Background

Digital Alpha offers institutional investors and portfolio managers a comprehensive solution to improve their investment process through their Framework for Custom Factor Investing Implementation on AWS Marketplace Professional Services. This framework includes a modern data platform, decision support platform, and analytics platform. The modern data platform combines data lakes, data warehouses, AI/ML, and real-time data processing to deliver high-quality business analytics. The decision support platform analyzes information from various sources for faster decision-making. The analytics platform aligns factor models with strategies and uses MLOPs pipelines to operationalize them at scale. With this framework, clients can create custom models and applications, diversify factors with new data sources, and quickly make changes to their investment strategies. The system is fully automated, providing end-to-end factor investing management, from monitoring portfolios to adding new analytics or scenario analysis.

Features

• Unlock Custom Insights: Create custom models/applications and internal analytics from client defined factors.
• Diversify Inputs: Enhance diversification of factors by bringing in new data sources.
• Streamline Model Deployment: Ability to operationalize new strategize and models – both traditional and ML models.
• Automate Portfolio Optimization: Fully automated end to end factor investing system to help monitor the portfolios.
• Agile Adaption: Ability to quickly make changes either to the factor or data sources or models or adding additional analytics, scenario analysis.

Benefits

• Improved Investment Performance: Custom models and analytics based on client-defined factors and new strategies help improve investment performance.
• Better Risk Management: Diversification with new data sources and the ability to quickly make changes enable better risk management and decision-making.
• Increased Efficiency: Fully automated factor investing system streamlines portfolio management, freeing up time for more strategic investment decisions.
• Faster Time to Market: Efficient operationalization of both traditional and ML models helps get new strategies to market faster.
• Greater Customization: Flexibility to create custom models and applications and quickly adjust factors, data sources, and analytics provides greater customization for tailored investment solutions.

Common Use Cases

• Factor-based portfolio management: Customize investment portfolios based on targeted factors using the framework's data sources and analytics capabilities to align with investment objectives.
• Risk management and forecasting: Improve risk forecasting accuracy, monitor risk exposure in real-time, and make informed investment decisions by leveraging the platform's risk management capabilities.
• ESG and Impact investing: Integrate ESG factors into the investment process to achieve financial returns and positive social or environmental outcomes, reducing exposure to companies that detract from intended impacts.
• Tactical asset allocation: Identify factor shifts in existing portfolios and optimize performance by leveraging the platform's data analytics capabilities to quickly make changes and add additional analysis.

Deliverables

• Assessment: The solution starts with a free workshop to assess the client's needs and understand their investment objectives. This helps in configuring the framework to suit the client's requirements.
• Deployment and Configuration: The framework is then deployed in the client's environment, and customized based on their specific needs.
• Implementation and Managed Services: Optional implementation services are also available to ensure a smooth transition, followed by ongoing managed services to provide support and maintenance.