Fraugster, an AI payment intelligence company, today announced the launch of their latest product, Alternative Credit Decisions, which allows Buy Now Pay Later (BNPL) and Enterprise merchants to approve more customers without increasing credit risk. There is a pressing need for a new approach because BNPLs are reporting much higher bad debt impairment rates than credit cards. For every $1 Bn of processing volume BNPLs write down $19.2 Mn of bad debt compared to $270k per billion for credit cards. At the same time, millions of good customers worldwide continue to experience service denials because BNPL providers and e-commerce merchants are unable to accurately determine their level of risk. This includes a significant proportion of returning shoppers who are treated as if they are buying something online for the first time. This is happening because credit decisions are missing important data.

Alternative Credit Decisions enriches BNPL credit scoring models with over 100 attributes that give a more accurate picture of a buyer’s true credit risk. These include highly valuable data points like a buyer’s positive transaction history, account history, purchase history and unpaid amounts. This is made possible by global network intelligence and real-time graph networks.

Christian Mangold, Fraugster CEO, says: “Our mission is simple, we want our customers to feel confident that they can trust the person they are approving to repay the amount they are borrowing. The positive results we are already seeing with trial customers make me confident that we can help the e-commerce ecosystem approve more customers without increasing exposure to loan defaults.”

Fraugster customers won’t only benefit from more accurate decisions, but also reduced costs. Currently, BNPLs and enterprise merchants broadly use credit bureau checks to increase their confidence in an approval decision and pay a fee for each check. Alternative Credit Decisions reduces the need for these checks altogether to save costs and improve accuracy. The product also helps customers rationalise other third party data vendor costs.