To Scale or Not To Scale?

Initially, Core Capital Management & Research desired the necessary tools required to increase operational efficiency to rival that of its commercial competitors.

In this scenario, a single manager, managing various portfolios was trying to compete with many portfolio managers. Improving the current processes would require centralizing resources using a cloud-native approach.

Synergy Insights was tasked with designing, developing, and deploying the cloud infrastructure, utilizing Amazon Web Services (AWS).

For CCMR, the numbers are everything…

Synergy integrated API’s from various digital trading platforms, including Interactive Brokers and IEXCloud, to develop financial applications and models that give our product owners access to datasets.

These datasets are created using real-time pricing and fundamental data, which then funnel through an ETL process to finally be stored in a postgreSQL database.

The data is then queried and deployed into data science models using AWS SageMaker to find insights in equities and commodities.

From the fact findings, trade executions are then automated and processed using Lambda functions for the purpose of buying, selling and rebalancing of equities.

Architecture Diagram

1. Store API tokens from Interactive Brokers, IEXCloud, and other financial data platforms securely using AWS Secrets Manager.
2. Use Amazon API Gateway to create an endpoint for our AWS Lambda functions and connect to these APIs securely using the API tokens.
3. Use Lambda functions to access database credentials from Secrets Manager to connect
4. Automatically rotate API keys and credentials every 30 days for best practice.
5. Post real-time pricing and ticker data, using Lambda, to our internal PostgreSQL database from the endpoint, created using Amazon RDS.
6. Execute trade orders against the database and query results using Lambda functions and store transaction data in real-time into a data lake, using Amazon Simple Storage Service (S3).
7. Query data from the database using Lambda functions and then use AWS SageMaker to build, train, and deploy data science models based on findings.
8. Query data from logs stored in S3 to feed data models in SageMaker.
9. Send portfolio status reports to end users using Amazon Simple Notification Service (SNS) as the primary messaging service. (Add SNS to diagram and renumber steps)

How did we do it?

Centralized multiple API’s to a singular database, went from managing 100 portfolios to a singular methodology to execute trades based in the cloud that makes decisions serverlessly. Additionally,

How did it help?

During the 2021 Texas Blackout, CCMR’s infrastructure proved resilient due to multiple availability zones, a feature common with cloud infrastructure.

By utilizing AWS, Synergy is able to ensure that CCMR experiences substantial improvements in the following pillars:

1. Operational Excellence
2. Security
3. Reliability
4. Performance Efficiency
5. Cost Optimization

If you would like to learn more information about how Synergy Insights can help your business through cloud technology, please visit us at synergyinsights.io or you can reach out to us at solutions@synergyinsights.io!