Developed in conjunction with UCD College of Business the Professional Diploma in Advanced Operational Risk Management in Financial Services showcases extensive academic thinking and rigor as well as unique, real-world insights from our partners Bank of Ireland, Citi and Deloitte.
The Professional Diploma in Advanced Operational Risk Management in Financial Services has been designed in conjunction with operational risk management professionals, working in financial services and leading academics in operational risk management. It will equip participants with a deep, practical understanding of operational risk management frameworks and measurement methodologies in financial institutions. This qualification is the benchmark operational risk qualification recognised in the Irish financial services industry sectors of the financial services industry.
This specialist programme will provide you with;
A deep and practical understanding of the requirements and responsibilities of operational risk management
Global best practice tools for the identification, assessment, measurement and management of operational risks
Insights into latest academic thinking in areas such AI applications to operational risk management and emerging machine learning models
A thorough understanding of the key practical and relevant operational risks facing banking professionals in Ireland today including inter alia: financial crime prevention/AML/CFT, KYC, external and internal fraud, information security, IT resilience, cybercrime, outsourcing, business continuity planning, data quality, data protection, impact on capital and other practical areas
Knowledge and skills to capture, report and investigate operational risk events, how to produce meaningful risk MI including Key Risk Indicator (KRI) data and trend analysis, and how to implement operational risk appetite
Tools to identify, measure and mitigate risks and thereby improve business performance
Enhanced business judgement, critical analysis and problem-solving skills.
If you hold an IOB designation or a designation managed by IOB, CPD hours may be awarded on successful completion of this programme.
Each 5 ECTS module comprises of up to 15 delivery hours per trimester (i.e. up to 5 evenings) and each 10 ECTS module comprises of up to 30 delivery hours per trimester (i.e. up to 10 evenings).
Assessment is a combination of continuous assessment and end of trimester exams.
Upon successful completion of this programme you will be awarded the Professional Diploma in Advanced Operational Risk Management in Financial Services (level 9) from UCD.
01. Risk Governance, Culture, Business and Enterprise Risk Management (10 ECTS) €1,100
02. Operational Risk and Capital Markets (5 ECTS) €550
03. Strategic Operational Risk, Conduct Risk and Reputational Risk Management (10 ECTS) €1,100
04. Alert Models and Operational Risk Management (5 ECTS) €550
Aisling O'Sullivan - Programme Manager
Students seeking admission to the MSc Pathway or its constituent programmes must possess:
a) An Honours degree (second class honours grade 2 award or higher) OR
b) Admission many also be considered for experienced professionals who do not meet the admission requirements as set out above, where they can demonstrate knowledge through their work i.e. they have more than 5 years’ experience in a management role (to be considered on a case by case basis).
You must be a current member of IOB, or become a member, to undertake this programme.
(NFQ level 9, 10 ECTS)
At the end of this module, participants will understand: Corporate governance, including best practice governance standards. The board responsibilities and expectations of the risk management function. Risk governance frameworks, risk appetite statements and risk policies. The duties of directors under common law, company law and the Central Bank’s Corporate Governance Code for credit institutions. The impact of culture, leadership and behaviour on risk profile and the effectiveness of risk management. The Central Bank’s fitness and probity standards. The role of audit and risk committees, particularly in relation to risk management and an organisation’s system of internal controls. The challenges in setting executive director levels of pay and the link between executive remuneration and excessive risk-taking. Banking model risks. Single Supervisory Mechanism. Enterprise Risk Management (ERM). ERM frameworks and how such frameworks are implemented. Approaches to risk integration and aggregation.
(NFQ level 9, 5 ECTS)
At the end of this module, participants will understand: Operational risk framework and related processes including RCSA (inc. monitoring), Operational Risk Assurance, Governance, Policies, Training. Understand Operational Risk Events. Appreciate linkage to other risk types within capital markets and I side the organisation – financial risk, strategic risk, IT risk etc. Understand the various external data sources available to compare and contrast specific operational risks across firms. Be introduced into the financial data science methods to study the relationships between various operational risks and capital market outcomes. Be introduced into the currently available academic evidence on the relationships between operational risks and capital market outcomes. Appreciate the further research necessary to develop a thorough understanding of the profession of operational risk and its relationships to capital markets.
(NFQ level 9, 10 ECTS)
At the end of this module, participants will understand: The requirements and responsibilities of conduct risk management. Conduct risk frameworks, conduct risk appetite statements, measurement methodologies and global best practices. Operational risk as a risk management discipline in its own right. The distinction between operational risk, credit risk, market risk and Sarbanes-Oxley. The Basel III operational risk implications. Operational risk capital calculation methodologies. Reputational risk and its importance as the top strategic business risk.
(NFQ level 9, 5 ECTS)
At the end of this module, participants will: Have a comprehensive appreciation of the key issues involved in predictive analytics in financial services. Demonstrate a knowledge of the institutional and regulatory contexts of the illustrated application areas in financial services. Be able to explain and discuss with insight classification related problems in financial services. Have an appreciation of the role of economic policy and regulation in the predictive analytics in financial services field. Demonstrate a knowledge of the regulation which can be addressed via Alert models and the impact of regulation and enforcement actions in banking. Understand the impact of Cyberdata. Have an appreciation of the views from other industries e.g. Aviation, Military, Energy, Food distribution.