AI and data reshape the commercial credit lifecycle

Chartis Research’s Credit Lending Operations 2026 report finds commercial lenders are shifting from siloed lending systems to integrated, AI-driven end-to-end platforms that use real-time analytics and API-enabled ecosystems to speed underwriting, strengthen risk monitoring and improve loan servicing.

The report attributes the change to pressure on banks to raise efficiency, accelerate credit decisions and deliver a smoother borrower experience as market conditions and client expectations change. Chartis identifies growing investment in artificial intelligence, data integration and API connectivity as the main enablers of more cohesive lending operations that link data, processes, systems, partners and frontline staff.

Banks and credit teams are prioritising AI use cases with immediate operational impact. These include automated document processing in underwriting, rules-based and machine-learning models for credit assessment, workflow automation to reduce manual handoffs, and continuous portfolio monitoring for earlier risk detection. Real-time analytics feed models with up-to-date transaction, payment and covenant data so decisions reflect current exposures rather than periodic snapshots.

API-enabled ecosystems allow institutions to connect internal systems and third-party services without wholesale replacement of legacy platforms. Wrapping older systems with APIs lets lenders introduce modern user interfaces, integrate external data providers and streamline partner workflows while keeping core banking systems intact. Chartis highlights this incremental modernisation approach as a practical path for banks that want to improve operations without disrupting ongoing business.

Operational change extends beyond technology. The report describes the need for an operating model that fosters cross-functional collaboration and integrates external partners where appropriate. Successful programs combine data governance, shared processes and clear accountability so information flows across origination, underwriting, portfolio management and servicing. Risk, compliance and IT functions are expected to coordinate as new analytical methods and automation are deployed.

Better data integration gives institutions greater visibility into customers and exposures. Consolidated information makes it easier to spot concentration risks, track borrower behaviour and identify cross-sell opportunities. Continuous monitoring tools built on AI and analytics can flag early signs of portfolio deterioration and support more timely remediation or restructuring decisions.

A webinar in association with FIS will discuss how real-time analytics and API ecosystems affect decision-making in commercial lending. Panelists include Dale Glajchen, vice president and head of commercial loan servicing and syndication at FIS; Emily Bogan, global head of lending origination and credit at FIS; and Anish Shah, research director at Chartis Research. Sharon Kimathi will moderate.

The Chartis report finds lenders are moving beyond isolated point solutions toward integrated platforms where automation, analytics and connectivity operate across the full credit lifecycle. The report documents modernisation strategies that allow institutions to evolve existing systems rather than replace them entirely.