Chapter 4 Learning Outcomes Flashcards
- What are some of the key benefits of data categorisation?
Some key benefits include: enabling scaling/aggregation of data; providing completeness by identifying gaps; facilitating internal reporting through common data grouping; enabling regulatory reporting by structuring data to requirements; enabling benchmarking against peers with comparable categorization; and reducing interpretation variability through common definitions.
4.1 Define the objectives of data categorisation and use of data categorisation in the management of operational risk.
The objectives are to organize risk data into a structured hierarchy to enable analysis, monitoring, reporting and management. This provides a common language for discussing risk across the organization and a consistent approach for capturing, aggregating and interpreting risk data.
4.2 Describe the different data types that need categorisation.
Typical data types needing categorization include:
- Process types
- Risk types/categories
- Control types
- Industries
- Business lines
- Products/services
- Customers/clients
- Distribution channels
- Geographies
- Causes
4.3 Distinguish between different approaches to creating and applying categorisation structures.
Firms can adapt existing industry structures like Basel II or create their own bespoke scheme. The bow tie model is another approach, distinguishing causes, events and impacts to support categorization. Schemes are applied to risk processes like RCSAs, scenario analysis, and other frameworks to enable consistent data usage. Appropriate balance of granularity, simplicity and flexibility is needed for adoption.
4.4 Explain the various challenges in creating and applying categorisation structures.
Challenges include: scope/boundary definition of what’s in and out; achieving appropriate granularity - enough for usefulness but not too complex; getting management buy-in through intuitive terminology aligned with business; ongoing scheme maintenance as business changes; ensuring consistent quality application of categories by staff; balancing putting categorization at point of business knowledge versus centralised risk expertise.
