68637Cocoon 'buy now, pay later' platform developmentClosedStudyInnovate UKBuy now, pay later (BNPL) means a consumer can buy something today and pay for it in the future. This is great for both consumers and businesses: consumers can spread the cost of high-value items into easy-to-manage instalments and, because of this, businesses that offer BNPL see up to a 30% increase in sales. Businesses work with a BNPL finance provider who fund the purchase and collect the repayments from the consumer in the future. Many businesses offer BNPL interest-free to consumers -- the business pays the interest and this cost is offset by the increased sales they experience. This is a win-win for businesses and consumers: businesses generate more sales and consumers have access to interest-free credit. To determine which consumers they should provide BNPL terms to, finance companies perform 'credit checks' on potential consumers. A credit check is used to check a consumer's credit history and lets lenders know a consumer has used credit responsibly in the past, giving them an idea of how likely the consumer is to make future repayments. However, there are 10-14m consumers in the UK (20-25% of the adult population) that find it difficult to access credit from mainstream BNPL providers (PWC). This is because these consumers might, for example: not have previously applied for credit or have a mildly adverse credit history. These consumers are often rejected for interest-free BNPL even though they might be creditworthy and able to make the repayments. This is bad for businesses and consumers: businesses lose out on extra sales and consumers lose access to interest-free finance, often seeking alternative sources of high-interest finance to fund their purchases. The aim of our project is to R&D a technology platform that will use alternative sources of data, only recently made available through open banking, and machine learning to enable businesses to determine if they can provide BNPL to consumers rejected by existing providers. Our product disrupts BNPL by cutting-out the lender, providing a lower cost service to businesses. In our model, the merchant provides interest-free credit and takes the lending risk to benefit from the extra custom, using our technology to make decisions in a risk-managed way. From our feasibility study, we estimate that using open banking transaction data coupled with machine learning will allow businesses to serve up to ~20% more consumers profitably with BNPL. This would facilitate an additional £2bn of spending in the economy.