Credit Risk & Data Analytics

Learning Outcomes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• Assess the relevance of statistical package outputs to the decisions being addressed.
• Work with software to develop data analytics solutions, such as predictive scorecards, clustering models, and different types of regressions.
• Identify the statistical models appropriate for analysing the various decisions that confront a data analyst in different industries.

Transferable and Generic Skills

Having successfully completed this module you will be able to:

• Critically analyse practical difficulties that arise when implementing retail credit risk models; understand the cross-fertilisation potential to other business contexts (e.g. fraud detection, marketing, CRM, etc.).
• Manage time and tasks effectively in the context of individual study.
• Demonstrate an ability to use world-class software and to interpret its output in the relevant techniques.

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• Interpret the output of statistical techniques used for the main data analytics applications.
• Understand the process of data analytics, particularly in the retail lending sector.
• Demonstrate a critical understanding of different types of data analytics methods and the problems they can solve.

• Introduction to data analytics and retail credit risk modelling
• Introduction to credit risk and the related regulations, such us the Basel II and III regulations and Internal Rating-Based (IRB) models
• Descriptive/diagnostic analytics (e.g. basic descriptive statistics and visualizations)
• Data pre-process (e.g. sampling, missing value and outlier handling, etc.)
• Classification approaches (e.g. logistic regression, decision trees, etc.) for scorecard development
• Performance measurements for scorecards (e.g. ROC curves, Lift, Gini, etc.)

The module is delivered through pre-course reading and lectures. The various concepts will be illustrated using real-life credit scoring data and software. In addition there will be some in-lecture exercises.

Formative

This is how we’ll give you feedback as you are learning. It is not a formal test or exam.

Feedback

• Assessment Type: Formative
• Feedback: Formative group feedback on students’ performance in in-lecture exercises will be provided verbally immediately after the exercises. If possible, students will use technological tools to answer questions in the exercises.
• Final Assessment: No
• Group Work: No

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.