“Revolutionizing Credit Risk Assessment and Modelling: The Role of Alternative Data Sources and Machine Learning in Improving Lending Practices in Mauritius”

The research
will address the following questions and hypotheses:
Question 1: Can
alternative data sources, such as social media activity and transaction
history, augment the accuracy of credit risk assessment compared to
traditional credit scoring systems?
Question 2: What
machine learning algorithms, when applied to credit risk modelling,
proffer
the highest predictive accuracy and efficiency?
Question 3: How
can the transparency and fairness of credit risk models be improved to
provide actionable insights for lending institutions?
Through an
in-depth investigation of these questions, this research aims to stipulate valuable
insights and solutions to the financial industry, ultimately bettering credit
risk modelling and
lending practices
in Mauritius.