  This paper discusses the system architecture design and deployment of
non-stationary multi-armed bandit approaches to determine a near-optimal
payment routing policy based on the recent history of transactions. We propose
a Routing Service architecture using a novel Ray-based implementation for
optimally scaling bandit-based payment routing to over 10,000 transactions per
second, adhering to the system design requirements and ecosystem constraints
with Payment Card Industry Data Security Standard (PCI DSS). We first evaluate
the effectiveness of multiple bandit-based payment routing algorithms on a
custom simulator to benchmark multiple non-stationary bandit approaches and
identify the best hyperparameters. We then conducted live experiments on the
payment transaction system on a fantasy sports platform Dream11. In the live
experiments, we demonstrated that our non-stationary bandit-based algorithm
consistently improves the success rate of transactions by 0.92% compared to the
traditional rule-based methods over one month.
