Banks adopt AI and APIs to integrate commercial lending

Banks are replacing isolated lending tools with integrated end-to-end platforms that combine artificial intelligence, real-time analytics and API connectivity. Financial institutions aim to shorten credit decision times, increase oversight of loan exposures and automate routine servicing tasks.

Lenders cite pressure to raise efficiency, accelerate credit decisions, tighten risk monitoring and meet changing borrower expectations. Rather than replace legacy systems, many institutions are linking existing systems, data and external partners into a single operating model that provides consistent, visible and auditable credit processes from origination through servicing.

Institutions are targeting AI where it can change day-to-day work: automated underwriting and credit assessment to reduce decision lag, workflow automation to cut manual handoffs, continuous risk monitoring to detect shifts in exposure, and servicing automation to handle routine borrower interactions. Real-time analytics and API-enabled data feeds bring transaction, borrower and market information together so underwriters and portfolio managers can act on current data.

Advances in data integration are allowing banks to combine customer records, loan systems, accounting entries and third-party feeds into a single view of borrower credit and portfolio health. These combined data sets enable risk scoring across portfolios, identification of concentration issues, and routing of tasks to internal teams or external service providers based on defined criteria.

Modernisation strategies commonly follow an incremental path to preserve operational resilience. Banks are adding API layers over legacy systems, building shared data services, implementing modular automation around specific lending stages and putting governance in place to control data flows and model use. The goal for many institutions is to improve efficiency and portfolio performance without disrupting daily lending activity or requiring full system replacement.

Findings in the Chartis Credit Lending Operations 2026 report have focused industry discussion on moving from fragmented point solutions to unified lending operations where intelligence, automation and connectivity work together. An upcoming industry webinar associated with FIS will feature Dale Glajchen, vice president and head of commercial loan servicing and syndication at FIS; Anish Shah, research director at Chartis Research; and Tim Probst, global head of commercial loan servicing, enterprise and client strategy at FIS. Sharon Kimathi will serve as moderator.

Lenders continue to prioritise identifying high-impact AI use cases, improving data integration and adapting operating models to support more continuous, data-driven credit decisions while maintaining operational stability.