Issues In Related Party Transactions – Identification And Transaction Bench marking
Introduction
Related party transactions are common in the corporate world, involving dealings between entities with pre-existing relationships, such as parent companies and subsidiaries, or between companies and their key management personnel and directors. While these transactions can be a normal and essential part of business operations, they often raise significant concerns regarding fairness, transparency, and compliance. The complexity and potential for conflicts of interest inherent in RPTs necessitate rigorous identification and benchmarking processes to ensure that such transactions are conducted at arm’s length.
In this article, we delve into the key issues surrounding related party transactions. We will explore the challenges in identifying these transactions and the critical role of transaction benchmarking in ensuring that they adhere to market standards. By understanding these aspects, stakeholders can better navigate the intricacies of RPTs and safeguard the interests of all parties involved.
Throughout this article, for the sake of brevity, we shall refer to related party transactions as ‘RPTs’, the Companies Act, 2013 as ‘the Act’, the Companies (Management and Administration) Rules, 2014 as ‘the Rules’, and AS 18 and Ind-AS 24 collectively called ‘Accounting Standards’. We shall strictly restrict our focus on identification and transaction benchmarking of related parties and related party transactions.
Identification
The first step entails with the identification of the related party. Identification of a related party involves determining relationships and transactions between the reporting entity and individuals or entities that could exert control, joint control, or significant influence over the entity, or be influenced by it. This process encompasses assessing direct and indirect associations, including those with directors, key managerial personnel, their relatives, and entities within the corporate hierarchy such as holding, subsidiary, and associate companies. Additionally, it extends to identifying significant investors, joint ventures, and entities under common control. The identification also includes recognizing close family members and any arrangements that might influence the financial and operational decisions of the reporting entity.
Section 2(76) of the Act defines ‘related party’ while Section 188(1) of the Act provides for related party transactions. The main misalignment comes at the point where the expression ‘related party’ is covered differently by the Act and the Accounting Standards. In reality, in several family-owned unlisted entities, the transaction approvals are back-dated, and compliance reporting with regards to the Act is aided with the help of Notes to Accounts. For reasons below, we have attempted to explain why this exercise is futile. The endeavour to pursue identification and reporting of related parties is purely conjecture and preposterous, as leads to non-compliances in identification even before the turn of approval comes. Before proceeding further, it’s important to understand how we see related party from the lens of the Act and the Accounting Standards to cement a holistic understanding. While the definition is covered in their respective sources, we shall cover the basis for differentiation. While the Act focuses on corporate governance and protection of shareholders’ interests to further legal compliance, Accounting Standards focus on financial reporting, transparency and ensure that financial statements provide a true and fair view of the financial position and performance of an entity. Failure to identify related parties can impair a company’s endeavour in reporting the true and fair position of the financial affairs. Conducting transactions with related parties is not illegal; the failure to report the same is certainly illegal, considering the economic nexus which takes birth between the company and the transacting party can prejudice the interest of other unrelated parties, their qualitative mistakes thus watering down to quantitative results in the financial statements. With this in mind, we shall proceed with yet another facet of related party transactions.
Ordinary Course of Business
The Act uses the expression ‘ordinary course of business’ but does not define the same. Black’s Law Dictionary defines ‘ordinary course of business’ as the ‘normal routine in managing trade or business’ In common parlance, ‘ordinary course of business’ would include transactions which are entered into in the normal course of the business pursuant to or for promoting or in furtherance of the company’s business objectives, as per the charter documents of the company. The following factors are indicative for determination compliance under the Act:
1.Objects Clause in the Memorandum of Association
2.Nature of Business and Industry
3.History of Transaction
4.Periodicity and Frequency
The above list is not exhaustive. Individually, none of the above parameters can amount to the transactions being in the ordinary course of business.
In the case of Bharti Televentures Ltd. v. Addl./Jt. Commissioner of Income Tax, the Delhi High Court held that the Memorandum and Articles of Association is not conclusive for deciding whether an activity is in the ordinary course of business of the company. Frequency of the activity is sought to be highlighted. It should be a continuous activity carried out in a normal organised manner. In the case of Seksaria Biswan Sugar Factory v. Commissioner of Income Tax, the Bombay High Court, the Court decided that the amount lent by the company to a third party will not be in the ordinary course of business. The Court observed that just because an activity is included in the Memorandum of Association, the activity per se does not become an activity in the ordinary course of business of the company.
Transaction Benchmarking
Transaction benchmarking in relation to RPTs refers to the process of comparing the terms, conditions, and prices of transactions between related parties to those of similar transactions between unrelated (independent) parties. The goal is to ensure that the related party transactions are conducted at arm’s length, meaning they are consistent with the terms that would prevail in a competitive, open market environment. Explanation (b) to Section 188(1) of the Act states the expression ‘arm’s length transaction’ to be a transaction between two related parties to be conducted as if they were unrelated parties to ensure there is no conflict of interest.
A contract is an agreement enforceable by law wherein the conditions are subservient to the performance of the scope of the contract. Any payment made towards satisfying the scope of the contract is the consideration. It is pertinent to note that the Third Proviso to Section 188(1) contains the expression ‘arm’s length basis’ and not ‘arm’s length price’ for the sole reason that the scope of each transaction by the company with the related party is beyond pricing or the consideration involved. Ergo, the conditions form an important factor in determining whether or not the company exercises the same commercial wisdom with the unrelated party which it exercises with the related party. Several factors including, but not limited to: credit period, mode and terms of payment and time for completion are inalienable factors to determine the arm’s length basis. While the Act provides for identification, approval and reporting of related party transactions, it does not prescribe methodologies and approaches which may be used to determine whether a transaction has been entered into on an arm’s length basis.
In Iljin Automotive Private Limited v. Asst. Commissioner of Income Tax, the ITAT Chennai Bench opined that “the determination of ‘arm’s length price’ seeks answer to the question – What would have been the price if the transactions were between two unrelated parties, similarly placed as the related parties in so far as nature of product, and terms and conditions of the transactions are concerned?”.
In practice and referring to the Guidance note issued by the ICSI, we can take Section 92F and Section 92C of Income-Tax Act 1961 as base for determining the RPTs. Further the Audit Committee (or the Board if the Audit Committee is not applicable) may consider the parameters given in the company’s policy on transactions with related parties. The methodological rigor which distinguishes arm’s length basis with arm’s length price is the function to apply recognized methods such as the comparable uncontrolled price method, the resale price method, cost plus method, profit split method, transaction net margin method, or any other method as may be provided in Rule 10AB of the Income-tax Rules, 1962.
The other method for determination of the arm’s length price shall be any method which considers the price which has been charged or paid, or would have been charged or paid, for the same or similar uncontrolled transaction, with or between non-associated enterprises, under similar circumstances, considering all the relevant facts. The most appropriate method shall be applied, for determination of arm’s length price. Where more than one price is determined by the most appropriate method, the arm’s length price shall be taken to be the arithmetical mean of such prices. Here, it is worth noting that the expression ‘transaction on arm’s length’ may not mean a price at which the third parties transact similar goods. The term ‘arm’s length basis’ means a bundle of terms and conditions including price and not price alone, in isolation of other terms and conditions. A brief comparative for the different methods is provided below:
| Method | Description | Applicability |
|---|---|---|
| Comparable Uncontrolled Price Method | Compares the price charged in a controlled transaction to the price charged in a comparable uncontrolled transaction. | Best used when there are reliable and comparable uncontrolled transactions available. |
| Resale Price Method | Compares the gross margin earned in a controlled transaction to the gross margin earned in comparable uncontrolled transactions. | Useful for distribution operations where the reseller does not add substantial value to the product. |
| Cost Plus Method | Adds an appropriate gross profit mark-up to the supplier’s costs in a controlled transaction. | Applicable in manufacturing or service contexts where value-added can be accurately determined. |
| Profit Split Method | Allocates combined profits from controlled transactions in proportion to the value of each party’s contribution. | Suitable for highly integrated operations where each party makes unique and valuable contributions. |
| Transactional Net Margin Method | Compares the net profit margin relative to an appropriate base in a controlled transaction to those in comparable uncontrolled transactions. | Widely applicable when gross margins or pricing data is not available or less reliable. |
Artificial Intelligence and its Impact
Implementing artificial intelligence to predict market conditions and adjust prices in real-time for arms-length pricing could have significant implications for related party transactions provisions under the Act. While companies can mitigate the risk of being accused of transferring profits to related parties to mitigate tax issues, the usage of thresholds and trigger points can flag transactions which can be used to seek necessary approvals and provide for timely reporting. Real-time pricing adjustments through AI algorithms could enhance transparency in related party transactions. Companies would have clearer documentation and justification for the prices charged, making it easier to demonstrate compliance with regulatory requirements. It can also help companies gain a competitive leverage over their peers.
However, the same poses ethical considerations. AI uses training data sets and an algorithm model to provide appropriate results. AI algorithms must ensure fair and equitable pricing for all parties involved. There is a risk that AI-driven pricing models could inadvertently perpetuate biases or favour certain parties over others. Companies must actively monitor and mitigate bias in their AI models to ensure fair treatment. There should be transparency in how AI determines prices and adjusts them based on market conditions. Companies need to be transparent about the data sources, algorithms, and decision-making processes involved in AI-driven pricing to build trust with stakeholders. Lastly, AI algorithms may rely on vast amounts of data, including personal or sensitive information. Companies being data fiduciaries must ensure that they handle data ethically and comply with privacy regulations (the Digital Personal Data Protection Act, 2023 in India) to protect the privacy rights of data principals involved in related party transactions.
Conclusion
Issues in related party transactions, particularly in identification and transaction benchmarking, pose significant challenges for companies. Accurate identification of related parties is often complex due to intricate corporate structures and indirect relationships, requiring meticulous scrutiny to ensure compliance with legal and accounting standards. Once identified, benchmarking transactions against market standards becomes critical to establish that they are conducted at arm’s length. This ensures fairness and transparency, preventing financial misstatements and conflicts of interest. However, the lack of comparable market data and subjective judgment in valuation can complicate this process. Therefore, robust internal controls, comprehensive disclosure practices, and adherence to regulatory guidelines are essential to mitigate risks and maintain the integrity of financial reporting.
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