Ind AS vs. Indian GAAP: What are the key differences?
India is trying to move to the Indian IFRS accounting standards popularly known as Ind AS. This move will not be easy considering that Ind AS is rather different from the current Indian GAAP standards. Here are some highlights in the differences between the two standards that are bound to make the migration challenging.
Objectives of Indian Accounting Standards (Ind AS):
- Transparency and Consistency: IND AS ensures all companies in India report their finances in a clear, consistent way, making it easy to understand their performance.
- Comparability: Financial statements prepared using IND AS are comparable across different companies, allowing investors and analysts to easily compare the financial health of various businesses.
- Global Alignment: IND AS follows international best practices, making Indian companies’ financial statements understandable to foreign investors and stakeholders.
- High-Quality Information: By following IND AS, companies provide investors and other interested parties with reliable and accurate financial information.
In essence, IND AS aims to create a level playing field for financial reporting in India, fostering trust and facilitating better investment decisions.
Difference Between IND AS and Indian GAAP
IND AS (Indian Accounting Standards) and Indian GAAP (Generally Accepted Accounting Principles) are two accounting frameworks used in India, but with some key differences:
Taxonomy
Generally, the Indian GAAP taxonomy has an estimation of 2500 elements. This is a small figure compared to the Ind AS element count of 6800.
Scope of Tagging
Indian GAAP requires only 300 mandatory elements to be tagged. Under IGAAP, the accounting treatment of acquisition varies widely depending on the legal structure which affects the reported amount of goodwill. This is entirely different with Ind AS. This is because the MCA has expanded the scope of tagging where there are no minimum tagging requirements. Under Ind AS, it is not relevant whether an acquisition is a legal entity or even a group asset as long as it is an acquired asset.
Validation
In the interest of data transparency, there are more elaborate disclosures by corporations to the MCA in the Ind AS taxonomy than there are in Indian GAAP. In fact, in INGAAP additional disclosures such as rate reconciliation, tax holidays and even joint ventures are not required. In IND AS however, the MCA validation tool validates more than 800 mandatory fields of information. This ensures accountable disclosures while also increasing the complexity of tagging.
Records
Unique records such as DIN/PAN/CIN/SRN are a necessary provision in the case of Ind AS. Dummy records are unacceptable with all records being centralised. This makes validation more robust considering there is an interlinking of different government databases. This is different in the case of INGAAP with dummy records being acceptable without the requisite need of providing unique records.
Why is outsourcing a better option at this stage?
There are various benefits that come with outsourcing the audit process at this stage. Outsourcing ensures an in-depth analysis of the operations and their compliance with both Ind AS and Indian GAAP by the service provider. They also ensure an unbiased appraisal, which is essential in generating new ideas and proposals for better performance. External auditors also reduce the costs of auditing. The certified consultants are skilled enough and do not require training fixed salary, thus saving costs and resources hugely.
Clearly, Ind AS is vastly different from Indian GAAP. These differences make the switch a daunting task. However, it’s essential to note that in case of cost audits, it is mandatory to tag the product headings as per the Central Excise Act with other relevant information such as net worth, net revenue as per cost books. This demonstrates the necessity of outsourcing the cost auditing to a certified consultants who have demonstrable knowledge of all the aspects involved. Therefore, guidance from knowledge experts is highly recommended at this transitional stage.
DataTracks: Streamlining Your XBRL Conversion and Tagging for IND AS Compliance
DataTracks offers a comprehensive solution for companies in India grappling with XBRL filing requirements under Indian Accounting Standards (Ind AS). Their services encompass:
- XBRL Conversion: DataTracks expertly converts your financial statements prepared according to Ind AS into the XBRL format, ensuring all data is accurately represented.
- IND AS Tagging: Our team precisely tags each data element within your XBRL document using the relevant Ind AS taxonomy. This guarantees your filings adhere to the specific disclosure requirements of Ind AS.
By outsourcing your XBRL conversion and tagging to DataTracks, you can achieve:
- Effortless Compliance: Meet MCA filing deadlines with confidence, knowing your XBRL submissions are error-free.
- Enhanced Accuracy: Their data validation processes minimize the risk of errors, ensuring the integrity of your financial data.
- Improved Efficiency: Free up your internal resources by delegating the XBRL conversion and tagging tasks to DataTracks’ experts.
DataTracks India empowers Indian companies to navigate the complexities of XBRL filing under Ind AS. Their efficient and accurate conversion and tagging services ensure a smooth and compliant regulatory reporting experience.
Frequently Asked Questions on IND AS
What is the new Ind-AS taxonomy?
The new Ind-AS taxonomy is a standardized way to electronically tag financial statements prepared according to Indian Accounting Standards (Ind-AS). It essentially acts as a classification system for financial data.
Who is required to use the new Ind-AS taxonomy?
Companies that prepare their financial statements for accounting years beginning on or after April 1, 2015, are required to use the new Ind-AS taxonomy when filing their XBRL documents. XBRL stands for Extensible Business Reporting Language, a format for electronically tagging financial data.
What are the benefits of using the new Ind-AS taxonomy?
- Standardization: It ensures consistency in how financial data is presented, making it easier to compare financial statements from different companies.
- Efficiency: Electronic tagging simplifies filing and analysis of financial data.
- Transparency: It promotes better financial transparency for investors and other stakeholders.
What are the main differences between the Ind AS taxonomy and the C&I taxonomy?
The Ind AS taxonomy reflects the adoption of Indian Accounting Standards (Ind AS) issued by the ICAI. Here’s a breakdown of the key changes:
- Alignment with Ind AS: The Ind AS taxonomy follows the requirements of the new accounting standards, leading to more detailed and comprehensive financial disclosures.
- Additional Disclosures: The new taxonomy incorporates mandatory reporting of additional information not required under C&I.
- Increased Elements: The structure of the taxonomy has expanded significantly with a roughly 64% rise in the number of elements. This allows for capturing more granular financial data.
- Improved Structure: The taxonomy utilizes more tables and residual elements for better organization and data capture.
- Enhanced Validation: Formula linkbases ensure consistency by validating relationships between monetary elements. For example, the sum of opening balance and changes during the year must match the ending balance.
- Dimensional Reporting: The Ind AS taxonomy uses “dimensions” instead of “tuples” for a more flexible approach to categorizing financial data.
Why were these changes made?
A: The shift to the Ind AS taxonomy brings Indian financial reporting practices closer to international standards (IFRS). This promotes transparency, facilitates comparisons between companies, and enhances the usefulness of financial statements for stakeholders.
Who is required to use the Ind AS taxonomy?
A: Companies that prepare their financial statements for accounting years beginning on or after April 1, 2015, must use the Ind AS taxonomy for filing their XBRL documents (electronic tagging of financial data)