Tesis
Es conveniente implementar XBRL en la transición a NIIF/ IFRS
Autor
Leal Góngora, Yury Neyith
Institución
Resumen
With the aim of internationalizing economic relations, with improvements in competitiveness, with an accounting and financial globally accepted standard, and with the intention of being at the forefront in the way we do business today, Colombia is in a process convergence under international financial reporting standards IFRS / IFRS. Although it is inevitable some organizations resist change, this structural change must be done responsibly and disposal, it is necessary to prepare officers and invest in technology (adapting software for its proper application), for some companies, the limitation Technology is part of the problem, and for people who know XBRL, this could be the solution to this technological barrier, for that reason, this system will be studied to be clear about the pros and cons of its implementation and what types of companies benefit. The central purpose of this research is to define, whether it is advisable to implement XBRL in the process of convergence with international financial reporting standards IFRS / IFRS.
XBRL (Extensible Business Reporting Language) developed by a non-profit consortium, is software that provides the option to create, transmit and analyze information. This system works as technological support can help in the process of convergence, reducing the impact
on the adoption of IFRS to implement it properly. XBRL is used in major financial centers and regulatory agencies as a benchmark for the presentation of financial statements and other reports.
Users can send and receive information as "interactive data with commonly accepted labels" for three reasons:
Each segment information provided is the same for everyone with little room for mistakes. This is really possible, by labeling each piece of information, with a label of accounting in a standardized taxonomy based on IFRS / IFRS.
These financial data can be read with the software "interactive reader" to carry forward and compare benchmarks and best performance. The common challenge of turning data into information and information into knowledge is eliminated.
The information can be extracted quickly in financial models, spreadsheets without worrying about having to develop new taxonomies adapted or having to re-read and enter data.