Model Risk in Banking: A Minor Irritant or a Major Concern?
Event Details
Free
Date and Time
Thu, 20 June 2024
12:00 - 13:00
Location
Your event Zoom link is available via IOB Learn, but will also be emailed to you before 11am on the morning of your event.
Event Details
Free
Date and Time
Thu, 20 June 2024
12:00 - 13:00
Location
Your event Zoom link is available via IOB Learn, but will also be emailed to you before 11am on the morning of your event.
In this programme taster sample lecture we will introduce the model management lifecycle and identify risks and issues for financial institutions in the use of models, and particularly forecasting models.
The Professional Diploma in Banking was introduced specifically to support the development of individuals in leadership positions, or who aspire to leadership roles in banking and financial services.
It exposes students to contemporary issues in ethics and corporate governance relevant to financial institutions within the context of understanding the importance of effective risk management.
Students must complete the two term 1 modules first (Risk Management in Financial Institutions AND Bank Governance and Regulation) before moving on to the term 2 module (Bank Capital and ALM). You can only start this programme in October.
There is 0.5 CPD hours for the following designations:
LCI
PB
CB
FCI
Dr. Fergus Gaughran
Head of Risk Analytics Ulster Bank
Extensive experience of credit risk, including PD, LGD and EAD model development, validation and governance to both IRB and IFRS 9 standards. Expert knowledge of both retail and wholesale modelling approaches. Has led projects across many analytics applications, including scorecard developments and strategies for both credit and arrears management. Expert in capital optimisation, stress testing and reverse stress testing, and ICAAP process. Highly qualified mathematician / statistician, educated to doctorate level. In depth knowledge of analytical tools, including multivariate regression, logistic regression, decision trees, Monte Carlo simulation, cluster and factor analyses, and others. Experience applying these techniques in a variety of business settings, including credit strategies and arrears management.
