If you’re selling online, chances are that 10% of your transactions are routed to manual reviews.
This is a costly and inefficient process, hurting results in more than one way. The question is can we automate these tasks safely, without increasing exposure to fraud.
FUGU has an innovative approach, automating manual tasks working on them after the payment but before the actual risk is assumed, increasing conversion, reducing churn, and preventing fraud.
How do we do it?
FUGU continues to track transactions after the payment, engaging flagged ones according to the relevant payment scenario, i.e. our system “understands” the transaction, its incongruent elements included, initiating actions required to complete the transaction safely.
Instead of rejecting transactions, we collect, evaluate, and store the evidence required, attempting to complete the transaction within the sphere of customer care. As we get to know the customer and the transaction better, true fraud distinguishes itself from valid complexities as indicated in a variety of signals we collect and process.
Most recently, we have been chosen by a fast-growing merchant on top of Shopify to do exactly this, reduce their post-payment manual labor costs without compromising revenue. Because of the nature of the business, they had to route an inordinate amount of transactions to manual reviews, for evidence and identity assurance. We implemented our solution, automating card scans, and selfie id’s with ML.
These tasks are completed after the payment, saving up to 40 man-hours a month but also applying reviews to more transactions, reducing the merchant’s overall exposure to chargebacks and disputes.