Banking & FintechBuilt By: FalconicLab
Building a Sub-50ms Real-Time Fraud Prevention Protocol
Internal R&D building a high-throughput fraud-scoring pipeline that holds sub-35ms inference latency at simulated loads of 50,000 transactions per second.
84%
Fraud Miss Reduction
28ms
Inference Speed
50k TPS
Load Test Throughput
The Enterprise Challenge
Legacy rule-based fraud engines common in fintech stacks run 100-250ms per transaction, which is too slow for real-time authorization at high volume and produces high false-positive rates.
The Falconic Engineering Solution
We built an in-memory feature store paired with an ONNX-optimized inference pipeline running on Cloudflare Edge workers and Kafka event streams, detailed further in our published experiment.
Quantifiable Results & ROI
Reduced simulated false-negative fraud misses by 84% versus a rule-based baseline
Held average inference scoring latency to 28ms under load
Sustained target throughput with zero dropped events during load testing
Technologies Deployed
PyTorchONNX RuntimeApache KafkaCloudflare WorkersRedis Feature Store