Background: A financial service provider was facing challenges with managing credit risk, particularly in assessing the creditworthiness of potential borrowers. They wanted to improve their risk management practices and find ways to more accurately predict and manage credit risk. The financial service provider reached out to AfroPavo Analytics and its subsidiary company, Tausi, for help.
Solution: AfroPavo Analytics and Tausi worked with the financial service provider to review their current credit risk management practices and identify areas for improvement. We proposed using machine learning and AI to analyze the large amount of data available on potential borrowers, including financial information, credit history, and other relevant data.
Tausi developed a customised machine learning model that could predict the creditworthiness of potential borrowers with high accuracy. The model was trained on a large dataset of historical loan data and was able to identify patterns and trends that were not apparent from traditional credit scoring methods.
We also developed a customised dashboard that allowed the financial service provider to visualize and understand the results of the model and make data-driven decisions about lending.
Results: As a result of implementing our solution, the financial service provider was able to significantly improve its credit risk management practices. The use of machine learning and AI allowed the provider to more accurately predict and manage credit risk, which led to a decrease in loan defaults by 30% and an increase in profitability. The financial service provider was also able to save time and resources that were initially used.