Credit Risk Analytics
Run by Bangor Business School
15 Credits or 7.5 ECTS Credits
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.
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.
C- to C+ Demonstration of the required knowledge and techniques but with significant mistakes and little development of the subject beyond lecture material.
B- to B+ Clear understanding of the subject, together with evidence of investigation and understanding of theoretical and application, but with some minor errors.
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.
Critically evaluate the role of risk analytics within financial institutions, and its integration in the credit assessment process and strategic decision making
Develop and evaluate the performance of a credit risk quantitative models
Perform a detailed assessment of the different aspects of risk-based pricing and profit maximisation
Comprehend and critically analyse the role of probability of default, loss given default, and exposure at default in bank capital calculations and regulatory requirements
Develop skills to implement and evaluate learning outcomes in Excel
Demonstrate a broad and in-depth understanding of the role of risk analytics in meeting regulatory requirements and policies
Teaching and Learning Strategy
One 3-hour lecture per week
Private study and revision of support material available on Blackboard.
- 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.
Resource implications for students
Resti, A. and Sironi, A. (2007) Risk management and shareholders’ value in banking. Wiley.
Courses including this module
Compulsory in courses:
- N3AX: MSc Banking and Finance year 1 (MSC/BANKFIN)
- N3CT: MSc Finance (with Incorporated Pre-Masters) year 1 (MSC/FIN1)
- N3CM: MSc Finance (10 month) year 1 (MSC/FIN10)
- N3AJ: MSc Finance year 1 (MSC/FINANCE)
- N3CR: MSc Investment Management (10 month) year 1 (MSC/IMGT10)
Optional in courses:
- N3AD: MBA Banking and Finance year 1 (MBA/BIF)
- N3DG: MBA Banking and Finance (with Incorporated Pre-Masters) year 1 (MBA/BIF1)
- N3BV: MBA Finance year 1 (MBA/FIN)
- N3CC: MSc Investment Management year 1 (MSC/IMGT)
- N3CX: MSc Investment Management (with Incorporated Pre-Masters) year 1 (MSC/IMGT1)