Our Solution
Fused GPT with RNN and Transformer architectures to model real-time transactional behaviors.
Trained with 125+ billion historical payment flows and dynamically analyzed card holder behavior to detect anomalies.
Heatmap-based scoring algorithms for intelligent prioritization of suspicious activities.
Outcomes Delivered
300 %
Improvement in fraud detection accuracy across high risk segments.
<50 ms
Real-time decisioning enabled with <50 ms detection across billions of transactions.
20 %
Reduction in manual review time for Tier 1 fraud investigation teams.
125 bn
Reduction in manual review time for Tier 1 fraud investigation teams.
Technical Highlights
A scaled delivery team of engineers, scientists, DevOps, analysts created a hybrid AI architecture combining rule-based logic with unsupervised neural learning.
- Cloud-native deployment using containerized microservices deployed on Azure Kubernetes Service in 8 weeks.
- Seamless integration with existing risk, compliance, and transaction platforms.
- 50 ms decision latency achieved through real-time transaction adjudication.
About Us
In the age of AI, rules of business are being rewritten. At ShimentoX, we’re at the heart of this transformation.
We harness the power of human ingenuity and AI to turn complexity into opportunity and innovation into reality. With Cloud as our backbone, AI as our catalyst, and data as our driving force, we create intelligent solutions that redefine what’s possible.
Client
A Leading Global Bank
Challenge
A top 500 global financial institution sought to modernize its fraud detection framework to operate at real-time speeds. With transaction volumes exceeding billions per day, the client needed a solution that could intelligently flag suspicious activity, learn from behavioral patterns, and significantly reduce the dependency on manual investigation teams.
Category
Fraud Detection
Industry
Banking
