XBRL Filing

XBRL Filing INR - 10,000.00

XBRL (eXtensible Business Reporting Language) is a language use for tranform electronic communication of business and financial data and business reporting around the world. It enable to all those who have to create, transmit, use or analyse such information. XBRL has been developed by XBRL International, a not-for-profit organisation of over 600 companies and agencies which is promoting its worldwide use.  

XBRL is a data-rich dialect of XML (Extensible Markup Language), the universally preferred language for transmitting information via the Internet. It was developed specifically to communicate information between businesses and other users of financial information, such as analysts, investors and regulators. XBRL provides a common, electronic format for business reporting. It does not change what is being reported. It only changes how it is reported

XBRL is a world-wide standard, developed by an international, non-profit-making consortium, XBRL International Inc. (XII). XII is made up of many hundred members, including government agencies, accounting firms, software companies, large and small corporations, academics and business reporting experts. XII has agreed the basic specifications which define how XBRL works.

In XBRL, information is not treated as a static block of text or set of numbers.

Instead, information is broken down into unique items of data (eg total liabilities = 100). These data items are then assigned mark-up tags that make them computer-readable. For example, the tag 100 enables a computer to understand that the item is liabilities, and it has a value of 100.

Computers can treat information that has been tagged using XBRL ‘intelligently’; they can recognize, process, store, exchange and analyse it automatically using software.

Because XBRL tags are formed in a universally-accepted way, they can be read and processed by any computer that has XBRL software. XBRL tags are defined and organized using categorization schemes called taxonomies

Different countries use different accounting standards. Reporting under each standard reflects differing definitions. The XBRL language uses different dictionaries, known as ‘taxonomies’, to define the specific tags used for each standard. Different dictionaries may be defined for different purposes and types of reporting. Taxonomies are the computer-readable ‘dictionaries’ of XBRL. Taxonomies provide definitions for XBRL tags, they provide information about the tags, and they organize the tags so that they have a meaningful structure.

As a result, taxonomies enable computers with XBRL software to:

·         understand what the tag is (eg whether it is a monetary item, a percentage or text);

·         what characteristics the tag has (eg if it has a negative value);

·         its relationship to other items (eg if it is part of a calculation).

This additional information is called meta-data. When information that has been tagged with XBRL is transmitted, the meta-data contained within the tags is also transmitted.

Taxonomies differ according to reporting purposes, the type of information being reported and reporting presentation requirements. Consequently, a company may use one taxonomy when reporting to a stock exchange, but use a different taxonomy when reporting to a securities regulator. Taxonomies are available for most of the major national accounting standards around the world.

XBRL is a member of the family of languages based on XML, or Extensible Markup Language, which is a standard for the electronic exchange of data between businesses and on the internet. Under XML, identifying tags are applied to items of data so that they can be processed efficiently by computer software.

XBRL is a powerful and flexible version of XML which has been defined specifically to meet the requirements of business and financial information. It enables unique identifying tags to be applied to items of financial data, such as ‘net profit’. However, these are more than simple identifiers. They provide a range of information about the item, such as whether it is a monetary item, percentage or fraction. XBRL allows labels in any language to be applied to items, as well as accounting references or other subsidiary information.

XBRL can show how items are related to one another. It can thus represent how they are calculated. It can also identify whether they fall into particular groupings for organisational or presentational purposes. Most importantly, XBRL is easily extensible, so companies and other organisations can adapt it to meet a variety of special requirements.

The rich and powerful structure of XBRL allows very efficient handling of business data by computer software. It supports all the standard tasks involved in compiling, storing and using business data. Such information can be converted into XBRL by suitable mapping processes or generated in XBRL by software. It can then be searched, selected, exchanged or analysed by computer, or published for ordinary viewing

Through XBRL, companies and other producers of financial data and business reports can automate the processes of data collection. For example, data from different company divisions with different accounting systems can be assembled quickly, cheaply and efficiently if the sources of information have been upgraded to using XBRL. Once data is gathered in XBRL, different types of reports using varying subsets of the data can be produced with minimum effort. A company finance division, for example, could quickly and reliably generate internal management reports, financial statements for publication, tax and other regulatory filings, as well as credit reports for lenders. Not only can data handling be automated, removing time-consuming, error-prone processes, but the data can be checked by software for accuracy.



Users of data which is received electronically in XBRL can automate its handling, cutting out time-consuming and costly collation and re-entry of information. Software can also immediately validate the data, highlighting errors and gaps which can immediately be addressed. It can also help in analysing, selecting, and processing the data for re-use. Human effort can switch to higher, more value-added aspects of analysis, review, reporting and decision-making. In this way, investment analysts can save effort, greatly simplify the selection and comparison of data, and deepen their company analysis. Lenders can save costs and speed up their dealings with borrowers. Regulators and government departments can assemble, validate and review data much more efficiently and usefully than they have hitherto been able to do.

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