Module ASB-4416:
Credit Risk Analytics

Module Facts

Run by Bangor Business School

15 Credits or 7.5 ECTS Credits

Semester 1

Organiser: Dr Gwion Williams

Overall aims and purpose

Credit risk analytics is one of the most successful uses of statistical modelling within financial institutions but its success isn’t only concerned with data and models; it requires a thorough understanding of business cycles and debt patterns, regulatory requirements, and the integration of quantitative techniques into the strategic management process.

The module examines the theory and practice of credit risk analytics and decision science in financial institutions. Topics include: the Merton default model, philosophy of risk analytics and scoring, default and losses calculations, validation, capital (both economic and regulatory) calculations, and credit portfolio management. Particular emphasis will be placed on topical areas within quantitative methods and regulatory requirements. The module will make extensive use of Excel and students will use trading software to gain practical experience of the methods discussed.

Course content

Monte Carlo, Bootstrapping, The Merton model (incl. structural default models), Scoring models, Loss Given Default (LGD) modelling, Default correlations, Credit portfolio risk, Validation of PD models, Bank capital calculations/Risk Weighted Assets.

Assessment Criteria

threshold

C- to C+ Demonstration of the required knowledge and techniques but with significant mistakes and little development of the subject beyond lecture material.

good

B- to B+ Clear understanding of the subject, together with evidence of investigation and understanding of theoretical and application, but with some minor errors.

excellent

A- to A* Excellent grasp of the concepts and techniques together with significant evidence of engagement and understanding of the theory and application in this area.

Learning outcomes

  1. Critically evaluate the role of risk analytics within financial institutions, and its integration in the credit assessment process and strategic decision making

  2. Develop and evaluate the performance of a credit risk quantitative models

  3. Comprehend and critically analyse the role of probability of default, loss given default, and exposure at default in bank capital calculations and regulatory requirements

  4. Develop skills to implement and evaluate learning outcomes in Excel

  5. Demonstrate a broad and in-depth understanding of the role of risk analytics in meeting regulatory requirements and policies

  6. Perform a detailed assessment of the different aspects of risk-based pricing and profit maximisation

Assessment Methods

Type Name Description Weight
Assignment 25
Final Examination 75

Teaching and Learning Strategy

Hours
Lecture

One 3-hour lecture per week

30
Private study

Private study and revision of support material available on Blackboard.

120

Transferable skills

  • Literacy - Proficiency in reading and writing through a variety of media
  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Information retrieval - Able to access different and multiple sources of information
  • Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
  • Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
  • Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
  • Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

Subject specific skills

  • The major theoretical tools and theories of finance, including financial mathematics, capital budgeting, informational efficiency, optimal risk sharing, portfolio theory, asset pricing and valuation, derivative pricing, risk management, and behavioural finance.

  • The relationship between finance theory and empirical testing, interpretation of accounts and other financial data, including asset pricing models, financial models and projections, event studies, applications of advanced tools of time series econometrics to the analysis of finance and macroeconomic data.

  • Technical skills relevant to financial markets’ operation, trading of financial instruments, and investment companies’ management.

  • Computational skills in financial service activity, and the use of finance theory and empirical evidence to interpret these services.

Resources

Resource implications for students

None.

Reading list

Resti, A. and Sironi, A. (2007) Risk management and shareholders’ value in banking. Wiley.

Courses including this module

Compulsory in courses:

Optional in courses: