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Lloyds Bank has deployed an applied intelligence platform to drive its cloud migration for lending infrastructure.
The platform, developed by FICO, has enabled the launch of a new cloud-based application viewer for underwriters and other teams.
The technology has also facilitated a significant bureau data upgrade in weeks rather than months.
The new platform uses real-time data ingestion and advanced analytics, which has helped the bank drive a 2.5 per cent credit card approval uplift, double new-to-bank consumer loan customers, and resolve over 50 system limitations.
The move comes after the bank struggled with its aging lending infrastructure, with fragmented systems creating inconsistencies across its digital channels, making it difficult to integrate new data assets for responsible lending, scalability, and sustainability.
Lloyds previously had over 20 on-premises applications and complex data flows in its legacy lending infrastructure.
The bank’s strategy required a large data mapping exercise to understand where derivations or changes to the data could be occurring through the various systems.
The exercise enabled the organisation to prepare downstream users of the data for changes, or amend the new data in order to not impact them at all.
“It became clear that our lending infrastructure was becoming a barrier to the strategic growth ambitions of the bank,” said Ian Rockliffe, head of consumer credit risk transformation, Lloyds Banking Group. “We needed the ability to scale to meet our customers’ needs within the digital channels.
“We also needed to bring in new data assets to support growth, sustainability and enhance our responsible lending position.”
Rockliffe went on to say that the new platform has enabled Lloyds to simplify its “whole technology estate” and implement a “market-leading” cloud-based infrastructure.
Lloyds also recently announced plans to migrate key data science and AI platforms to Google Cloud as it seeks to strengthen its AI capabilities.
The move has seen Lloyds migrate over 15 modelling systems to the new platform, including hundreds of individual models from the group’s on-premises infrastructure.
The collaboration is part of the bank’s broader transformation efforts focused on boosting customer service and operational efficiency through the integration of high-impact AI use cases.
