A platform approach modernises AI banking by unifying the engagement layer and stitching journeys end-to-end. As Backbase’s Jouk Pleiter argues, banks that platformise their customer experience can embed AI where it matters—decisioning, personalisation, and service—scaling value faster than channel-by-channel experiments. This is how incumbents regain speed and relevance.

Executive argument: the platform is the product

Banks don’t win AI-era loyalty by stitching tools onto legacy estates. They win by treating the platform itself as the product—a vertically integrated engagement layer that orchestrates every sales and servicing journey, front-to-back, with AI woven in. That’s the core of Jouk Pleiter’s case: platform thinking collapses silos, standardises journeys, and creates the control points where AI can add real value without fragmenting the estate.

The strategic shift is twofold. First, modernise the engagement layer—the place customers actually feel your bank—so journeys are owned end-to-end rather than by channels or products. Second, add an “intelligence fabric” to that platform so AI augments each step: onboarding, service, advice, fraud, collections. This is how incumbents regain speed without perpetual core replacement projects.

Why now: AI has changed the economics of modernisation

In 2026, AI is not a bolt-on; it’s the new operating system of growth and cost-to-serve. Banks that scale AI do three things differently: tie use-cases to value, standardise a capability stack (data, models, orchestration), and drive adoption with new ways of working. That blueprint rewards platforms that centralise orchestration and reuse across journeys—rather than one-off pilots in scattered channels.

Market signals reinforce this: vendors are shipping AI-powered engagement platforms and partnerships to close the human-digital gap (e.g., Backbase’s AI-powered platform and Unblu integration), while major banks push generative AI into frontline experiences at scale (e.g., NatWest). The direction of travel is clear: platformise, then productise AI across journeys.

What a platform approach looks like (and what it isn’t)

A true platform is journey-based and progressive: pick a priority journey—say SME onboarding—and modernise it front-to-back, reusing components across segments. It avoids “rip-and-replace” dogma, but also resists the opposite trap: incremental widgeting that never changes customer experience. Composability matters, but without a unifying engagement layer, composability devolves into integration theatre.

Backbase’s articulation is instructive: an engagement platform that unifies journeys and exposes standard control points for AI—decisioning, personalisation, and agentic workflow—rather than smearing point bots across channels. The goal is a bank-owned platform where AI can be governed, audited, and iterated rapidly.

Leadership playbook: five choices that separate winners

1. Own the engagement layer. Make it your primary product. Your channels are simply surfaces; the journey logic and data live on the platform. This is how you ship improvements weekly, not yearly. backbase.com
   
   

2. Adopt journey-based modernisation. Fund by outcome (e.g., “Reduce onboarding abandonment 30%”), not by system. Reuse components across retail, SME, and wealth. backbase.com
   
   

3. Stand up an intelligence fabric. Centralise retrieval, models, and agent orchestration so AI is permissioned, explainable, and reusable across journeys. McKinsey & Company
   
   

4. Design for human-digital collaboration. Blend automation with guided conversations—think co-browse, secure chat, and AI assistants that escalate to humans seamlessly. FF News | Fintech Finance
   
   

5. Govern for scale. Treat prompts, policies, and metrics as product artefacts. Measure conversion, time-to-resolution, fraud catch-rate, and NPS by journey, not channel. McKinsey & Company

What great looks like: signals of maturity in 2026

• Unified customer journeys across sales and service, with shared components and release trains.

• AI agents in production handling bounded tasks (pre-fill, triage, collections nudges) with human-in-the-loop controls.

• Design-ops for journeys, not pages: versioned flows, experiment frameworks, and telemetry that feed continuous improvement.

• Vendor ecosystem as a feature, not a dependency: targeted partnerships to close gaps without diluting platform control.

FAQs

Q1: How does the platform approach benefit banks?
It treats the engagement layer as a product, standardising journeys and creating governed touchpoints for AI. The result: faster change cycles, higher conversion, and lower cost-to-serve versus channel-led projects. McKinsey & Company

Q2: What role does AI play in this approach?
AI is woven into the platform’s “intelligence fabric”, powering personalisation, decisioning, and agentic workflow that can be reused across journeys—rather than scattered bots in each channel. backbase.com

Q3: Why is modernisation urgent now?
Competitive advantage is shifting to banks that can deploy AI at scale. Platformisation shortens time-to-value and reduces integration drag, allowing incumbents to match digital-native speed. BCG Global

Sources:

• McKinsey interview with Jouk Pleiter on the platform approach. McKinsey & Company

• Backbase AI-powered Banking Platform and Intelligence Fabric. backbase.com

• How to modernise the engagement layer (Backbase podcast with Pleiter). backbase.com

• Journey-based progressive modernisation explainer. backbase.com

• AI at scale in banking (McKinsey blueprint). McKinsey & Company

• BCG on the AI reckoning for banks (strategy context). BCG Global

• Backbase–Unblu partnership (human-digital collaboration). FF News | Fintech Finance

Next Steps

Ready to platformise your engagement layer and ship AI-powered journeys in quarters, not years? Generation Digital can help you prioritise the first journeys, stand up the intelligence fabric, and establish the operating model that sustains it.