To develop an AI/ML model for financial risk assessment of new customers using proxy and alternative data.
To study the impact of educational background on financial risk assessment accuracy.
To evaluate the effectiveness of using alternative data sources in improving risk assessment outcomes.
Collect and preprocess proxy and alternative data sources such as social media, online behavior, and educational background.
Design and implement machine learning algorithms for financial risk assessment, considering factors such as income, credit history, and education.
Evaluate the performance of the AI model in predicting financial risk for new customers and analyze the role of education in risk assessment accuracy.
Compare the results of traditional risk assessment methods with the AI-powered approach using proxy and alternative data to assess the improvement in accuracy and efficiency.
