The objective of this project is to author a research paper that explores the integration of survey-based consumer insights into credit scoring models to better predict purchase behavior in emerging markets where traditional credit data is limited. Using Kasi Insight's proprietary survey data, the paper will examine the relationship between self-reported financial attitudes, spending intentions, and observed credit behavior. The study aims to propose a novel framework for incorporating non-traditional data sources into credit risk models to improve predictive accuracy, enhance financial inclusion, and illustrate practical applications through African market case studies.

Research and Data Analysis:

• Analyze Kasi Insight's proprietary survey data to explore relationships between financial attitudes, spending intentions, and credit behavior.
• Conduct literature reviews on non-traditional credit scoring models and emerging market trends in financial inclusion.

Financial Model Development:

• Design and validate a framework that integrates survey data into credit scoring models to enhance predictive accuracy.
• Test the model using case studies from African markets to ensure its applicability and relevance.

Paper Writing and Presentation:

• Draft the research paper, ensuring a clear and cohesive narrative from the abstract to the case studies and conclusion.
• Create a summary presentation to communicate findings and practical implications effectively.