduce time‑to‑market for new products, and protect profit margins in a highly competitive landscape. Platforms that act as a sandbox for rapid experimentation are now viewed as mission‑critical infrastructure rather than optional add‑ons.

A defining trend highlighted in the report is the surge of low‑code and no‑code development environments powered by generative AI. Solutions such as Backbase’s Agent Studio let business users assemble complex, agentic workflows without deep coding expertise, while still offering pro‑code extensions for sophisticated use cases. This democratization of development accelerates innovation cycles, allowing banks to test hypotheses, iterate on user interfaces, and launch micro‑services in weeks instead of months. The integration of large language models also enables conversational interfaces that can handle onboarding, support, and cross‑selling, creating a more seamless end‑to‑end journey for consumers.

Despite the hype, many vendors’ “API‑first” and “AI‑native” claims fall short in practice. Banks report broken APIs, undocumented endpoints, and AI models that lack real‑world robustness, leading to costly integration delays. To mitigate these risks, institutions should adopt a rigorous vendor assessment framework that evaluates not only marketing promises but also sandbox performance, documentation quality, and post‑deployment support. Prioritizing platforms with proven generative AI pipelines—like Infosys Finacle’s proprietary models—can deliver tangible benefits while safeguarding against the illusion of seamless integration.