Overview
Course: Credit Risk
Applied Machine-Learning and Big-Data from Credit Risk Modeling
About this course
This course aims to provide the students with a thinking framework that allows them to (a) formulate the right problems and (b) implement innovative solutions in the context of Credit Risk Modeling. To achieve this goal, students must get familiarized with the latest technological advancements in the fintech industry and develop a technical skillset that comprises of data engineering, statistical modeling, financial acumen, and machine learning.
The course is divided into three sections:
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Technological fundamentals of financial applications
- This is the “tech” on “fintech”.
- The first section introduces the common fintech industry practices to develop and maintain simple financial applications. We’ll go through a set of exercises and examples to improve your technical proficiency and take your coding and algorithmic skills to the next level.
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Financial theory and concepts behind credit risk
- This is the “fin” on “fintech”.
- During this section, we’ll review the basic financial concepts and contextualize the credit risk problem in financial terms.
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Machine Learning for Credit risk modeling
- This is the essence/core of “fintech”.
- In the final module, we’ll introduce the most common machine learning modeling techniques to solve the credit-risk problem formulation.