Current State of Cross-Border Banking - Vrije Universiteit Amsterdam

Appendix: Data on Cross-Border Banking
General data-description
The figures on the cross-border Index reported in tables 1 to 3 of the main text are based on the
geographical segmentation of assets, revenue and employees. The data on these indicators have
been gathered from the annual reports over the years 2000 to 2005 of the largest banking groups in
the Americas (15), the Asia-Pacific (15) and Europe (30). The 60 largest banking groups are selected
on their capital strength as of year-end 2004 (The Banker, July 2005). When mergers or acquisitions
occur, consolidated data after the merger or acquisition of the acquiring-bank is presented. In the JP
Morgan Chase and Bank One merger, for example, data for JP Morgan Chase is used for the years
2000-2003, and Bank One data is included in the consolidated data for JP Morgan Chase in 2004 and
2005.
Assets
The indicator ‘assets’ is composed of loans to banks, loans to customers and securities. If the group is
involved in insurance activities, insurance investments and other insurance assets are included. Home
country assets (denoted by h), assets in the rest of the region (denoted by r) and assets in the rest of
the world (denoted by w) are measured as a percentage of total assets of the banking group.
Revenue
The indicator ‘revenue’ is based either on gross or net income, depending on which standard is used
in the geographical analysis of the annual report. Gross income includes interest income and similar
revenues, dividend income, commission income, income on financial transactions and other operating
income. If the group is also involved in insurance activities, general insurance premium income and
income from long-term assurance business is included. Net income is obtained by deducting all
relevant costs. Home country revenue (denoted by h), revenue in the rest of the region (denoted by r)
and revenue in the rest of the world (denoted by w) are measured as a percentage of total revenue of
the banking group.
Employees
The segmentation of ‘employees’ is based on the distribution of the (average) number of employees.
Employees in the home country (denoted by h), in the rest of region (denoted by r) and in the rest of
the world (denoted by w) are measured as a percentage of total employees of the banking group.
Calculation
The figures reported in tables 1 to 3 are the arithmetic average of the distribution of assets, revenue
and employees (the data for each indicator are available from the authors upon request). We use all
the information we have available for individual banks. For some banks we have information on all
three indicators, for others we have information on only two indicators and for a couple we only have
information on one of the indicators. If data on one (or two) indicator(s) is available, only this indicator
is used. An indicator can only be utilized if the available data can be divided into a ‘home’ country
component and a ‘rest of the region’ component. However, in several cases (in particular that of
employees) the available data can only be divided into a ‘home’ and a ‘non-domestic’ component. This
problem has been solved by dividing the ‘non-domestic’ component into two equal parts: ‘rest of the
region’ and ‘rest of world’. These data have only been used when no proper data on other indicators of
the banking organization is available.
Sample assumptions
We have used assumptions to generate the geographic distribution of assets, revenues and
employees from the annual reports in a systemic way.
Americas
Canadian annual reports mark year ended at October 31 st , US annual reports mark December 31 st as
year ended. The year 2000 in the dataset represents Canadian annual reports from 2000 and US
annual reports from 2000.
Geographical segmentation: home = country of origin; regional = rest of America, including Canada,
U.S., Mexico, Caribbean, Latin America; world = remainder.
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