Ditter JISIB 1 2011 19_28 6 Final - Kopie
Using XBRL Technology to Extract Competitive
Information from Financial Statements
Dominik Ditter *, Klaus Henselmann * and Elisabeth Scherr *
* Department of Accounting and Auditing, Friedrich-Alexander University
Erlangen-Nuremberg, Lange Gasse 20, D-90403 Nuremberg, Germany
dominik.ditter@wiso.uni-erlangen.de, pruefungswesen@wiso.uni-erlangen.de,
elisabeth.scherr@wiso.uni-erlangen.de
Received 1 June 2011; received in revised form 22 November 2011; accepted 26 December 2011
ABSTRACT: The eXtensible Business Reporting Language, or XBRL, is a reporting
format for the automatic and electronic exchange of business and financial data. In
XBRL every single reported fact is marked with a unique tag, enabling a full computer-
based readout of financial data. It has the potential to improve the collection and
analysis of financial data for Competitive Intelligence (e.g., the profiling of publicly
available financial statements). The article describes how easily information from
XBRL reports can be extracted.
Keywords: Financial Intelligence, XBRL, Competitive Intelligence, real-time Business Intelligence
1. Introduction
Competitive Intelligence (CI) can be defined as the
process of “gathering and analyzing information
about your competitors’ activities and general
business trends to further your own company’s
goals” (Kahaner 1998, 16). Important sources of
competitive information are publicly available
financial statements. They provide a lot of valuable
information about competitors as their financial
performance (e.g., for the calculation of financial
key metrics to measure the profitability of
competitors) and financial position (e.g., for the
evaluation of the capability to survive price wars).
However, this information usually cannot be used
to the full extent.
The established format types of published financial
statements, for example MS Excel, MS Word and
Adobe PDF, are unstructured and therefore not
computer readable. Software programs simply do
not know how to use this information. With no
information for further working, data processing
systems interpret the information as on-going text.
Every item (in approximately 100 to 500 pages)
must be manually fed into an analysis software tool
or database system. The effort it takes to manually
extract the required information from financial
statements is time-consuming and error-prone. For
this reason, CI managers are forced to acquire
adjusted or structured financial data from
intermediaries or business data providers. The
disadvantages of this approach are the high costs
Available for free online at https://ojs.hh.se/
Journal of Intelligence Studies in Business 1 (2011) 19-28
20
that are incurred and the fact that the data is not
obtained directly from the source (i.e., the target
company).
The eXtensible Business Reporting Language,
or XBRL, has the potential to solve these problems.
Information within documents that are provided in
the XBRL format enable automatic data processing
of almost all reported items without time-
consuming manual feed of data. The idea behind is
that companies have to publish their business
reports in a standardized electronic structure,
increasing the transparency of the reports for
investors. With a little programming effort,
everyone (including small investors) can access
financial data directly from the source, at low cost
and almost in real-time. As a side effect, XBRL
also offers opportunities for CI.
Today only a small amount of specific literature
for accessing XBRL data is available (except
Hoffman 2006). This article is based on Hoffman
2006 and describes how information from XBRL
data can be extracted and used for CI. The article
shall serve as a technical guide and outlines how to
get started and what instruments are required.
This article proceeds as follows. First, we give a
short explanation of the XBRL Concept, before
explaining an approach to XBRL data extraction in
Section 3. In this example, specific financial line
items of an actual XBRL document will be
extracted. Because the implementation status of
XBRL is very sophisticated in the U.S., all
explanations for extracting and using XBRL are
based on SEC filings. The article closes with a
discussion of the effects of XBRL on the
development of CI and a short summary.
2. The XBRL Concept
Because XBRL is a derivate of XML technologies,
the fundamentals of XML will be illustrated first,
followed by an introduction to the fundamentals of
the XBRL Concept.
2.1 Fundamentals of XML
The eXtensible Markup Language, or XML, is a
meta-language for the creation of a self-defined
document markup language (Watt 2002, 10).
A popular markup language is the HyperText
Markup Language, or HTML. With HTML, it is
possible to assign a specific look or layout to
document content. Therefore, the text or numbers
of an HTML-formatted financial statement (file
extension *.html) are tagged (marked) by specific
expressions. For example, HTML tags can indicate
that the number “14013000000” is to be displayed
in bold letters or in the color green. This enables
computer programs like Mozilla Firefox or
Microsoft Internet Explorer to interpret and present
the document content in the deposited layout. The
World Wide Web Consortium (W3C) lists the
applicable markups (vocabulary) and logical
structure (grammar) for the creation of an HTML
document in the HTML Specification (W3C
Recommendation, 1999).
XML is similar to HTML in the way it uses tags.
However, XML markups define the meaning of
document content. For example, in Figure 1 the
number “14013000000” is encircled by two tags
indicating the start and the end of the markup.
These tags tell us that the number reported is the
net income of a company (and not its turnover,
assets, etc). Further, we can see that it is the net
income for the year 2010 and that it is measured in
US dollars (not euros or pounds). Using this
information, a suitable computer program could
open the file, read the number and do any
computations with it. No human beings are needed
to retype the numbers on a keyboard. Access to the
data is much faster and less error-prone.
In contrast to HTML, XML is a meta-language.
Therefore, the W3C does not regulate the
vocabulary, but a set of grammatical rules for
creating self-defined computer readable markups
(Watt 2002, 10). The name and order of elements
and attributes used for the creation of markups can
be arbitrarily extended. The XML Specification
ensures that XML markups, which consist of a
logical structure of elements, attributes and values,
are well-formed (W3C Recommendation, 2008).
Figure 2 illustrates two simplified examples of
well-formed XML documents with the description
of identical data content. The examples A and B
(see Figure 2) show that there are different
possibilities to describe the same issue according to
14013000000
element name attributes
start-tag end-tag
Figure 1: Logical structure of markups
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XML rules. For XML documents to be
automatically exchangeable between different
senders and receivers, all participants of the
communication chain have to use the same XML
markup language. In other words, a uniform and
consistent markup of document content must be
ensured. Therefore, the usable element names and
attributes have to be predefined and deposited in a
schema file. Today it is common to do this with the
XML Schema language (van der Vlist 2002, 2). An
XML document is “valid” if the markups conform
to the rules of the corresponding schema file.
Therefore, this XML document is an instantiation
of the schema or a so-called instance document
(Binstock 2003, 12). XML instance documents (a
technical term for a valid document with data
content; file extension *.xml) and schema
documents (documents in which the declared
elements and attributes like NetIncomeLoss and
year are deposited; file extension *.xsd) are
connected by the bold expressions in Figure 2. A
so-called validating XML Parser (module of a
software program; responsible for the reading in of
an XML document) can search for the attribute
schemaLocation (Harold 2004, 453). If this
reference to the schema document is available, the
Parser can check the XML document for
conformity against the predefined schema. In other
words, by rejecting XML documents in the event of
inconsistencies or markup errors, the schema can
control consistency.
Because it is possible to select a free number of
self-defined elements and attributes, two different
XML markup languages may use the same name
for an element. For example, in Figure 2 “Apple”
addresses the company Apple Incorporated.
However, in another context “Apple” may mean a
kind of fruit. To ensure a clear unique
classification, this name conflict can be solved with
XML Namespace (W3 Schools, 2011). A
namespace is an inventory of affiliated elements
and attributes that can be identified with a unique
name. The namespace name must be an URI
(Uniform Resource Identifier) (W3C
Recommendation, 2009). Because URIs are
absolutely unique, it is not possible for the same
URI to exist again. A default namespace is defined
in the start tag of the root element by the attribute
xmlns = ”URI” (Evjen 2007, 29). It thereby applies
to all other elements that are reported within the
document. In the upper example of Figure 2 the
elements Apple and NetIncomeLoss are associated
with the namespace ”http://www.apple.com
/instance/ExampleA”.
14013000000
8235000000
14013000000
8235000000
Figure 2: Two well-formed XML documents
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Via the creation of individual, customized tags,
XML is a very flexible standard for electronic data
exchange. Almost all transmission requirements
and communication constellations can be covered
with XML. However, for the structured exchange
of business information a certain recognized
framework has been established: XBRL.
2.2 Fundamentals of XBRL
XBRL was created for the automatic and electronic
exchange of business data. The non-profit
organisation XBRL International Incorporated
(XII) maintains the standard in an own
specification. XBRL is a meta-language for
creating markup languages for business reporting
issues. But in contrast to XML, the XBRL
Specification provides both the grammar and core
vocabulary (XBRL International Incorporated
2008, 2).
The XBRL syntax is based on several open,
globally accepted standard specifications, including
XML, XML Schema, XML Namespace, XLink and
XPointer. The repertoire of XML technologies
selected for XBRL is compiled in the XBRL
Specification (SEC Release 33-9002 2009, 11).
Furthermore, the XBRL Specification outlines
elements and attributes used to define reporting
elements and to express relationships among them.
Therefore, the unity open-standard XBRL can be
understood more precisely as the “core language”
for the creation of markup languages for business
reporting issues. However, with XBRL it is
possible to create not only a markup language,
rather more a classification system (taxonomy)
(Hoffman 2010, 301).
There are many different types of accounting
standards around the world, for example, IFRS
(International Financial Reporting Standards),
US GAAP, German GAAP, Swiss GAAP, etc.
Each accounting system demands the reporting of
different numbers and data. Sometimes the
differences are smaller, sometimes bigger. To make
things more complicated, there are different
reporting requirements in every country for banks
and insurance companies than there are for
industrial companies.
For automatic electronic reporting purposes,
each reporting standard has to be converted into a
standardized structure. In XBRL, this is done with
a hierarchical structure (taxonomy) to cope with the
complex and extensive accounting rules. Hence,
taxonomies consist of XML schema documents and
so-called Linkbases (see Figure 3). Schema
documents and Linkbases are separate files, but
they are an entity and together constitute a
taxonomy (EDGAR Online, 2011).
The schema documents represent an unsorted
list of declared element names and their
corresponding attributes (Hoffman 2010, 82). As
schema documents contain a predefined list of a
business report’s possible contents, taxonomies are
often interpreted as “digital dictionaries” for the
transmission of financial statements, for instance
(Hoffman 2010, 301). It would be theoretically
possible to store all declared elements in one single
document, but this would be difficult, due to
thousands of elements that are needed for the
markup of a financial statement (e.g., the US-
GAAP Taxonomy contains approximately 19,000
monetary and non-monetary element names).
For this reason, the elements and their associated
attributes are usually stored according to their
purpose in different schema documents. Elements
that have been defined in an XBRL Taxonomy are
so-called concepts (Hoffman 2006, 67).
Figure 4 illustrates an excerpt of an element
declaration from the US-GAAP Taxonomy. In this
figure an element with the name NetIncomeLoss is
declared. Companies can use the element name for
transmitting a financial line item: in this context,
net income in accordance with US GAAP
standards.
The XBRL Specification provides several
elements and attributes (vocabulary) that can be
used to describe the declared elements in more
detail. The attribute nillable (possible value:
true/false) determines if there is an obligation to
report this item in the instance document (SEC,
2010). This concept does not need to be included in
the report if the value is true. The attribute type
XLink /
XPointer
XBRL Taxonomy
SchemaDocumentA.xsd
CalculationLinkbase.xml
Schema Documents Linkbases
SchemaDocumentB.xsd
SchemaDocumentC.xsd
SchemaDocumentD.xsd
DefinitionLinkbase.xml
PresentationLinkbase.xml
LabelLinkbase.xml
ReferenceLinkbase.xml
Figure 3: Basic structure of an XBRL
Taxonomy
Figure 4: Concept declaration
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expresses if the concept is a monetary item, a string
item, a date item and so on. The taxonomy
developer may add an optional balance attribute
(possible value: debit/credit) to the concept
definition if it is a monetary item type (XBRL
International Incorporated 2008, 80). For example,
it will indicate if the reported fact is an asset or a
liability in the Statement of Financial Position. The
attribute periodtype indicates if the concept is an
instant or duration type. The net income is a
duration type because it is part of the Statement of
Income (Hoffman 2010, 89).
A special feature of XBRL is to describe
complex relationships (links) between different
concepts (concept-to-concept link) or to add
auxiliary information to concepts (one-way link).
The different links are stored in separate files
according to their purpose, the so-called Linkbases
(e.g., label links are generally stored in a separate
document, the so-called LabelLinkbase). The
supported Linkbases according to the XBRL
Specification are shown in Figure 3. The
Calculation-, Definition- and PresentationLinkbase
contain concept-to-concept links, whereas the
Label- and ReferenceLinkbase contain one-way
links.
The links are built with the help of the W3C
specifications XML Linking Language (XLink) and
XML Pointer Language (XPointer). Every concept
has the attribute id that serves as unique identifier
(Hoffman 2010, 88). In Figure 4, the identifier of
the declared concept is “us-gaap_NetIncomeLoss”.
With the help of the identifier, XPointer can locate
(point to) concepts in the schema document. XLink
is used to describe the relationships (links) between
two located concepts or from one located concept
to auxiliary information. The concrete XLink and
XPointer rules can be looked up in the XBRL
Specification (http://www.xbrl.org/SpecRecommen
dations).
A calculation link between two monetary item
type concepts enables them to be linked
mathematically, but with the limitation it only
allows the description of the summation or
subtraction between them (EDGAR Online, 2011).
For example, the use of calculation links enables
the description of net income as total earnings
minus expenses. All specified calculation links
between concepts are aggregated to a Linkbase, in
this case the CalculationLinkbase. The function of
the calculation links is important because it makes
it possible to control if the reported monetary
statements are mathematically complete and correct
(XBRL Spain 2005, 21).
The DefinitionLinkbase serves to express
different kinds of (inter)relationships between
concepts (Hoffman 2006, 67). For example, it can
be deposited that an explanation to the impairment
must be disclosed in the notes in the case of asset
impairment.
The main function of the PresentationLinkbase is
to display the list of unsorted concepts in a
hierarchical structure according to the presentation
rules of the accounting standards. Additionally, for
each hierarchical level the order of the concepts can
be deposited according to the particular formal
requirements (IASCF 2010, 23). For example,
within the Statement of Financial Position the
assets are comprised of current assets and non-
current assets. Furthermore, US GAAP requires
current assets to be displayed before non-current
assets. This can be implemented with the use of
presentation links. All in all, the presentation links
offer the possibility to group and sort the unsorted
list of declared schema elements for the human eye.
The LabelLinkbase offers the possibility to add
a human-readable name (e.g., net income) for a
concept (e.g., ). If several links
with human-readable names in different languages
have been defined, XBRL reports can be prepared
and read in different languages (van der Heiden
2006, 15). For example, the company Apple could
provide the numbers of its balance sheet. Analysts
from Germany could choose the German language
and they would receive a report with lines like
“Sachanlagen”, “Vorräte” and so on. An English-
speaking analyst would see “Property, Plant &
Equipment” and “Inventories” on his report. By
overcoming the language barrier in this way,
information about foreign competitors is easier to
understand.
The aim of the ReferenceLinkbase is to
reference the underlying legal background of the
concept and descriptive literature in commentaries.
Reference links may also provide documentations
about the correct usage of the special concept.
In summary, taxonomies consist of schema
documents and Linkbases. Schema documents only
represent a container of unsorted concepts. They
will be structured with the individual Linkbases.
In the area of accounting, taxonomies are
primarily developed and published by such
standard-setters as the IFRS Foundation or the
Financial Accounting Standards Board (FASB).
Depending on the particular legal situation or
XBRL adoption degree in the respective countries,
the reporting companies may or are required to use
the taxonomies to create and file reports in XBRL
format (instance documents). Due to the
standardized markup structure, XBRL reports can
be automatically readout and processed by
computer programs. To fulfill this aim, it is
important that all participants of the reporting chain
use the same standardized taxonomy. How easily
information from XBRL reports can be extracted
shall be illustrated with the help of SEC Filings
according to the US-GAAP Taxonomy in the
following.
24
3. Extracting competitive information from
XBRL Financial Statements
This section describes how competitive information
can be extracted from US GAAP XBRL reports.
An actual annual report from the company Apple
Incorporated serves as basis for the illustration.
3.1 Financial data provided by the SEC
XBRL can be implemented for different business
reporting issues (e.g., banking supervision, tax and
other regulatory reporting as well as internal
management reporting). However, XBRL
originally has been created to improve the data
exchange of financial statements. With different
taxonomies, it is possible to represent the specific
national accounting standards like US GAAP, IFRS
or German GAAP.
In the U.S., companies have to use the US-
GAAP Taxonomy when they are obligated to
prepare their financial statements according to US
GAAP and SEC regulations (XBRL US, 2008). In
2006, the non-profit jurisdiction XBRL US was
commissioned by the U.S. Securities and Exchange
Commission (SEC) to develop a taxonomy that is
consistent with US GAAP requirements and the
Commission’s regulations (SEC Release 33-9002
2009, 12). In 2010, the on-going development and
maintenance responsibilities for the US-GAAP
Taxonomy devolved to the FASB (FASB, 2011).
The taxonomies supported by the SEC XBRL
mandate are listed on the Web site
http://www.sec.gov/info/edgar/edgartaxonomies.sht
ml.
Because of the SEC XBRL mandate
(or Interactive Data Program), many XBRL filings
of listed companies are available for analysis
online. Beginning with fiscal periods ending on or
after June 15, 2009, domestic and foreign large
accelerated filers that prepare their financial
statements in accordance to US GAAP and have a
public equity float above $5 billion were required
to provide their financial statements to the SEC and
on their Web sites in XBRL format (SEC Release
33-9002 2009, 42). All other public companies that
fell under the definition of large accelerated filers
using US GAAP were required to submit their
financial statements in XBRL format for fiscal
periods ending on or after June 15, 2010. Finally,
all remaining US GAAP filers and all foreign
private issuers using IFRS had to comply with the
XBRL requirements in year three of the phase-in
(SEC Release 33-9002 2009, 43). For foreign
private issuers using IFRS, the requirement to file
XBRL reports was postponed until SEC approval
of the IFRS-Taxonomy (SEC, 2011). It was
estimated that about 500 companies in year one,
1,800 companies in year two and about 12,000
companies in year three of the phase-in were
required to submit their filings in XBRL (Hoffman
2010, 219) to the SEC Electronic Data-Gathering,
Analysis, and Retrieval system (EDGAR). Anyone
can access this data pool and download the XBRL
filings (Forms 10-K, 10-Q, etc) free of charge. By
providing several types of RSS Feeds, all XBRL
filings can be downloaded to and integrated into a
database or an analysis tool. In combination with
the EDGAR system, XBRL enables competitive
information from thousands of companies to be
downloaded and analysed almost in real-time.
3.2 Extracting Apple’s XBRL Data
For extracting all information that an XBRL report
provides, a special XBRL Processor is needed. The
reason is that an XML Processor has no knowledge
of XBRL and thus is not able to understand and
handle the structure and relationships among the
different XBRL documents (Hoffman 2006, 494).
An XBRL Processor can follow the XLink and
XPointer expressions and is able to put the
different information together. It can read, write,
control, handle or otherwise process XBRL data
(Hoffman 2010, 232). An XML Processor can also
be used to extract information; however, it is not
possible to use all information (e.g., to
mathematically check for correctness and
completeness) XBRL documents provide (Hoffman
2010, 24).
An XML Processor is a software program that
can read, change, delete or transform XML
documents. The module of the XML Processor
responsible for the reading-in of an XML document
is called XML Parser. An XML Parser facilitates
access to the content of an XML document by
converting it into an Application Programming
Interface (API). Afterward, this API can be
accessed with programming languages for further
processes (Maruyama 2002, 21). One possible
programming language is Visual Basic for
Applications (VBA), which can be directly
embedded in MS Excel (Hoffman 2006, 495).
MS Excel is a well-known and widely used
analysis tool. Furthermore, one important
component is already integrated into it: an XML
Parser. As a result, MS Excel can be a useful tool
for extracting competitive information from XBRL
financial statements. With only a little technical
expertise, XBRL data can be extracted without the
help of special software. Because the built-in XML
Parser is used, only a stand-alone instance
document and not the (extension) schema and the
different (extension) Linkbases can be used (note:
XBRL supports creating own individual concept-
extensions if the taxonomy structure does not
provide the adequate concept for transmission.
However, when the taxonomy structure is extended
or adjusted, it is necessary to publish the
corresponding extension schema and extension
25
Linkbases.). Nevertheless, this simple approach can
generate huge benefits for CI.
Apple’s annual report for the fiscal year 2010
can be downloaded from the SEC EDGAR
database in the data formats HTML/ASCII and
XBRL. Figure 5 shows a simplified excerpt of the
XBRL report (instance document). Among other
data, it contains all information needed for the
automatic extraction and calculation of the key
metric Return on Sales (after interests and taxes)
that is defined as the ratio between net income and
sales (Tracy 2009, 132). It is one way of measuring
a company’s profitability (here the Return on Sales
after interests and taxes). Therefore, it is a useful
key performance indicator for many Competitive
Intelligence purposes. However, there are an
infinite number of other calculations that could be
automated as well.
In accordance to US GAAP, companies have to
report their sales revenues as net value, that is as
revenues earned from selling products minus sales
returns, sales allowances and sales discounts.
Therefore, for the calculation of this key metric,
Apple’s net sales is inserted into the formula for the
term sales. The net income is calculated after
subtracting the expenses from earnings and
represents the profit for the year attributable to
shareholders. In Apple’s instance document, the
values for the numerator and denominator of the
ratio Return on Sales are transmitted by the
predefined element names SalesRevenueNet and
NetIncomeLoss of the US-GAAP Taxonomy 2009.
In order to distinguish between GAAP (prefix: us-
gaap) and Non-GAAP element names (prefix: dei),
a so-called prefix is used. A prefix in the start-tag
of an element associates a specific namespace to
single element names instead of assigning a default
namespace for all element names within an
instance document (see section 2, Figure 2). Each
element name prefix is associated with an own URI
(Harold 2004, 65).
For human beings the instance document in
Figure 5 might look a bit confusing. But computer
programs can find a path through this “data
jungle”, finding and extracting the information
needed. The standardized structure enables the
selective and automatic analysis of financial
statements.
In our approach, a few lines of VBA code will need
to be written (see Figure 6) and the code will have
to be inputted into the Visual Basic Editor in MS
Excel. First, it is necessary to convert the instance
document to an API so that the document content
can be accessed. Afterward we can search for the
element names SalesRevenueNet and
NetIncomeLoss and import the contained values
into an MS Excel spreadsheet. In Figure 6 the VBA
code for the extraction of the net sales (see the bold
expression) is illustrated. If we feed the storage
location of the instance document into column A in
the MS Excel spreadsheet (see Figure 7) and
execute the VBA program (or VBA Macro), this
specific fact value will automatically be imported
into the denoted column E.
APPLE INC
2010
FY
65225000000
14013000000
2009-09-272010-09-25
iso4217:USD
Figure 5: Simplified excerpt of Apple's instance document
26
3.3 Results
By extending the VBA code (or replacing the bold
expression), the remaining columns in the MS
Excel spreadsheet (columns B, C, D and F; see
Figure 7) can be filled.
After the import of the needed information into
the spreadsheet, normal MS Excel formulas can be
applied to the values (column E and F) in order to
calculate the requested key metric. For the
company Apple we calculate a Return on Sales of
21.48 % for the fiscal year 2010 with the aid of
Apple’s XBRL data. The result is displayed in
column G. Therefore, with XBRL no manual work
for the calculation of the Return on Sales is needed
anymore. If we do this calculation only once and
for one company, the benefits of this approach
seem to be limited. The true potential appears if we
imagine that the procedure will be applied to many
companies. By extending the VBA Macro with a
few more lines of code, it would be possible to
calculate a ratio (or dozens of them) for thousands
of competitors in a fully automated process. It
would be possible to compare Apple’s performance
measure with all other examined companies (or the
industry average) by a pivot table (benchmarking)
or further graphical analysis, for example. Often
used analytical CI techniques like benchmarking
and competitor profiling (e.g., the profiling of
financial statements) (Bouthillier 2003, 54)
therewith can be supported.
4. Effects of XBRL on the Development of
Competitive Intelligence
The ultimate goal of CI is to gather and analyse as
much (external) information as possible in order to
guide strategy by understanding a company’s
marketplace competitiveness and its adaptability to
future changes in the competitive environment. In
the literature the CI process is often divided into
the following four steps: (1) Direction,
(2) Collection, (3) Analysis and (4) Dissemination
(Vrien 2004, 3). For the collection of competitive
information (step (2)) there are several different
sources possible. Studies found that the systematic
screening of the internet is among the most
important and widely-used instruments of CI
(Vrien 2004, 11 and 17). The “internet" technology
XBRL provides a lot of opportunities for CI. When
all participants in the reporting chain (sender and
receiver) use the same XBRL taxonomy, an
Figure 6: Sample VBA code to extract an XBRL fact value
Figure 7: Extraction results
Sub ExtractXBRLforCI()
Dim Row As Range
Set Row = Sheet1.Range("A2")
'XML Parser --------------------------------------------------------------------------------------
Dim instanceDocument As MSXML2.DOMDocument
Set instanceDocument = New MSXML2.DOMDocument
instanceDocument.async = False
instanceDocument.validateOnParse = False
instanceDocument.Load (Row)
'XBRL Extraction --------------------------------------------------------------------------------
Dim Nodelist As MSXML2.IXMLDOMNodeList
Set Nodelist = instanceDocument.getElementsByTagName("us-gaap:SalesRevenueNet")
Dim Node As Object
For Each Node In Nodelist
Cells(Cells(Rows.Count, "E").End(xlUp).Row + 1, "E").Value = Node.Text
Next Node
End Sub
27
automatic selection of individual desired data is
possible. A time-consuming manual search through
online available financial statements will not be
needed anymore. In combination with other
internet technologies like RSS, the financial data
can be extracted almost in real-time directly from
the source and it doesn’t have to be acquired at
high cost. Besides the analysis getting faster and
cheaper, a broader data basis can be examined.
Mass data can easily be analysed as well as textual
or qualitative data (e.g., information about the
company’s strategy and the managers’ forecast to
the future performance) with the use of XBRL.
With taxonomies (esp. LabelLinkbases) available
in different languages, the collection of data can be
driven independent from language hurdles. This
will become more and more important for CI due to
globalized markets.
All in all, XBRL contributes to a quantitative
better collection of data without reducing the data
quality. The data quality rather increases. The fact
that step (2) in the CI process improves, has also
positive consequences for the steps (3) and (4). On
the basis of better data, qualitatively and
quantitatively, more reliable decisions are possible.
5. Summary
The article illustrates a simple approach to
automate the extraction and further processing of
financial statement information (e.g., for profiling
of financial statements) using publicly available
XBRL reports and MS Excel. With the creation of
a simple VBA Macro, XBRL data enables
calculating not only one stand-alone key metric,
but whole MS Excel templates (e.g., scoring
systems or benchmarking models) can be fed with
financial data.
The XBRL technology provides a lot of
opportunities for CI. Competitive information from
financial statements can be collected and analysed
independent of former limitations (e.g., data
volume, language or qualitative data). Designed as
an open-standard, it is possible to customize the use
of XBRL to own individual needs so that it can
greatly simplify and speed up the analysing of
financial data.
References
Binstock C et al. (2003) The XML Schema
Complete Reference, Pearson Education Inc.,
Boston, Massachusetts
Bouthillier F and Shearer K (2003) Assessing
competitive intelligence software: a guide to
evaluating CI technology, Information Today
Inc., Medford, New Jersey
EDGAR Online (2011) Try XBRL Glossary,
Available online on URL:
http://www.tryxbrl.com/Learn/Glossary/tabid/5
8/Default.aspx
Evjen B et al. (2007) Professional XML, Wiley
Publishing, Indianapolis, Indiana
FASB (2011) FAF/FASB XBRL Taxonomy Role,
Available online on URL:
http://www.fasb.org/jsp/FASB/Page/
Harold E and Means S (2004) XML in a Nutshell,
Third Edition, O’Reilly Media Inc., Sebastopol,
California
Hoffman C (2006) Financial Reporting Using
XBRL, Available online on URL:
http://frux.wikispaces.com/
Hoffman C (2010) XBRL for Dummies, Wiley
Publishing, Indianapolis, Indiana
IASCF (2010) The IFRS Taxonomy Guide 2010,
Available online on URL:
http://www.ifrs.org/NR/rdonlyres/38EAB57A7
264A7491ECEEEF29BBE8A6/0/ITG20102010
0702.pdf
Kahaner L (1998) Competitive Intelligence: How to
Gather, Analyse and Use Information to Move
Your Business to the Top, Touchstone, New
York
Maruyama H (2002) XML and Java, Second
Edition, Pearson Education Inc., Boston,
Massachusetts
SEC Release 33-9002 (2009) Interactive Data to
Improve Financial Reporting, Available online
on URL:
http://www.sec.gov/rules/final/2009/339002.pdf
SEC (2010) XBRL Glossary, Available online on
URL:
http://www.sec.gov/spotlight/xbrl/glossary.shtm
l
SEC (2011) No-Action Letter, Available online on
URL:
http://www.sec.gov/divisions/corpfin/cfnoactio
n/2011/caq040811.htm
Tracy J (2009) How to read a financial report,
Seventh Edition, John Wiley & Sons, Hoboken,
New Jersey
van der Heiden J (2006) XBRL in Plain English,
Available online on URL:
http://www.bataviaxbrl.com/downloads/XBRLi
nPlainEnglishv1.1.pdf
van der Vlist E (2002) XML Schema, O’Reilly
Media Inc., Sebastopol, California
Vrien D (2004) Information and Communication
Technology for Competitive Intelligence, Idea
Group Publishing, Hershey, Pennsylvania
W3C Recommendation (1999) HTML 4.01
Specification, Available online on URL:
http://www.w3.org/TR/html401/
W3C Recommendation (2008) Extensible Markup
Language (XML) 1.0, Available online on URL:
http://www.w3.org/TR/REC-xml/
W3C Recommendation (2009) Namespaces in
XML 1.0, Available online on URL:
http://www.w3.org/TR/REC-xml-names/
28
W3 Schools (2011), XML Namespaces, Available
online on URL:
http://www.w3schools.com/xml/xml_namespac
es.asp
Watt A (2002), XML in 10 minutes,
Sams Publishing, Indianapolis, Indiana
XBRL International Incorporated (2008) XBRL 2.1
Specification, Available online on URL:
http://www.xbrl.org/Specification/XBRL-
RECOMMENDATION-2003-1231+Corrected-
Errata-2008-07-02-redlined.doc
XBRL Spain (2005) White Paper on XBRL
Technology, Available online on URL:
http://www.xbrl.es/downloads/libros/White_Pa
per.pdf
XBRL US (2008) US GAAP Taxonomy Preparers
Guide, Available online on URL:
http://xbrl.us/Documents/PreparersGuide.pdf