10076260Responsible AI for responsible lendersClosedGrant for R&DInnovate UKNestEgg connects borrowers to responsible lenders. The NestEgg platform is one place for people to check whether they are eligible to join as well as qualify for loans from responsible lenders across the UK. Once someone has found a suitable loan, NestEgg supports their lender to make a fair credit decision. This process will improve by using AI to combine credit reference and open banking information. This enables lenders to make consistent and fairer decisions in double quick time. But more can be done. Currently the data sources for credit decisioning are in too many different places. A manual review to cross reference the data sources takes too long and is subject to human error. Furthermore, the Financial Conduct Authority found that insufficient credit information leads lenders to make decisions that do not reflect an individual's financial circumstances. As a result, consumers are more likely to have access to credit they can't pay back or denied credit they could afford. This project uses Artificial Intelligence to make decisions based on the interplay between these distinct data sets for responsible, non-profit lenders. Over a five month period 20+ SME lenders will work together using AI to automate credit decisions by cross referencing data sets, with an initial focus on affordability assessment because of the cost of living crisis. The project will evaluate: a) the proportion of lending decisions overridden by humans b) whether AI fairly automates affordability assessment c) how AI can help lenders meet regulatory requirements d) the extent to which sharing information based on these results improves the credit profiles of declined applicants. This initial small scale experiment uses a fraction of the data. It simply isn't possible for a human to consider every way in which data could be used to support automated decisioning. We'll therefore also consider ways to introduce machine learning so we're better able to respond to changes in the market and economy whilst carefully balancing the risks of automation to ensure continued transparency in how decisioning algorithms work. Our lender clients serve a diverse population. We must ensure that AI does not undermine their ability to support those from disadvantaged backgrounds.