Modernizing Clearing Infrastructure Using AWS Countdown with M1 Finance

Founded in 2015, M1 is a digital wealth management startup that provides investment, banking, and lending services to consumers. The company manages nearly 10 billion dollars in assets and serves over 300,000 customers. Despite this large footprint, M1 is a lean operation with 180 employees.

Historically, M1 relied on a third-party clearing service to facilitate the proper settlement of trades and the transfer of funds between buyers and sellers. However, as M1 grew, this third-party service limited the company’s ability to customize financial solutions and launch new features. In turn, these limitations prevented M1 from delivering an ideal customer experience.

M1 needed more control over the clearing process, but it saw that becoming a self-clearing operation would be a complex undertaking. “Clearing is complex and requires significant technology, regulatory compliance, and capital,” says Simon Lam, vice president of platform engineering at M1. “That’s why very few companies self-clear.”

M1 wanted to create an internal clearing system and bring those capabilities to the cloud, where the company hosted many of its other operations. However, its small engineering team needed additional support to create a solution that was efficient, agile, and simple to implement.

Since its founding, M1 has relied on AWS services and support to help level up its capabilities and deliver a better experience for its users. The company chose to deepen this relationship and use AWS Countdown for support and guidance during the migration. AWS Countdown is a feature of AWS Enterprise Support, a comprehensive suite of resources that includes proactive planning, advisory services, automation tools, communication channels, and 24/7 expert support.

M1’s journey to a self-clearing firm was a multiyear undertaking. The process began with its legacy books and records database. The startup had acquired third-party software that included an SQL Server environment; to optimize this system, M1 migrated it to Amazon Relational Database Service (Amazon RDS), a simple-to-manage relational database service optimized for total cost of ownership. Through AWS Countdown, M1 gained crucial support.

The AWS team performed an initial architecture review, where M1 received detailed recommendations on scalability, operational efficiency, and resiliency. Then, the startup attended sessions for performance testing with a specialist in Amazon RDS for SQL Server, which companies can use to set up, operate, and scale a SQL Server database in the cloud with just a few clicks. The AWS account team worked closely with M1 to verify and raise service limits in advance to prevent potential issues and verify that the Amazon RDS instance could handle the startup’s heavy workloads.

Next, M1 built out the rest of its clearing architecture, adopting both Amazon Elastic Compute Cloud (Amazon EC2), which offers the broadest and deepest compute platform, and Amazon Elastic Kubernetes Service (Amazon EKS), the most trusted way to start, run, and scale Kubernetes, to support diverse workloads. Throughout this build phase, the AWS team acted as an extension of M1’s lean engineering team, providing guidance and expertise to help them navigate the project’s complexities.

“The fact that we are a small startup did not affect the success of this project,” says Lam. “The AWS team has done such a great job of understanding our context and needs.”

Additionally, M1 adopted Amazon Simple Storage Service (Amazon S3)—which is built to retrieve any amount of data from anywhere—as its storage service. With the new clearing system in place, the startup was ready to migrate over 300,000 customer accounts off the third-party service. To mitigate risk, M1 conducted the migration in three phases between July and October 2023. Through AWS Countdown, M1 gained on-demand access to AWS experts, who were ready to take action if any issues arose. After the successful completion of the three phases, M1’s migration to AWS was complete.

With better control over the clearing process, M1 can now optimize the system according to its specifications and introduce new revenue-generating features, such as securities lending. The company has vastly improved the customer experience since the migration, especially around tax filing. M1’s user tax data correction rate has improved significantly from 30 percent to 3 percent, which amounts to a 90 percent reduction. Additionally, the company’s brokerage business has doubled its revenue by removing the need to pay fees to the third-party clearing service.

By becoming a self-clearing operation on AWS, M1 is in a strong position to compete with larger fintech companies and further strengthen its offerings. The startup can optimize its balance sheet, offer promotions, and continue innovating on new products and features thanks to the control and agility it has brought to its system. As it moves forward, M1 will continue to use AWS services and expertise to support its growth journey.

“We’re interested in working with people who are invested in our success,” says Lam. “Whether it’s through promotions or continuing to improve our clearing system, we’re going to keep building and improving. We’ll continue to benefit from the success of AWS through our ongoing work together.”