The Solution: Credit Line Optimization
Client: A Credit Fintech that connects investors with available capital to risky consumers who need credit.
The Challenge
Capital allocation is a complex task because it requires deciding month-to-month how much to raise from each investor, each with their own terms (interest rates, deadlines, and capacities), and simultaneously determining how much to lend to each customer, who have distinct risk profiles, acquisition costs, and expected returns.
The Objective
Allocate capital raised from investors to credit borrowers with the goal of maximizing portfolio returns.
The Solution
We've developed a solution based on mathematical optimization that prescribes the ideal capital movement to maximize returns over more than a decade.
The solution considers:
Different investor profiles and their terms.
Distinct customer groups.
Cost and performance curves for each deployment.
Constraints such as minimum bank balance, raise and deployment capacities.
Past decisions that still impact the current model.
Recurrence effects, such as reduced costs and increased returns for loyal customers.
Results
Generation of varied scenarios with high accuracy for more effective planning.
Clear weekly prescriptions for capital movement, optimizing its use.
Automatically identifies and flags conflicting decisions.
Supports long-term planning and fast re-planning.
Our solution was validated by the customer's data science team after extensive testing.