Client Description
Machine Learning-Based Credit Fund
Our client is a digitally-enabled asset manager based in Boston. The client focuses on alternative credit products, especially in the marketplace / P2P lending space. Using a proprietary A.I. and machine learning-based model, the client identifies loans that are most likely to outperform.
Problem Statement
The client developed a proprietary private credit evaluation algorithm, and wished to validate its efficacy for investment valuation.
Project Approach
Valuation Review
We broke down the valuation process and evaluated the ability of each step in achieving its intended operation.
Industry Best Practice
We reviewed machine learning-based valuation methodologies in the industry to identify best practice and key gaps.
Methodology Refinement
The client went on to successfully secure USD 100m in seed AuM from an institutional investor.
Key Achievements
Methodology Evaluation
A comprehensive rating of each step within the valuation process, against peers and best practice.
Algorithm Refinement
Refinement to data collection and data cleansing processes to enhance valuation input.
Successful AuM Seeding
The client went on to successfully secure USD 100m in seed AuM from an institutional investor.
