Greenhill - Automating Investment Model Performance Measurement
Project Overview
One Liner: Greenhill - Automating Investment Model Performance Measurement
Automating Investment Model Performance Measurement
GreenHill delivers investment performance reporting with a focus on accuracy, independence, and clarity. One of our more powerful—but currently manual—capabilities is tracking and measuring the performance of client-defined investment models (custom portfolios of securities).
Today, building and maintaining these models requires significant manual effort from our service and support team. For this Senior Project, students will design and develop a solution to automate the creation, management, and ongoing maintenance of these investment models.
The vision: a scalable, user-friendly system that allows clients to define, update, and manage their proprietary investment models—while seamlessly integrating with GreenHill’s performance calculation engine.
Key areas of focus may include:
Model creation workflows (user input, validation, and structure)
Version control and change tracking for model updates
Data integration with market securities and pricing data
Automation of performance calculation inputs
Front-end interface for client interaction (web-based portal)
Optional exploration of rules engines or AI-assisted model management
This project sits at the intersection of financial technology, data engineering, and user experience. It also represents a meaningful competitive differentiator for GreenHill, making your work directly impactful to the company’s growth and operational scalability.
Students will gain exposure to real-world financial data challenges, system design, and automation within an enterprise environment. As with all GreenHill projects, creativity and independent thinking are encouraged—we provide the vision, but welcome your ideas on how best to execute it.
Two of GreenHill’s owners are Drexel alumni, and we are proud to continue investing in Drexel talent through this partnership.
More about GreenHill can be found at ghill.com.
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