Fair Finance Revolutionises Lending with LendingMetrics Automated Decisioning

Fair Finance has transitioned its underwriting process from manual operations to automated decisioning by implementing LendingMetrics’ Auto Decision Platform (ADP). This move aims to increase efficiency for the specialist lender, which focuses on providing credit to individuals typically excluded from mainstream financial services, while maintaining human oversight for complex cases.

What was announced

Fair Finance selected LendingMetrics following an open tender process. This selection followed an option analysis conducted by an external consultancy to evaluate various technology providers in the market. The implementation involves the Auto Decision Platform (ADP), a system designed to transition the lender from a 100% manual underwriting process to a streamlined, automated workflow. The technology is intended to handle "black and white" decisions—those that clearly meet or fail the lender's criteria—automatically. This shift allows the internal underwriting team at Fair Finance to dedicate their time to reviewing complex applications that still require a human touch or fall into "grey areas" of credit risk.

The ADP system is described as future-proofed, meaning it is designed to accommodate ongoing changes to decisioning logic and the integration of new third-party data suppliers as the lender's requirements evolve. By adopting this technology, Fair Finance aims to achieve a higher level of operational efficiency while maintaining its focus on serving those excluded from mainstream financial services. The deployment follows a trend of specialist lenders seeking to modernise their legacy stacks to better handle increasing application volumes without a linear increase in headcount.

"Fair Finance was keen to find technology that would automate its underwriting process and take lending to a new level of efficiency. It now has in place a future-proofed system that allows for ongoing decisioning changes and new third-party data suppliers."

David Wylie, Director of LendingMetrics

The companies involved

LendingMetrics is a specialist in credit risk technology and decisioning software, providing tools that allow financial institutions to automate their lending processes. The company’s flagship product, the Auto Decision Platform (ADP), is widely used across the UK financial sector to manage credit risk and data integration. LendingMetrics operates as an independent technology provider, focusing on modular systems that can be updated as regulatory and market conditions change. Fair Finance is a social enterprise and lender based in the United Kingdom, specifically focused on financial inclusion. The firm provides personal and business loans to individuals and micro-enterprises that are typically unable to access credit from high-street banks. Historically, Fair Finance has relied on manual underwriting to assess the risk of borrowers who may have non-standard financial backgrounds or limited credit histories. The adoption of automated decisioning marks a significant evolution in its operational model, as it seeks to scale its lending capacity while continuing to serve a vulnerable or underserved demographic.

What FF News has reported before

FF News has tracked LendingMetrics’ expanding influence in the automated decisioning space through several recent partnerships. In 2025, the company secured agreements to automate specialist vehicle lending for Camco Finance and provided digital decisioning tools for Chorley Building Society. The firm’s technical standing was further highlighted when it was named Technology Partner of the Year for the seventh consecutive time in August 2026. More recently, in November 2026, the company moved to strengthen its leadership team by appointing Jamie Land as Head of Presales to drive further innovation in credit risk.

What this means

This implementation highlights a broader shift in the specialist lending sector, where the high cost of manual underwriting is becoming a significant barrier to scaling operations. For firms like Fair Finance, the challenge lies in automating processes without losing the nuance required to serve "thin-file" or credit-impaired borrowers who are rejected by mainstream algorithms. This move puts competitive pressure on other niche lenders to adopt similar hybrid models—automating the straightforward approvals and rejections while reserving human expertise for complex cases. It also raises questions about the long-term role of human underwriters as automated platforms become increasingly sophisticated at interpreting alternative data points that previously required manual judgment.