Digital banking technology provider Plumery AI has introduced "AI Fabric," a new offering poised to transform how financial institutions integrate artificial intelligence. This solution addresses the persistent challenge of embedding AI into daily banking functions while steadfastly upholding governance, robust security, and regulatory compliance.
Standardizing AI Deployment in Banking
Plumery AI positions "AI Fabric" as a standardized framework for connecting generative AI tools and models with core banking data and services. The company asserts this product aims to lessen reliance on custom integrations, fostering an API-first, event-driven architecture designed for scalability.
The financial sector widely recognizes this integration hurdle. Despite significant investments, many AI deployments remain limited. McKinsey research highlights that banks often struggle to move pilots to production due to fragmented data and legacy operating models. The consultancy advises that enterprise-level AI adoption requires shared infrastructure, consistent governance, and reusable data assets.
Ben Goldin, Plumery AI's founder and chief executive, emphasized that financial institutions demand real production use cases that enhance customer experience and operations, without compromising governance, security, or control. He noted that the event-driven data mesh architecture redefines how banking data is utilized, avoiding yet another AI layer on fragmented systems.
Overcoming Data Fragmentation
Fragmented data estates pose a significant barrier to operational AI in banking. Legacy core systems alongside newer digital channels create silos, complicating each AI initiative with fresh integration, security reviews, and governance approvals, thus increasing costs and slowing delivery.
Studies corroborate that fractured data pipelines complicate decision traceability and heighten regulatory risk, particularly in areas like credit scoring and anti-money-laundering. Regulators mandate that banks explain and audit all AI-driven outcomes.
Plumery AI states its AI Fabric tackles these issues by presenting domain-oriented banking data as governed streams, enabling reuse across multiple applications. The company argues that separating systems of record from systems of engagement allows for more secure innovation.
AI's Growing Presence and Market Trends
Despite implementation challenges, AI is deeply embedded in many financial operations, with widespread application in customer service, risk management, and compliance. Examples include AI-powered chatbots for inquiries and machine learning models for credit risk assessment and fraud detection. These advanced applications rely on high-quality data flows, though integration complexity often limits smaller institutions.
Plumery operates within a competitive landscape of digital banking platforms, typically serving as orchestration layers. Its strategy aligns with an industry shift towards composable, API-centric architectures, allowing banks to integrate AI and third-party services incrementally. Partnerships, like with Ozone API, further enable rapid delivery of standards-compliant services.
Navigating Readiness and Regulatory Oversight
Sector readiness for large-scale AI adoption remains uneven; a Boston Consulting Group report found fewer than a quarter of banks prepared. Gaps persist in governance, data foundations, and operational discipline. Regulators respond with controlled experimentation environments, like the UK's regulatory sandbox initiatives, to foster innovation while reinforcing accountability.
For vendors like Plumery, the opportunity lies in delivering infrastructure that harmonizes technological ambition with regulatory realities. AI Fabric enters a market with clear demand for operational AI, where success hinges on demonstrating safe and transparent tools. Platforms showcasing technical flexibility and governance adherence are poised to become pivotal in digital banking’s next phase.
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Source: AI News
