A threshold based approach to merge data in financial risk management

According to the last proposals by the Basel Committee, banks are
allowed to use statistical approaches for the computation of their cap-
ital charge covering nancial risks such as credit risk, market risk and
operational risk.
It is widely recognized that internal loss data only do not suce to
provide accurate capital charge in nancial risk management, especially
for high severity and low frequency events. Financial institutions typically
use external loss data to augment the available evidence and, therefore,
provide more accurate risk estimates. Rigorous statistical treatments are
required to make internal and external data comparable and to ensure
that merging the two databases leads to unbiased estimates.
The goal of this paper is to propose a correct statistical treatment to
make external and internal data comparable and, therefore, mergeable.
Such methodology augments internal losses with relevant, rather than
redundant, external loss data.