The Core Modernization Imperative: How Modern, Cloud-Native Architectures Enable AI-First Transaction Banking

Introduction: Why Core Modernization Is Now Non-Negotiable

Transaction banking is at a crossroads. As corporate clients demand real-time, integrated, and AI-powered solutions for working capital, banks are under mounting pressure to deliver seamless, embedded experiences. Yet, many are held back by legacy technology—fragmented systems, siloed data, and monolithic architectures that stifle innovation and slow time to market. The result? Missed opportunities, rising operational costs, and a widening gap between what clients expect and what banks can deliver.

The imperative is clear: to compete and lead in the era of AI-first, embedded transaction banking, banks must modernize their core. This means moving beyond incremental upgrades and embracing cloud-native, coreless, and modular architectures that unlock agility, scalability, and the full potential of AI.

The Four-Step Modernization Journey

Modernizing the core is a complex undertaking, but with a clear roadmap, banks can de-risk the journey and accelerate value realization. Here’s a practical, four-step guide to core modernization:

1. Confirm Your Ambitions

A successful transformation starts with a clear, organization-wide vision. Define the case for change—why modernization is essential for your bank’s future, how it aligns with your strategic goals, and what outcomes you expect. Assess your organization’s readiness, from culture and leadership commitment to technology and data maturity. Secure buy-in from the boardroom to the front lines, and establish a leadership team empowered to drive the program.

Pitfalls to avoid:

Unclear or misaligned ambitions that fail to galvanize the organization
Underestimating the need for cross-functional commitment and change management

2. Mobilize the Program

With ambitions set, assemble the right team and partners. Develop a detailed roadmap that links customer journeys to technology and operational enablers. Design a future-proof, coreless architecture—modular, API-driven, and cloud-native. Fast-track critical enablers such as cloud infrastructure, API strategies, and data governance. Begin shaping the operating model for a coreless bank, ensuring risk, compliance, and business functions are engaged from the outset.

Pitfalls to avoid:

Large upfront investments with delayed value realization
Rebuilding legacy complexity instead of embracing modularity and coreless design

3. Prove the Platform

Deliver a ‘pathfinder’—a customer-facing launch that demonstrates the new platform’s capabilities. This first release is pivotal: it builds belief, enables real-world learning, and sets the stage for iterative scaling. Focus on foundational elements (cloud, data, DevSecOps), select initial customer segments for migration, and ensure robust risk and compliance controls. Use this phase to refine migration strategies, integration patterns, and operating models.

Pitfalls to avoid:

Failing to launch due to overambitious scope or lack of readiness
Underestimating migration and integration complexity

4. Scale, Progressively

With the platform proven, accelerate expansion through iterative releases. Prioritize features and migrations that deliver the most value, and maintain strong communication to sustain momentum. Establish a ‘modernization factory’ to manage ongoing migrations, decommission legacy systems, and continuously enhance the platform. Embed new ways of working, leveraging agile, cross-functional teams focused on customer outcomes.

Pitfalls to avoid:

Poor sequencing of migrations, leading to customer disruption
Losing momentum due to inadequate communication or change management

Why Coreless, Modular Architectures Are Essential for AI-First Transaction Banking

Legacy systems are the single biggest barrier to delivering AI-powered, embedded transaction banking. Siloed data, rigid product systems, and slow release cycles make it nearly impossible to provide the real-time, personalized, and integrated experiences that clients now expect. In contrast, coreless, modular architectures offer:

Decoupled Data and Business Logic: Data is no longer trapped in product silos, enabling unified, real-time insights across all banking relationships.
API-Driven Integration: Open APIs allow seamless connectivity with client ERPs, fintech partners, and third-party platforms, making embedded finance a reality.
Cloud-Native Scalability: Elastic infrastructure supports real-time analytics, AI model training, and rapid scaling of new services.
Composable Services: Banks can assemble best-of-breed components, swap out modules as needed, and innovate at pace without being locked into a single vendor.

This architectural shift is the foundation for AI-first transaction banking—enabling:

No-code, self-service dashboards that empower clients to build custom working capital views and forecasts
Embedded finance capabilities that bring banking directly into clients’ workflows
Proactive, AI-driven recommendations and instant credit decisions
Scalable distribution of new products and services across partner ecosystems

Common Pitfalls and How to Avoid Them

Modernization is fraught with risks, but most failures stem from a handful of recurring issues:

Lack of alignment and leadership commitment: Without a clear, shared vision, programs stall or lose momentum.
Big-bang approaches: Attempting to replace everything at once leads to cost overruns and delivery failures. Iterative, value-driven releases are essential.
Recreating legacy complexity: Simply replicating old systems in new technology misses the opportunity for simplification and modularity.
Neglecting data and integration: Failing to decouple data and design robust API strategies undermines the benefits of modernization.
Underestimating change management: Technology alone is not enough—success requires new ways of working, cross-functional teams, and a culture of continuous improvement.

Real-World Impact: What’s Possible

Banks that have embraced core modernization are already seeing transformative results:

Faster onboarding: Onboarding times for SMEs and corporates have dropped from weeks to under an hour, with automated KYC and digital workflows.
Personalized, AI-powered dashboards: Clients gain real-time, unified views of working capital, with proactive forecasts and tailored financing offers.
Embedded finance at scale: Banks deliver services directly within client ERPs, driving deeper engagement and new revenue streams.
Cost and efficiency gains: Modern architectures reduce annual run costs by up to 50%, freeing resources for innovation and growth.

The Road Ahead: From Vision to Value

The convergence of AI, generative AI, and embedded finance is reshaping transaction banking. Banks that act now—modernizing their core, harnessing data and AI, and embedding themselves in their clients’ digital ecosystems—will unlock new value, deepen relationships, and secure their place at the center of the corporate financial landscape.

Publicis Sapient partners with leading banks to design and deliver next-generation transaction banking solutions. Our expertise spans strategy, product, experience, engineering, and data—enabling clients to define and execute AI-first, embedded finance strategies, build and scale modern platforms, and deliver seamless, personalized experiences that drive client loyalty and growth.

Ready to build the future of transaction banking? The time to modernize is now. Let’s unlock the power of AI-first, embedded banking—together.