It is widely recognized that calibration on internal data may not suffice for computing an accurate capital charge against operational risk. However, pooling external and internal data lead to unacceptable capital charges as external data are generally skewed toward large losses. In a previous...

Intense reflections are being conducted at the moment regarding the way to pool heterogeneous data coming from both banks' internal systems and industry-pooled databases. We propose here a sound methodology. As it relies on maximum likelihood principle, it is thus statistically rigorous and...

The Loss Distribution Approach has many appealing features since it is expected to be much more risk - sensitive than any other methods taken into consideration by the last proposals by the Basel Committee. Thus this approach is expected to provide significantly lower capital charges for banks...

In this paper, we explore the Loss Distribution Approach (LDA) for computing the capital charge of a bank for operational risk where LDA refers to statistical/actuarial methods for modelling the loss distribution. In this framework, the capital charge is calculated using a Value-at-Risk measure....

This paper demonstrates that aggregate losses are necessarily low as long as we remain under the standard assumptions of LDA models. Moreover empirical findings show that the correlation between two aggregate losses is typically below 5%, which opens a wide scope for large diversification...

This paper follows the different steps necessary for implementing a LDA in practice: - Step 1: Severity Estimation - Step 2: Frequency Estimation - Step 3: Capital Charge Computations - Step 4: Confidence Interval - Step 5: Self Assessment and Scenario Analysis For each of these steps, we try to...