Think about a medium or small business that needs to transfer funds to the other side of the world. The fees incurred during payment processing are decided by the bank and the business has very little influence over the amount of fees taken by the bank, or the route that the payment takes. Very often the fee can be instrumental in influencing the business’ decision in how to transfer the payment, and currently the customer cannot influence that decision.
All this is about to change with the adaption of FeeWize, a machine learning based platform that puts the power to decide in the hands of the customer. Based on huge amounts of payment data, the machine learning algorithm takes a two phased approach – first calculating the correspondent via which the SMB’s bank will process the payment, in conjunction with the clearing scheme; and then calculating the fees for each one of the viable correspondents.
The SMB will then have full visibility of the fee amounts and when the payment will arrive at the receiver’s bank. Based on liquidity and business management considerations, the SMB can decide how to route the payment.
Built With
- auzre
- eclipse
- ffdc
- java
- javascript
- machine-learning
- python
- rest-api
- spring-boot
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