Frameworks and Strategies for OpRisk Management Under Basel III

As long as people, systems and processes remain imperfect, operational risk (OpRisk) management will be an essential component of every organization's strategy. The need for strong OpRisk management practices is greater now more than ever, as rapid advancements in technology and increased globalization have resulted in evolving regulatory and business environments. With better operational risk management, organizations can effectively pursue their objectives, minimize their losses and realize higher returns.

This course will provide a sound theoretical foundation from which to explore cutting-edge OpRisk techniques under a changing regulatory environment, including an overview of the latest updates to the Basel Accords. Participants will also have the chance to put theory into practice through the analysis of case studies focused on common real-world situations. They will leave this course equipped with the tools necessary to model, measure and manage operational risk within their organization.

Program Takeaways

• Theory and Application – Explore the latest operational risk theories and techniques, and practice applying theoretical knowledge to resolve MBA-style case studies
• Database Modeling – Learn how to collect and model an operational risk database (losses, business and control factors, scenarios, etc.) from complex organizations
• Emerging Risks – Examine the latest operational threats that the financial industry faces and learn how to manage these risks

Agenda

Day 1

Session 1: Establishing and Modeling an Operational Risk Database

• How OpRisk can be modeled like market and credit risk
• How to automate the collection of OR data
• Step by step guide on how to collect business and control environment factors
• Understanding the regulatory requirements for setting an OR database

Session 2: Measuring Operational Risk

• Developing scenarios and scenario analysis
• Using business and control factors in OR measurement
• Statistical analysis
• OpRisk measurement after the SMA

Session 3: Stress Test and CCAR

• Performing stress test in operational risk
• Modeling OpRisk for CCAR
• Hedging OpRisk using insurance and derivatives

Session 4: Case Study Resolution: Mortgage Lender

• Participants will resolve an MBA-style case of a company with serious operational risk issues

Day 1 Conclusion and Evaluations

Day 2

Session 5: Total Quality Management and Operational Risk

• How TQM can help operational risk management
• Understanding the Basel Accord
• Analysis of several case studies of major operational risk events of various types

Session 6: Multifactor Analysis using Key Risk Indicators and Operational Losses

• Using KRIs to understand what drives operational risk
• Key statistical techniques: (Non)Linear Regression, Clustering

Session 7: Cybersecurity, FinTech and the New OR threats

• Data mining and Machine Learning techniques
• Neural networks/ Support Vector Machines/ Bayesian Belief Networks
• Overview of commercially available risk platforms

Session 8: Case Study Resolution: Allied Commercial Bank of Connecticut

• Participants will resolve an MBA-style case of a company with serious operational risk issues

Program Conclusion and Evaluations