Banks build AI-powered end-to-end lending platforms

Banks are moving from disconnected point solutions to integrated lending platforms that combine data, processes, systems, partners and staff. Financial institutions are layering artificial intelligence, real-time analytics and API connectivity across the credit lifecycle to automate document processing, improve credit scoring in underwriting, support workflow automation, monitor portfolios and streamline loan servicing.

The Chartis Credit Lending Operations 2026 report found lenders face rising pressure to improve efficiency and borrower experience while operating in more complex market conditions. The report and industry practitioners identify AI use cases across underwriting, workflow automation, risk monitoring and servicing.

Real-time analytics and APIs link loan origination, credit-assessment and servicing systems so banks can use up-to-date customer and exposure data, run models continuously and route tasks across internal teams and external partners. That connectivity lets institutions add AI models on top of existing systems rather than replace core platforms.

An upcoming webinar in association with FIS will examine which AI use cases deliver the most impact across underwriting, automation, monitoring and servicing. Panelists will 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.

Banks pursuing modernisation report practical approaches such as integrating internal data sources to produce fuller borrower views, deploying API layers to connect legacy systems with new analytic tools, and prioritising automation where it reduces manual effort and improves model-driven decisions. Institutions are also testing the use of external data and third-party services in lending workflows without changing core operations.

Chartis describes the sector as moving from fragmented point-solution architectures to more unified lending operations, with the stated goal of greater visibility, consistency and agility across the loan lifecycle to manage portfolios and respond to borrower needs and shifting credit conditions.