AI and data reshape the commercial lending lifecycle

Banks are replacing siloed loan systems with integrated end-to-end platforms that combine artificial intelligence, real-time analytics and API connectivity to change how credit is originated, assessed, managed and serviced.

Lenders face pressure to speed credit decisions, reduce operating costs and strengthen oversight while meeting higher borrower expectations. Many institutions are moving from disconnected point solutions to operating models that link data, processes, systems, partners and staff into a single lending environment.

Chartis Research’s Credit Lending Operations 2026 report identifies a shift from fragmented processes to unified operations that increase visibility and consistency across lending activities. The report highlights practical AI applications such as automated underwriting and credit assessment, document and workflow automation, ongoing portfolio monitoring and enhanced servicing tools.

An industry webinar hosted with FIS will examine these shifts. The panel includes Dale Glajchen, vice president and head of commercial loan servicing and syndication at FIS; Anish Shah, research director at Chartis Research; Tim Probst, global head of commercial loan servicing, enterprise and client strategy at FIS; and moderator Sharon Kimathi.

Banks are prioritizing specific AI use cases that have clear data inputs and measurable outcomes, including faster initial credit decisions, reduced manual review and earlier detection of borrower stress. Chartis reports that AI is delivering benefits when applied to defined tasks rather than broad simultaneous rollouts.

Real-time analytics and API-enabled ecosystems are being used to connect internal records, third-party data and cloud services so decision-makers can see customer positions and exposures more clearly. APIs let banks integrate external partners-credit bureaus, accounting platforms and data providers-without replacing core systems, supporting faster and more consistent decisions and automating routine tasks while keeping human oversight for complex exceptions.

Modernization strategies emphasize incremental change: adding connective layers, API-led integration and targeted upgrades to join legacy systems with newer platforms. Institutions are piloting AI tools in limited areas, establishing cross-functional governance and scaling solutions that show measurable improvements in efficiency, risk management or portfolio performance.

Panelists will outline how lenders can prioritize use cases, design operating models to support information flow across the credit lifecycle and phase upgrades to avoid business disruption.