LendingMetrics Secures Morses Club Partnership and Unveils Major ADP Platform Upgrade

LendingMetrics has secured a partnership with Morses Club’s Home Collected Credit division to implement its Auto Decision Platform (ADP). This deal, coupled with a technical upgrade allowing lenders to integrate legacy risk models written in Python and SAS, signals a shift toward more flexible, hybrid credit decisioning environments for high-frequency consumer lenders.

What was announced

Morses Club selected LendingMetrics following a competitive tendering process supported by a series of face-to-face product and requirements workshops. The lender migrated to the Auto Decision Platform (ADP) to handle customer affordability assessments and responsible lending checks for its Home Collected Credit division. During the transition, Morses Club operated its legacy system in parallel with ADP to verify that the new solution delivered promised performance improvements. The implementation specifically introduced new digital capabilities for bank verification and customer identity verification.

Simultaneously, LendingMetrics launched a significant update to ADP. The platform now features a Universal Risk Model Adaptor, which allows credit risk professionals to incorporate existing risk models built in external programming languages—specifically Python, R, SAS, PMML, and JavaScript—into the automated decisioning workflow. This no-code engine allows for real-time manipulation of decisioning logic for KYC, fraud, and affordability without requiring lenders to abandon years of investment in proprietary in-house models. The upgrade is designed to bridge the gap between heavy historical investment in predictive models and the need for modern, automated execution, allowing for full interaction with ADP’s existing feature set.

"Many lenders have invested heavily over the years building and perfecting powerful and predictive risk models in other native languages. This upgrade means that for the first time we can ensure these very useful models are part of an automated decisioning process, making the job of credit risk teams much easier."

David Wylie, Commercial Director of LendingMetrics

The companies involved

LendingMetrics is a UK-based fintech specializing in credit decisioning and data solutions. The firm’s flagship product, the Auto Decision Platform (ADP), is designed to serve a broad spectrum of credit verticals, including banking, mortgages, commercial lending, consumer credit, and car finance. LendingMetrics has positioned itself as a provider of no-code technology, allowing risk teams to adjust logic and engine compilation capabilities on demand without deep developer intervention.

Morses Club is a major player in the UK’s home-collected credit market. Its Home Collected Credit division focuses on providing small, short-term loans to consumers, often those who may be underserved by mainstream banking. The company has been undergoing a digital transformation to modernize its traditional face-to-face lending model, integrating more robust affordability and identity verification tools to meet evolving regulatory standards for responsible lending. This shift is part of a broader move within the sub-prime and near-prime sectors to adopt more sophisticated digital stacks while maintaining the customer-centric focus of traditional home-collected credit models.

What FF News has reported before

FF News has tracked LendingMetrics’ steady expansion across the UK financial services sector. In 2025, the firm secured partnerships with Chorley Building Society to digitize their decisioning and with Camco Finance to automate specialist vehicle lending. The company’s market standing was further highlighted by its seventh consecutive Technology Partner of the Year win in 2026. More recently, FF News reported on the firm’s internal growth, including the appointment of Jamie Land as Head of Presales to further drive credit risk innovation.

What this means

This announcement highlights a critical tension in fintech: the struggle between legacy stability and modern agility. By allowing lenders to wrap existing Python or SAS models in a no-code interface, LendingMetrics is addressing a major barrier to digital transformation. Large lenders are often hesitant to migrate because they cannot afford to lose the nuanced risk logic built over decades. This move puts pressure on all-or-nothing SaaS providers who require clients to rebuild their logic from scratch. For the industry, it suggests that the future of credit risk isn't just about new algorithms, but about the interoperability of old data with new delivery systems.