Ai+ Training

     Payments must go through entities called as gateways, which vary in configurations such as pricing, number of risk checks, etc. Routing a payment transaction through any gateway available would have been simpler if each gateway was equally likely to process the transaction successfully, and hence one of the available gateways could have been chosen at random. 

     Payment aggregators face the following issues: 

1. Firstly many gateways or server downtimes go unrecognised,

2. Secondly routing through random gateway might lead to a lot of

transactions getting failed which inturn leads to loss of revenue and hamper user experience. Routing a payment transaction through the best gateway from multiple gateways is crucial to increase the probability of a payment transaction being successful based on the gateway’s previous performance. 

      In the real world, the performance of the gateway is contingent on various factors related to the gateway and the payment method type being used for transactions which affect performance of the gateway continuously. Hence, there emerges a need to have smart routing

algorithms. Proposed Smart Routing system implements a continuous feedback capability analogous to reinforcement learning systems, and learns the relationship from historical data and selects the best possible gateway for a transaction that results in a successful transaction. 

      The fundamental aim is to choose a gateway based on its likelihood of being the best, given the availability of its associated gateway for that particular transaction. This engine is currently in production and has given 4-6% by points improvement in success rate across all payment methods (credit, debit, UPI, Net-Banking). This helps improve user experience by preventing failures and also improves the revenue of the payment gateway used.

Local ODSC chapter in Delhi, India