Enhancing Financial Model Evaluations for Varde Partners

Client Overview

Varde Partners, a prominent global alternative investment adviser, faced challenges in streamlining the financial model evaluations conducted by their investment team.

Challenge

The investment team’s reliance on R and Excel for financial modeling was proving to be unsustainable due to scalability limits. The need for a more robust and efficient system was becoming increasingly apparent to accommodate the growing complexity of their financial analyses.

Project Goals

The project aimed to overhaul the existing financial modeling process by cleaning and structuring all data, migrating the model from Excel to a more scalable platform on AWS, and equipping the team with the necessary technical training for the transition.

The Solution

Blue Orange chose to implement an AWS SageMaker instance to support Värde’s market analysis and deal due diligence teams. This solution was designed to enhance the efficiency and accuracy of the team’s financial evaluations through several key initiatives:

• Integration of Advanced Models: Heuristic and statistical models were integrated into a proof-of-concept analytics environment, enabling more sophisticated analysis capabilities. Model Tuning and Data Cleaning: Efforts were made to improve the runtime and output accuracy, ensuring that financial models provided reliable and timely results. 
• Scenario Analysis Enhancements: Control variables were abstracted to facilitate scenario analysis and forecast comparisons, enhancing the team’s ability to evaluate various financial outcomes. 
• Reduction in Runtime: The system’s runtime was significantly reduced from hours to minutes, streamlining the entire financial modeling process and allowing for quicker decision-making. 
• Low-Code Analysis Process: A new process was created to enable low-code analysis, making the system more accessible to team members with varying levels of technical expertise.
• Comprehensive Training Program: The team received extensive training to ensure a seamless transition from Excel to SageMaker, covering both the operational use of the new system and the strategic implications of the upgraded technology. 

Technologies Used

• AWS SageMaker: Central to the project, used for hosting and executing complex financial models. 
• Snowflake: Employed for efficient data management and scalability within the AWS environment.

Business Impact

The implementation of AWS SageMaker transformed the financial model evaluation process for Varde Partners by:

• Increasing Efficiency: The significant reduction in runtime and the introduction of low-code processes allowed the investment team to conduct analyses more quickly and effectively.
• Enhancing Accuracy: Improved model tuning and data cleaning processes resulted in more accurate financial forecasts, crucial for investment decision-making. 
• Empowering the Team: With the provided training, the investment team became proficient in using the new system, which increased their productivity and ability to adapt to new challenges. 
• Scalable Foundation: The recommendations for incorporating advanced technologies like machine learning set the stage for further innovations in financial modeling at Värde Partners. 

Conclusion 

This project not only met the immediate needs of Värde Partners by enhancing the efficiency and scalability of their financial modeling processes but also positioned them well for future technological advancements. The transition to a modernized platform equipped the team with the tools necessary to maintain their leadership in the competitive field of investment advising.