Predictive Credit Scoring Model Development for Emerging Markets

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.

African Financial Insights Dataset Development

This project aims to develop comprehensive financial datasets using survey data provided by Kasi Insights Inc. The primary goal is to capture critical insights into African economies, consumer behaviors, and financial trends. By analyzing this data, learners will address the needs of global financial stakeholders, such as investment banks and data platforms, who require accurate and timely information for informed decision-making. The project will focus on synthesizing survey data into actionable datasets that can support investment strategies and economic planning in Africa. Learners will apply their classroom knowledge of data analysis, economics, and financial modeling to create datasets that reflect current market conditions and consumer trends. The project will involve tasks such as data cleaning, statistical analysis, and visualization to ensure the datasets are robust and insightful.

Academic Market Expansion for Kasi Insight

The Academic Outreach Project aims to establish Kasi Insight as a trusted provider of real-time African data for academic institutions in the US and Canada. This includes promoting our platform to universities, building partnerships with key stakeholders, and driving subscriptions from students, faculty, and libraries.

Integrating Consumer Insights into Credit Scoring Models

This project aims to develop a financial model that integrates consumer survey data into traditional credit scoring systems, specifically targeting emerging markets where conventional credit data is often sparse. The problem addressed is the limited predictive power of traditional credit scoring methods in these regions. By leveraging Kasi Insights' proprietary survey data, the project seeks to enhance the accuracy of credit risk assessments. The goal is to create a model that combines self-reported financial attitudes and spending intentions with observed credit behavior, thereby improving predictive accuracy and promoting financial inclusion. This project will provide learners with the opportunity to apply their knowledge of financial modeling and data analysis to a real-world problem, demonstrating the practical applications and economic impact of using alternative data sources in credit scoring.