From products to platforms: How Agentic AI is reshaping the future of core banking
Why AI-assisted banking starts with workflows - and why the core banking platform becomes more valuable when intelligence is applied safely
For most of banking's modern history, the product has been the anchor of the customer relationship. Mortgages, deposits, cards, loans and treasury services have defined how banks compete, generate revenue and differentiate. Yet the way these products are designed and delivered has changed remarkably little in two decades. Even as digital channels transformed the customer experience, the underlying product engines of most banks remained rooted in rigid catalogs, batch processes and monolithic cores. Agentic AI is now helping banks respond to that challenge by augmenting product workflows, not replacing the systems of record that underpin them.
While much of the industry conversation has focused on how AI improves service, operations and technology infrastructure, a deeper shift is underway at the product layer. AI is beginning to assist how banking products are built, priced, personalized and continuously improved. The next chapter of banking will not simply be AI-enabled. It will be AI-augmented: intelligence applied to banking workflows with clear oversight, governance and controls, increasing the value of the core rather than taking it over.
The end of one-size-fits-all banking
Traditional banking products were designed for broad customer segments and predictable demand patterns. A mortgage might come in a handful of variants; a savings product in three or four tiers. Standardization made sense when technology constrained flexibility and customers had fewer alternatives. That world no longer exists.
Nearly three quarters of banking customers now expect experiences tailored to their individual needs, delivered through the right channel at exactly the right moment.1 Yet more than half of banking executives admit they lack a consolidated customer view across accounts and products,2 and only 37% of customers feel they receive personal advice from their bank.3 The gap between customer expectation and structural capability has become one of the industry's most pressing product challenges.
McKinsey estimates that a typical bank relies on more than 1,500 different customer journeys, most of which need to be reimagined to remove friction.4 Personalization at this scale cannot be solved by adding new channels or refreshing user interfaces. It requires a fundamental rethink of how banking products are constructed - and that is precisely where Agentic AI creates a step change.
From static catalogs to intelligent product orchestration
Where Generative AI helps banks summarize information or respond to prompts, Agentic AI can assist, inform and orchestrate actions across systems to help achieve defined outcomes.7 In a product context, this means moving beyond static catalogs toward intelligent product orchestration - banking products assembled from approved components, guided by governed recommendations and supervised workflows.
Consider a small business experiencing a seasonal surge in demand. Rather than waiting for the owner to apply, an Agentic AI capability working alongside a modern core can identify the emerging liquidity need, evaluate the customer's financial position, assess risk, recommend a suitable lending structure and present it for appropriate review before a tailored offer is made. Retail customers approaching a life milestone could receive product configurations simulated from preconfigured components within seconds, with eligibility, pricing, risk and compliance guardrails explicit in the workflow.7
This is not personalization in the traditional sense, but the ability to recommend a relevant product configuration for one customer, at one moment in time, using approved product building blocks. Research suggests that tailoring products this way can drive revenue gains of 10% or more,5 while the use of Agentic AI could increase consumer retention rates by around 25%.6 These are structural (not marginal) uplifts in how banks generate value from their customer base.
Why the core matters more than ever
The promise of AI-augmented banking depends on one uncomfortable truth: intelligence is only as effective as the platform beneath it. AI systems require clean, unified, real-time data, clear workflow context and the ability to work with existing systems of record. Traditional cores, built on mainframes and rigid product architectures, were built to process transactions reliably - not to support supervised agentic workflows that assist product teams and relationship managers at scale.7 Legacy cores also struggle with volume: an estimated 80% to 90% of banking data exists in unstructured formats that resist conventional automation.7
This is why the core platform has re-emerged as one of the most strategic decisions a bank can make. Modern cores such as Finastra Essence are designed around the foundations AI requires: open APIs, cloud-native scalability, composable product frameworks, unified customer data and embedded analytics. Essence has been shown to reduce time to launch new products by up to 60%,8 giving banks the agility needed to compete in a market where product cycles are accelerating. Without this foundation, the promise of AI-augmented banking remains theoretical.
From products to financial experiences
As AI capabilities mature, the notion of a "product" itself will begin to evolve. Customers will not experience a mortgage, a savings account or a business loan as separate offerings. They will experience adaptive financial journeys - lending structures that adjust with income patterns, savings programs that recalibrate as goals change, and business banking ecosystems that grow with the company they serve.
This transforms the role of the core banking platform. It remains the trusted system of record, while also becoming a foundation for innovation - capable of supporting more personalized experiences at scale, integrating third-party services through APIs, and enabling continuous product evolution. The product organization must evolve alongside it: from designing individual products to curating libraries of approved components that AI can help assemble and recommend, with governance, risk, pricing, auditability and human oversight built into the flow.
The road ahead
The banks that will lead the next decade will not be defined by how loudly they adopt AI, but by how deliberately they apply it to the workflows that matter. The competitive frontier is shifting from channels and features to intelligence, adaptability and trust. Winning institutions will combine modern core banking technology, governed recommendations, supervised orchestration and composable product design to create financial experiences that feel genuinely relevant to each customer.
Agentic AI has the potential to move the industry beyond broad personalization and toward more precise, contextual individualization - banking where every customer receives product options that are better aligned to their needs, circumstances and timing. Realizing that vision requires a core banking platform capable of supporting AI safely: with clean data, strong guardrails, explainable recommendations and clear supervision. That is where the journey begins, and that is why the product agenda has become one of the most strategically important conversations in banking today.
References
1. "How to Improve the ROI of Personalization at Scale in the Era of AI." Forrester, May 2025.
2. "Over Half of Banking Executives Struggle with Data Silos: Report." Asia Banking & Finance, December 22, 2024.
3. Corey Wrinn. "How to Know What Your Customers Need Before They Do." The Financial Brand, November 19, 2024.
4. Shital Chheda, et al. "Five Ways to Drive Experience-Led Growth in Banking." McKinsey & Company, May 2, 2023.
5. Sonia Brodski, et al. "What Does Personalization in Banking Really Mean?" BCG, March 2019.
6. "Top 100 Agentic AI Facts & Statistics [2025]." Digitaldefynd, 2025.
7. Finastra Agentic AI Whitepaper Series, Universal Banking (2025): "Banking on Intelligence: Agentic AI is Here"; "Smarter Support, Deeper Customer Connections"; "Agentic AI Unlocks Hyper-Personalization for Modern Banks"; "Agentic AI Accelerates a New Chapter in Banking Efficiency"; "The Last Mile to Autonomous Banks".
8. "The Core Banking System That Makes You Customer-Relevant in a Digital World." Finastra, 2018. Retrieved from https://www.finastra.com/sites/default/files/documents/2018/04/brochure_fusion-essence-solution-overview.pdf
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