Agenda

Agenda

Quantifying Rare Events, ICAAP and SMA Course Agenda

Live virtual course | Agenda timing is in GMT
Respective time in HKT
Start: 8:30am GMT / 4:30pm HKT
Break: 9:30am GMT / 5:30pm HKT
Break: 10:45am GMT/ 6:45pm HKT

08:30 – 09:30

The role of scenarios in a post-Covid world

08:30 - 09:30

  • The importance of scenario identification
  • The place of scenarios in a consistent ORM framework
  • What Covid-19 changed to scenario analysis
  • Top risks and main concerns in the financial industry
  • Roundtable and sharing of practices and concerns

09:30 – 09:45

Break

09:30 - 09:45

09:45 – 10:45

Regulatory context: SMA, ICAAP, and operational scenarios

09:45 - 10:45

  • Essentials on SMA
  • Consequences of SMA on Pillar 2 and capital assessments
  • Regulatory essentials on ICAAP
  • ICAAP for small firms
  • The role of operational scenarios in ICAAP

10:45 – 11:00

Break

09:30 - 09:45

11:00 – 12:00

Scenario analysis step by step

11:00 - 12:00

  • Silent voting: how to run brainstorming sessions effectively
  • Scenario identification and selection
  • Governance of scenario analysis

08:30 – 09:30

Scenario assessment 1: methods for quantifying rare events

08:30 - 09:30

  • Assessment options in scenario analysis: fault tree, factor analysis, Bayesian approach
  • Structured scenario quantification
    • Risk drivers
    • Control layering
    • Impact types
  • Control identification, assessment and dependence
  • Impact identification and assessment ranges
  • Monte Carlo simulations using Excel

09:30 – 09:45

Break

09:30 - 09:45

09:45 – 10:45

Scenario assessment 2: operational risk measurement in practice

09:45 - 10:45

  • Guided class exercise on scenario assessment
  • Select a scenario and define its
    • Risk drivers
    • Controls and other mitigation factors
    • Impact types and ranges
  • Discuss the results and challenges

08:30 – 09:30

Measuring reputation impact: latest research using machine learning

08:30 - 09:30

  • Current and future applications of machine learning to operational risk management and measurement
  • Machine learning applied to reputation risk: the impact of news and tone  
  • Measuring reputation

09:30 – 09:45

Break

09:30 - 09:45

09:45 – 10:45

Model risk and model validation

09:45 - 10:45

  • Features of a good model
  • Understanding and adjusting for model limitations
  • Essentials of model validation
  • Key features of model risk management
  • Final remarks