Case Study: M1 Finance accelerates fraud detection and secures transactions with Rackspace Technology

M1 Finance secures transactions and accelerates fraud detection on AWS

M1 Finance, a fast-growing online financial services company, was collecting rapidly increasing volumes of user and system data that its legacy AWS-based Redshift warehouse and S3 data lake couldn’t query efficiently. Data silos and a manual, time-consuming log-review process hindered real-time visibility into login activity and slowed fraud detection, so the company needed a scalable, cost-effective pipeline to capture, process, and enable ad hoc queries on authentication and event data.

Onica (a Rackspace Technology company) built a scalable AWS solution using Amazon S3, AWS Glue, Amazon Athena, Amazon Redshift Spectrum, and AWS Lambda to compact, catalog, partition, and expose login data for fast querying. The new pipeline reduced multi-hour manual processes to near real-time, let analysts run ad hoc SQL queries without engineer intervention, added cost controls and alerts, and materially improved fraud-detection speed, scalability, and operational efficiency.

M1 Finance

Richard Whaling

Lead Data Engineer