Bank Modelling and Performance Analysis module (BU52009)

Bank modelling and performance analysis involves using statistical, mathematical, and financial models to evaluate and measure the performance of banks.

This involves analysing key indicators to assess, among others, profitability, asset quality, and capital adequacy, as we as using advanced mathematical techniques to estimate various forms of efficiency.

What you will learn

You will learn about efficiency analysis and alternative modelling techniques, as well as current issues associated with this field.

In this module, you will:

• utilise data sources in banking, such as Refinitiv Workspace and Datastream
• synthesise data to perform ratio analysis and risk assessment
• apply your knowledge to analyse problems and provide reasoned responses in the context of efficiency analysis and decision-making
• empirically estimate measures like market concentration
• critically evaluate relevant research, establishing the connection between theory and practice
• use appropriate terminology related to Bank Modelling and Performance Analysis

By the end of this module, you will be able to:

• know and understand key aspects of Bank Modelling and Performance Analysis.
• enhance your transferable skills, employability, and enterprise ability.

These skills will prepare you for future endeavours in the banking and finance industry.

Assignments / assessment

This module is 100% coursework and contains two graded assessments.

Continuous assessment (20%):

• Comprised of discussion boards and quizzes
• Each week there will either be an online multiple choice quiz or an assessed discussion board
   
• The discussion boards require real contributions which continue the discussion rather than simple repetitions or "yes" or "no" answers

Individual Coursework essay (80%):

• This essay involves applying a Data Envelopment Analysis model and evaluating the performance of a dataset of banks.
• Given after reading week (week 5) and due at the end of the semester (week 10)

This module does not have a final exam.

Teaching methods / timetable

This module follows a blended learning approach to combine the strengths of in-person and online learning methods.

Active learning is at the core of this learning style.

You will engage with the module in various ways including:

• in-person lectures
• computing labs
• interactive online sessions
• assigned readings and videos
• short quizzes to test your progress
• collaborative group work
• discussion boards