AI powered transaction analytics firm, Fuse, has enhanced its offering with the introduction of a new Income Verification Tool, which uses transaction data to provide lenders with detailed insight and probabilistic estimates into the income streams of prospective borrowers, while also painting a fuller picture of their financial position in real time.

The tool is particularly valuable when assessing the affordability and creditworthiness of individuals with non-traditional income patterns - for example those who are self-employed or part of the gig economy. Without an ongoing single source of income as a salaried employee would have, this group is far harder for a lender to verify and assess, meaning they may be more at risk of being unfairly excluded from accessing credit.

The solution, which builds upon Fuse’s existing transaction enrichment capabilities, uses advanced machine learning and Natural Language Processing to provide detailed insight into a person’s financial situation. It provides lenders with a probabilistic estimate of an individual’s income, enabling the lender to make an informed decision even in the case of an inconsistent salary. 

This insight empowers lenders to make fast, accurate and responsible lending decisions using up-to-date transaction data, without being solely reliant on the information associated with the traditional credit assessment process. As a result, lenders are able to increase acceptances and grow their customer base, while remaining confident that they are doing right by their customers. 

Using technology to assess affordability in this way allows lenders to enter new - and often underserved - markets quickly, and offer credit options in a responsible way that supports the long-term financial health of the borrower. 

The model is trained using data from the Pave app, a subscription-based, credit health builder app which caters to underserved groups in the credit market, e.g. gig economy workers, which is a key contributor to Fuse’s industry leading understanding of lending to this sector. The tool operates on data from more than 20 banks, all of which have different standards and conventions for how transaction data is formatted.

Sho Sugihara, CEO and Co-Founder, Fuse by Pave, comments: “Technology is transforming the financial sector for the better, facilitating the development of models that are more inclusive, safer, and built around the best interest of consumers. We are committed to driving positive change and the launch of the Income Verification Tool is the next step in this journey, promising to make credit more accessible and affordable for those with non-traditional income patterns.”