Focusing on SMEs with three to 50 employees, particularly those in less well-serviced regions, CFIT aims to explore how traditional and alternative commercial credit data can be integrated to enhance lending decisions.
The project seeks to assess whether technologies like Open Finance and real-time data sharing can offer lenders a more comprehensive understanding of a business’s creditworthiness.
Utilizing alternative data for credit evaluations
CFIT intends to combine traditional credit metrics with non-traditional sources such as transaction records, cash flow patterns, income trends, payment histories, and operational performance over time. This approach is designed to determine if applications previously rejected based on standard credit assessments might have been eligible under alternative criteria.
Officials from CFIT noted that this initiative builds upon previous Coalition efforts aimed at improving banks’ ability to extend loans. The current phase focuses more on the demand side by providing clearer insights into how businesses can improve their financial data to increase their chances of securing funding.
According to a recent British Business Bank study, 60% of SMEs that avoid seeking finance are not aware of available options. Additionally, research from Small Business Economics indicates that over 70% of SMEs discourage reapplying for loans after an initial rejection. This hesitation is reflected in the 20% real-terms decline in SME lending over the past decade.
To address these issues, the Coalition plans to develop a dashboard tool that consolidates relevant financial indicators affecting lending decisions. The goal is to provide SMEs with a more comprehensive and accessible view of their financial profiles, helping them understand how lenders assess them and what changes they can make to improve future applications.
Participating institutions include major banks and payment networks such as Lloyds Banking Group, HSBC UK, and Mastercard. The regional breakdown will also be part of the research, aiming to identify areas where credit access challenges are most significant.