The Basel Ii Oprisk Principles

The new mix of banking principles has opened up new opportunities, together with potential technical problems over implementation of risk management systems. The clash of political agenda and issues will, doubtless, arise in many financial institutions over the implementation

Organisation units

Locations

Products / staff tasks

Organisation units

Locations

Products / staff tasks

Figure 9.5 Attributed losses to processes

Source: Adapted from "A risk scorecard approach", U. Anders and M. Sandstedt, Risk, January 2003.

Figure 9.5 Attributed losses to processes

Source: Adapted from "A risk scorecard approach", U. Anders and M. Sandstedt, Risk, January 2003.

of Basel II. However, the recognition of the importance of OpRisk is a sure start to opening the Pandora's Box of risk management.

Loss database

This Loss database is the first step to detailing the losses or leakage that are parallel to the leakage and pilfering in the high-street stores. Operational risk is with us to stay, admitted or otherwise, in the banking and investment fields. It has been with us to stay in most other professions since their start. Creating a loss database in some ways is just catching up with standard retail industry practice.

OpRisk analysis, certainly under Basel II advanced standards, will eventually lead us to link the role of the investment parties with their associated losses. See Figures 9.5 and 9.6.

Furthermore, the database is compiled in the hope that we can link the internally manageable risks to establish lines of causality. One example has been to create a relation between the number of failed trades and the ratio of settlements processed per employee, plus to factor in the staff quality.8 More sophisticated regression analysis and other techniques such as Bayesian probability or neural networks hold some hope for connecting causal lines between losses. Doing it successfully will assist companies to improve their business processes. Good management demands that weak process areas must be found, and that means pinpointing who is responsible. Laying the blame for losses squarely at someone's door is likely to be one of the less universally acceptable tasks initiated by loss database analysis.

The Basel II Accord stems from the tremendous increase in financial leverage under a global market and the rising sophistication of the risk management activities. The new financial regulations have been introduced partly to integrate more forms of risk and to improve the

8 'Forecasting from Loss-Events', Z. Molla, Investec, London, 5-6 June 2003.

Figure 9.6 Investment project parties and associated losses

reputation of national financial systems following recent infamous financial failures. But, the potential of risk management monitoring has to meet the abilities of the internal management corporate skills. Where these levels remain low, then there will be difficulty for the bank to effect constructive change.

Financial statements and operational risk variance and exceptions will be noted and reported. Further supervisory visits are likely when the deviance cannot be initially explained. Further investigation may then cause additional regulatory capital to be demanded. Written warnings are then issued. Finally, if the miscreant bank does not comply, the last resort is the withdrawal of the banking licence. So, logical progression of the regulator's bark to bite:

1. Check-list performance bands.

2. Variance and exceptions report.

3. Further supervisory visits.

4. Additional regulatory capital.

5. Warnings.

6. Withdrawal of banking licence. Loss database drawbacks

The loss database has abusiness case justification going for it. But, it is battling against the banking status quo of how things are traditionally done. One of the main reasons for data losses will come from the difficulty in reconciling all the composite dealing and accounting systems from the bank to derive a consolidated loss figure. Lack of IT systems integration will cause some data accuracy to be lost. Loss of control over the input and collation of the data will also increase the room for error. Data input by manual means also increases the room for data error. Some banks and funds will not have the data internally for developing the Loss Database. See Table 9.2.

Table 9.2 Data capture for loss database

Data source

% of sample respondents

Manual process

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