M1 Finance secures transactions and accelerates fraud detection on AWS

Legacy infrastructure inhibits growth

M1 Finance’s platform was built on AWS prior to its engagement with Onica, a Rackspace Technology® company. The company had a data warehouse comprising an Amazon Redshift cluster managing just under 400GB of data. The cluster facilitates its internal analytics needs and serves as a clearinghouse for data from backend services as well as third-party vendors and other sources.

In addition to the data warehouse, M1 Finance has a data lake using Amazon S3 that serves as a staging ground for loading data into Amazon Redshift and as an archive store. However, the data lake wasn’t equipped with capabilities for ad hoc queries — a functionality M1 Finance was looking for to improve its fraud detection capabilities.

With rapid user growth, the company found it was collecting significantly higher amounts of data from internal systems than what could fit in its existing data warehouse. Handling such high data volume could get very expensive with traditional data warehousing.

Additionally, the company also had Java applications, which had accumulated data over many years, that could be highly useful for fraud analytics. This data was trapped in silos of legacy databases and it wasn’t able to find a solution to query a high volume of rapidly moving data with its existing system.

As an organization in the financial industry, M1 Finance takes user data security extremely seriously, and it’s imperative that its team has the ability to track system access and usage to detect and prevent fraud. The company’s existing process for reviewing system logs was manual and not scalable. As the volume of data and logs continued to increase, the company required a more efficient process to execute a task that is highly time-sensitive.

The M1 Finance team wanted real-time visibility into suspicious activity so it could respond as soon as possible. It learned about Onica from the AWS Jumpstart program and was impressed with the expertise and capabilities available at Onica. It found the team had insight and knowledge that could be valuable to M1 Finance’s needs.

Real-time scalability and efficiency

The new solution streamlined the process significantly, automating what was previously done manually over multiple hours to a practically real-time solution. The design of the solution provides scalability, low cost operation and integration with existing data sets.

Furthermore, the solution offers great flexibility, replacing the process of needing to queue tasks for an engineer with one where data analysts can perform ad hoc dynamic queries. M1 Finance business users now have the ability to build robust queries at scale and are able to address their multi-petabyte size data sources and return meaningful timely results. This provides a significant advantage in fraud detection where every minute reduced in processing time can mean proportionately greater success and improved security.

To help mitigate cost risk for M1 Finance, Onica built alerts for Amazon Redshift Spectrum and Amazon Athena. M1 Finance’s team was also pleased with the delivery of the solution that was carefully tailored to its existing practice and unique use case. The company felt confident about the way the team at Onica handed-off the solution, and educated the M1 Finance team in effective implementation and management.