AI-Powered Transaction Monitoring for Miden

Business Problem

Miden’s transaction monitoring process required significant manual effort, leading to:

Operational inefficiencies due to high labor costs and time-consuming review processes.
Delayed fraud detection, increasing financial security risks.
Limited scalability, restricting Miden’s ability to handle growing transaction volumes efficiently.

About Miden

Miden is a modern issuer processor and banking stack that enables businesses to integrate financial features, including seamless payments, reconciliation, instant virtual cards, and account opening. They are on a mission to redefine financial transactions with enhanced security and efficiency. To improve fraud detection and streamline operations, Miden sought to implement an AI-driven transaction monitoring system.

Explore Now

Solution

goML partnered with Miden to develop an AI-powered Transaction Monitoring system leveraging AWS’s advanced infrastructure. This initiative automated fraud detection, enhanced real-time insights, and significantly reduced manual monitoring efforts.

1.

AI-Driven Analytics Dashboard – Built using Python, RDBMS, and AWS S3 to provide real-time insights into transaction patterns and anomalies.

4.

GenAI Training & Enablement – Equipped Miden’s team with AI adoption strategies for long-term scalability and operational efficiency.

2.

Automated Anomaly Detection – Machine Learning models identified suspicious transactions using predictive analytics, reducing manual intervention.

3.

Secure & Scalable Processing – Utilized AWS Lambda for serverless computing, AWS S3 for secure data storage, Postgres for structured data management, and Docker for containerized deployment.

Outcomes