Author: inavatiq

Case Details: S.M.A. Siddique Steels vs. State Tax Officer/Commercial Tax Officer [2026] 183 taxmann.com 621 (Madras)

Judiciary and Counsel Details

• Krishnan Ramasamy, J.
• J.Sankarapandian for the Petitioner.
• R.Suresh Kumar, AGP for the Respondent.

Facts of the Case

The petitioner challenged the impugned assessment order issued by the State Tax Officer/Commercial Tax Officer. The factual sequence reveals that the show cause notice (SCN) was issued solely by uploading it on the GST portal, without utilizing any alternative modes of service. The petitioner did not respond, asserting that he had no knowledge of the SCN. The assessment order was passed ex parte, denying the petitioner an opportunity of personal hearing. It was contended that such proceedings violated the principles of natural justice. The matter was placed before the High Court.

High Court Held

The High Court held that while portal upload is a valid mode of communication, the Assessing Officer ought to have ensured effective service by exploring alternative modes, preferably through registered post with acknowledgment due (RPAD), when no response was received. The court set aside the impugned order, subject to the deposit of 25% of the disputed tax, and remanded the matter for fresh consideration after issuing due notice and affording personal hearing, in accordance with Section 169, read with Section 75 of the CGST Act and Tamil Nadu GST Act.

The post HC Quashes GST Assessment for SCN Served Only on Portal appeared first on Taxmann Blog.

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AI is changing how professionals work—but is it ready for Indian tax law? To find out, Taxmann.AI teamed up with IIT Kharagpur to conduct the LE-BTL Benchmark Study, testing 12 leading LLMs on Income Tax, GST, FEMA, and more. Here's what they found.

Table of Contents

1. Introduction
2. Key Findings
3. The Methodology
4. Domains Covered
5. The Findings
6. How to Overcome the Shortcomings of LLMs?

1. Introduction

In a first-of-its-kind research collaboration, Taxmann.AI, in partnership with IIT Kharagpur, conducted India’s inaugural benchmarking of 12 leading Large Language Models[1] (LLMs). The study was conducted by a curated panel of AI researchers and senior tax professionals to evaluate the accuracy and reasoning capabilities of these models within the intricate landscape of Indian tax law.

As the global benchmarks often ignore the unique statutory and judicial nuances of the Indian legal system, the study introduced a purpose-built IRAC+ evaluation framework to test models on issue identification, rule application, and professional justification.

The results reveal that the advanced proprietary models, such as GPT-o3 and Gemini 2.5 Pro, consistently outperform open-weight and lightweight alternatives on complex tax queries. The methodology employed in the study is a structured, multi-layered approach designed to address the specific complexities of the Indian legal system, which includes frequent amendments, layered statutes, and contradictory judicial precedents.

2. Key Findings

The study yielded the following principal findings:

• Proprietary models (GPT and Gemini families) consistently outperform open-weight and lightweight models across all evaluated dimensions.
• LLMs exhibit inverse performance behaviour with respect to question complexity, achieving lower accuracy on simple questions while performing better on complex, multi-layered legal problems.
• “Persona” prompting (assigning the model a specific role) reliably improves model performance. However, “few-shot” (providing sample questions and answers) prompting produces inconsistent results and may degrade performance.
• Open-weight models such as DeepSeek V3 fail to cross the 50% accuracy threshold on specialised legal tasks.
• GPT-5 falls within the mid-tier accuracy band and fails to deliver the depth of structured reasoning expected of frontier models.
• While most models perform adequately on Issue and Rule Identification, they struggle significantly with Application of Law and Justification, which emerge as the primary bottlenecks.
• GPT-4o was validated as an automated judge, exhibiting a very high rank-correlation (0.97) with human expert evaluations.
• Although the LLM-as-a-judge showed mild score inflation, it preserved consistent relative rankings across models, demonstrating scalability for benchmarking.
• Performance varied significantly by domain. Models performed strongly in tax law but poorly in niche areas such as FEMA and Accounting Standards.
• Top-tier models demonstrated high internal stability, with minimal divergence between best- and worst-case scores. Lower-tier models exhibited high volatility.
• The LLM-as-a-judge is slightly more “optimistic” (lenient) in its absolute scores than human experts.
• No model exceeded 80% accuracy; even the strongest proprietary systems remained capped at approximately 70–73%.

3. The Methodology

Four core components define the methodology:

• The IRAC+ Evaluation Framework
• Benchmark Construction and Dataset
• Experimental Setup
• Scoring Mechanism

3.1 The IRAC+ Evaluation Framework

To move beyond generic language benchmarks, the study extended the traditional IRAC framework into IRAC+, recognising that standard IRAC inadequately captures the reasoning demands of complex tax scenarios. The six evaluated dimensions were:

• Issue Identification: Identifying the core legal or factual controversy.
• Rule Identification: Citing relevant statutes, circulars, notifications, and case laws.
• Application of Law: Applying the identified rules to specific facts, including tax reasoning and handling exceptions.
• Conclusion: Delivers a logical, defensible, and actionable final outcome.
• Interpretation: A new dimension added to test the understanding of legislative intent, amendments, and specific statutory context.
• Justification: A new dimension added to evaluate the ability to construct legally persuasive reasoning (e.g., drafting grounds for appeal).6

3.2 Benchmark Construction and Dataset

The benchmark consists of over 100 expert-validated questions covering Indian Direct Taxes, Indirect Taxes (GST), FEMA (Foreign Exchange Management Act), Accounting Standards, and judicial precedents.

To ensure objective evaluation, every question was paired with a high-quality reference answer drafted by experienced Chartered Accountants and tax consultants. These “gold standard” answers served as the ground truth against which model outputs were scored.

3.3 Experimental Setup

Each model was tested using three distinct prompting strategies to analyse how instruction tuning affects performance:

• Base (Zero-shot): The question was posed in a zero-shot manner with no additional context.
• Persona Prompt: The model was assigned a specific role (e.g., “You are a Tax expert…”) to trigger domain-specific behaviour.
• Few-shot Persona Prompt: The model was given the persona, context, and an illustrative example to guide its reasoning.

3.4 Scoring Mechanism

The study used an LLM-as-a-Judge approach, primarily using GPT-4o to score responses. The judge was provided with the Candidate’s Answer, the Ground Truth Reference, and a strict Scoring Rubric. The judge assigned a score of 1 to 5 for each of the six IRAC+ dimensions using specific checklists.

• 1 (Inadequate): Does not cover 50% of the required response.
• 3 (Usable): Aligned with ground truth and covers 80% of the response; immediately usable after minor edits.
• 5 (Gold Standard): Reserved for answers with explicit discussion of counterarguments, caveats, and verbatim statutory extracts.

To mitigate the inherent biases of LLM judges (such as a preference for longer answers), the methodology employed a Hybrid Approach. This involved cross-validating the results using a subject-matter human expert and an alternative LLM Judge (Gemini 2.5 Flash). The study found a very high correlation (0.97) between the rankings provided by the LLM judge and the human experts, validating the methodology’s reliability.

4. Domains Covered

The study covered the following domain areas:

• Income Tax (Income Tax Act, 1961 and Income Tax Rules, 1962)
• GST (Central Goods and Services Tax Act, 2017)
• FEMA
• Accounting Standards
• Judicial Precedents (Conflicting interpretations by different Tribunals, High Courts and Supreme Court).
• Circulars and notifications
• Double Taxation Avoidance Agreements (DTAA)

5. The Findings

5.1 Clear Stratification of Models

The study identified three distinct performance clusters based on overall accuracy, with a marked dominance of proprietary models over open-weight versions.

• Top-Tier (Accuracy > 50%): This tier is occupied exclusively by proprietary models. GPT o3 Pro, GPT o3, and Gemini 2.5 Pro consistently led the rankings.
• Mid-Tier (Accuracy 30% – 50%): This group includes Gemini Flash 2.5, GPT o4 mini, and the open-weight model DeepSeek V3. These models often struggled to maintain consistency across complex legal tasks. Notably, GPT-5 (specifically in “No Prompt” and “Persona Prompt” settings) fell into this tier, failing to deliver the detailed logical reasoning expected of a newer model.
• Low-Tier (Accuracy < 30%): Models such as Grok3, GPT-4o, and GPT-4o mini performed poorly, often failing to understand the nuances required for tax compliance.

5.2 Scoring Dynamics by Prompting Strategy

The study found that how a model is prompted significantly alters its scoring potential, though the effect is not uniform across all models.

• Persona Prompting: Assigning a specific role (e.g., “You are a Tax Expert”) improved performance across all tiers.
• The Few-Shot Dilemma: While few-shot prompting (providing examples) helped under-aligned models like DeepSeek V3 and GPT o1, it actually reduced the performance of top-tier models like GPT o3 and Gemini 2.5 Pro. The study suggests that for high-reasoning models, static examples may cause “context saturation,” crowding out the model’s latent reasoning capabilities or introducing noise.

5.3 IRAC+ Dimension Scores

Models generally scored well on Issue Identification and Rule Identification (syntactic tasks). However, scores dropped sharply for Application of Law and Justification. These dimensions require multi-step logic and statutory adaptation, making them the primary differentiators between strong and weak models.

Top-tier models exhibited a very tight divergence (0.23%) between their “Interpretation” and “Conclusion” scores. This indicates that when these models correctly interpreted the law, they almost always reached the correct conclusion. In contrast, lower-tier models displayed high volatility, often interpreting a rule correctly but failing to apply it to a logical conclusion.

5.4 The “Complexity Paradox”

A counterintuitive finding was the relationship between question complexity and accuracy. Models frequently achieved higher accuracy on “Complex” questions than on “Simple” ones. For example, Top-Tier models averaged ~60-70% on complex questions but often scored lower on simple queries.

This suggests that current LLMs may be over-optimised for intricate reasoning or “overfitted” to complex training data, inadvertently sacrificing the ability to handle basic recall and straightforward comprehension tasks.

5.5 Topic-Specific Variance

Scoring varied significantly depending on the legal subject matter:

• Direct Tax: This was the strongest category, with top models achieving up to 72.84% accuracy.
• FEMA and Accounting Standards: These niche areas saw lower scores and higher dispersion among models (mostly 40%–60%).

5.6 Biasedness of LLM-as-a-judge

The study found that the LLM-as-a-judge demonstrated biasedness at various fronts:

• They assigned higher scores to longer answers, regardless of their actual correctness.
• They favoured answers listed first in the evaluation prompt.
• They showed a preference for responses generated by their own model family (e.g., a GPT -4 judge preferring GPT-generated answers).
• They exhibited higher scores than human experts.
• They are more lenient than human reviewers. While human experts penalise superficial legal fluency, LLM judges may award high scores to responses that appear well-structured or fluent but lack legal depth.
• They can be easily manipulated by “hacks” or superficial formatting choices rather than the substance of the reasoning.
• Inserting specific tokens (such as a colon “:”) or boilerplate phrases like “Solution:” or “Thought process:” can systematically trigger false positives.
• Slight rewording of the evaluation prompt can yield different scores, making reproducibility difficult.
• They often report high confidence in their judgments even when they are wrong. This phenomenon undermines trust, especially in high-stakes domains like tax law.
• They failed to identify hallucinations in judicial precedents.
• They favour fluent writing over legal accuracy.

To mitigate these biases, we employed a Hybrid Approach, using human experts to “anchor” the benchmark and cross-validating results with a secondary LLM judge (Gemini 2.5 Flash) to ensure the rankings were reliable despite these inherent systemic flaws.

6. How to Overcome the Shortcomings of LLMs?

Here are the key methods to overcome these shortcomings:

• Implement a Hybrid Evaluation Framework: To overcome the biases and reliability issues of LLM-as-a-Judge, the study proposes a Hybrid Approach that combines AI scalability with human rigour. Use subject-matter experts to evaluate dimensions like reasoning depth and citation fidelity, rather than generic fluency.
• Separate Deterministic from Generative Tasks: LLMs often fail at precise numeric calculation and formal rule evaluation. Limit the LLM’s role to tasks it excels at, such as rule selection, summarisation of statutes, and interpretation of text, rather than relying on it for mathematical logic.
• Move from Static to Dynamic Prompting: The study found that while Persona Prompting consistently improves performance, Few-Shot Prompting can sometimes degrade performance in top-tier models due to “context saturation” or noise. Instead of using static few-shot examples that remain unchanged, systems should use dynamic, context-aware few-shot examples tailored to the specific task or input. This prevents crowding out the model’s latent reasoning capabilities with irrelevant signals.
• Integrate Retrieval Augmented Generation (RAG): LLMs lack knowledge of real-time amendments and specific circulars, leading to outdated or hallucinated advice. Systems must toggle between the LLM’s inherent knowledge and retrieval tools that give direct access to the latest statutes, notifications, and case laws. The retrieval datasets must be continuously updated to reflect the latest statutes, case law, etc., as models cannot “learn” these from static training weights alone.
• Human-in-the-loop: Given the risk of “overconfident errors” and hallucinations regarding judicial precedents, fully autonomous deployment is unsafe. Deployment must follow a human-in-the-loop model, with legal experts validating outputs, particularly for “Application” and “Justification,” which are identified as the primary bottlenecks to AI accuracy. Maintain meticulous audit trails and clearly separate deterministic outputs from generative ones to verify the provenance of every conclusion.

Disclaimer:

All comparative statements, rankings, scores, and performance observations presented herein arise solely from a controlled, methodology-based benchmarking exercise conducted as part of the LE-BTL research study using the IRAC+ evaluation framework. The results are based on specific test conditions, datasets, prompts, evaluation criteria, and scoring parameters defined exclusively for the purposes of this study.

References to third-party artificial intelligence models, products, services, trademarks, or brand names are made strictly for academic and research-based comparison. All such names and marks remain the property of their respective owners. Nothing contained herein shall be construed as implying any affiliation, endorsement, sponsorship, partnership, or commercial relationship with any third-party AI provider.

The findings reflect performance only within the defined scope and conditions of the study and do not constitute a general, definitive, ongoing, or future assessment of any AI model’s capabilities, accuracy, reliability, compliance, or suitability for any particular purpose. Actual performance may vary materially depending on system updates, deployment environments, user inputs, and other variables.

This publication is intended solely for informational and research purposes and does not constitute legal, technical, commercial, regulatory, or professional advice.

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[1] Jain, Nitish and Wadhwa, Naveen and Goyal, Pawan and Ghosh, Saptarshi and Pawar, Sankalp and Shinde, Abhishek and Boinepally, Karthik and Malpani, Vrinda V and K, Raaga, LLM Evaluations for Bharat Tax Laws (‘LE-BTL’). A Framework to Evaluate and Benchmark the Accuracy of Large Language Models (‘LLMs’) in the Context of the Indian Tax Laws (November 19, 2025). Available at SSRN: https://ssrn.com/abstract=5941734 or http://dx.doi.org/10.2139/ssrn.5941734

The post Taxmann.AI X IIT Kharagpur LLM Evaluation | LE-BTL Benchmark Study appeared first on Taxmann Blog.

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RBI Directions 2025 introduce a comprehensive regulatory overhaul covering priority sector lending, co-lending, credit risk management, Basel III norms, and borrower protection measures. These updates aim to strengthen prudential oversight, enhance transparency, and ensure a balanced flow of credit across sectors while aligning India’s banking framework with evolving economic and risk management requirements.

Table of Contents

1. Amendment to Prudential Regulations on Basel III Capital Framework and Investment Portfolio Norms for All India Financial Institutions (AIFIs)
2. Master Directions – Reserve Bank of India (Priority Sector Lending – Targets and Classification) Directions, 2025
3. Reserve Bank of India (Co-Lending Arrangements) Directions, 2025
4. Reserve Bank of India (Non-Fund Based Credit Facilities) Directions, 2025
5. Reserve Bank of India (Interest Rate on Advances) (Amendment Directions), 2025
6. Reserve Bank of India (Lending Against Gold and Silver Collateral) – (1st Amendment) Directions, 2025
7. Reserve Bank of India (Trade Relief Measures) Directions, 2025
8. Reserve Bank of India (Commercial Banks – Credit Risk Management) Directions, 2025

Check out IIBF X Taxmann's Banking & Finance Yearbook 2026 which is a comprehensive annual reference that delivers a clear, system-level understanding of regulatory, policy, legal, and sectoral developments shaping India's BFSI landscape. More than a compilation of circulars, it contextualises each regulatory change within the broader framework of financial stability, governance, consumer protection, and sustainable growth. The 2026 Edition reflects a phase of consolidation and recalibration—highlighting stronger bank balance sheets, declining NPAs, deeper digitalisation, and heightened focus on climate and sustainability risks. Structured for both professional application and exam readiness, it serves as an indispensable desk reference for banking professionals, regulators, compliance teams, and academic users.

1. Amendment to Prudential Regulations on Basel III Capital Framework and Investment Portfolio Norms for All India Financial Institutions (AIFIs)

1.1 Introduction

The Reserve Bank of India (RBI) has amended specific provisions under the Prudential Regulations on Basel III Capital Framework, Exposure Norms, Significant Investments, and Operation of Investment Portfolio Norms for All India Financial Institutions (AIFIs). The change aims to provide greater flexibility in investments aligned with the developmental mandates of AIFIs.

1.2 Summary

The amendment modifies paragraph 34.2 of the RBI Directions issued on September 21, 2023, governing prudential norms for AIFIs such as EXIM Bank, NABARD, NaBFID, NHB, and SIDBI.

As per the revised clause, investments made by AIFIs in long-term bonds and debentures (having a minimum residual maturity of three years at the time of investment) issued by non-financial entities will not be counted towards the 25% ceiling applicable to the Held to Maturity (HTM) category under the investment portfolio.

This relaxation enables AIFIs to extend greater long-term funding to infrastructure and industrial sectors without breaching prudential investment caps. It also clarifies that such investments, made under the statutory mandates of AIFIs, are consistent with sound risk management practices and capital adequacy requirements.

The amendment comes into effect from April 1, 2025, and has been issued under Section 45L of the Reserve Bank of India Act, 1934. All AIFIs are required to make necessary adjustments in their investment and accounting systems to comply with the revised provisions.

1.3 Comments/Rationale

The amendment encourages long-term financing by AIFIs, supporting credit flow to productive sectors while maintaining prudential control over portfolio risks.

Circular No. – RBI/2024-25/116|DOR.MRG.REC.60/00-00-017/2024-25 | Dated February 17, 2025

Reference Link – https://www.rbi.org.in/Scripts/NotificationUser.aspx?Id=12783&Mode=0

2. Master Directions – Reserve Bank of India (Priority Sector Lending – Targets and Classification) Directions, 2025

2.1 Introduction

The Reserve Bank of India (RBI) issued updated Master Directions on Priority Sector Lending (PSL) on March 24, 2025, superseding the earlier 2020 directions. These Directions, effective April 1, 2025, aim to ensure a structured and adequate flow of credit to key sectors contributing to socio-economic development, particularly those underserved despite being creditworthy.

2.2 Key Highlights

• Applicability – To all Commercial Banks, Regional Rural Banks (RRBs), Small Finance Banks (SFBs), Local Area Banks (LABs), and Urban Co-operative Banks (UCBs), excluding salary earners’ banks.
• Purpose – To delineate a framework that promotes credit flow to essential sectors for balanced and inclusive growth.

2.3 Main Provisions

• Categories under PSL – Agriculture, MSMEs, Export Credit, Education, Housing, Social Infrastructure, Renewable Energy, and Others.
• Revised PSL Targets:

1. 1. Domestic banks and large foreign banks – 40% of ANBC.
   2. RRBs and SFBs – 75% of ANBC.
   3. UCBs – 60% of ANBC.
   4. Agriculture – 18% of ANBC, of which 14% for Non-Corporate Farmers and 10% for Small and Marginal Farmers (SMFs).
   5. Weaker sections – 12% of ANBC.

• Adjusted Net Bank Credit (ANBC) – Computed as per revised formula incorporating exemptions, on-lending, and eligible investments.
• Regional Weighting Framework – Higher weight (125%) assigned to incremental PSL in districts with lower per capita PSL (below Rs. 9,000) and lower weight (90%) for high-credit districts (above Rs. 42,000).
• Sectoral Definitions and Eligibility:

1. 1. Agriculture: Includes farm credit, allied activities, infrastructure, and ancillary services.
   2. MSME: Loans to micro, small, and medium enterprises, start-ups (up to Rs. 50 crore), and factoring transactions.
   3. Housing: Loans up to Rs. 50 lakh for individuals (depending on population tier) and up to Rs.  12 crore for healthcare facilities.
   4. Renewable Energy: Loans up to Rs. 35 crore for projects; Rs. 10 lakh for households.

• On-Lending and Co-lending – Permitted to NBFCs, MFIs, and HFCs under specified limits (up to Rs. 10–20 lakh per borrower) with overall caps (5–10% of PSL portfolio).
• Monitoring and Reporting – Compliance to be monitored quarterly; shortfall in PSL targets to attract contributions to RIDF/NABARD and related funds with penal interest rates.

2.4 Comments/Rationale

The 2025 revision consolidates all PSL norms into one directive, enhancing clarity and operational efficiency for banks. The updated framework reflects RBI’s focus on inclusive credit expansion, regional balance, and support for emerging sectors such as renewable energy, agri-infrastructure, and start-ups.

Reference – RBI/FIDD/2024-25/128 (Master Directions FIDD.CO.PSD.BC.13/04.09.001/2024-25, March 24, 2025).

Link – https://www.rbi.org.in/Scripts/NotificationUser.aspx?Id=12799&Mode=0

3. Reserve Bank of India (Co-Lending Arrangements) Directions, 2025

3.1 Introduction

RBI issued the Co-Lending Directions, 2025 to create a uniform framework for joint lending by banks and NBFCs. The norms streamline governance, customer handling and risk sharing, replacing earlier fragmented guidelines. These Directions apply to all commercial banks (except SFBs, RRBs, LABs), AIFIs and NBFCs/HFCs from January 1, 2026.

3.2 Summary

The Directions require a formal co-lending agreement between partner REs, defining roles, underwriting standards, servicing responsibilities and grievance redressal. Each RE must retain a minimum 10% share of every loan. Co-lending does not apply to consortium or multiple banking arrangements, and if the model includes digital onboarding, the Digital Lending Directions also become applicable.

Loan agreements must clearly mention the servicing entity and borrower interface. Any change must be notified to the borrower. The Key Facts Statement (KFS) must reflect loan share, interest, charges, responsibilities and escalation paths. Partner REs classify the borrower’s exposure uniformly—if one RE reports SMA/NPA, the other must mirror it.

Co-lent loans must be disbursed through an escrow mechanism, and the partner RE must take its loan share within 15 days, failing which the loan stays solely with the originating RE. Disclosures on fees and APR must be transparent, and fees cannot include credit enhancements or guarantees except permissible DLG.

Priority Sector treatment can be applied independently by each RE for its own share. Transfer of co-lent loans must follow the MD–Transfer of Loan Exposures, 2021. Co-lent portfolios must be part of internal and statutory audits. REs must maintain business continuity plans to avoid disruption even if the co-lending arrangement ends.

DLG may be provided (by the originating RE) up to 5% of outstanding loans in line with Digital Lending rules. REs must publish on their websites a list of all active co-lending partners, and periodic financial disclosures must show details of the aggregate co-lent portfolio, including performance and DLG arrangements.

3.3 Comments/Rationale

These Directions bring consistency and strengthen borrower protection in co-lending models, where rapid growth had created variations in practices. The framework ensures transparency, standardised governance, clear customer interface, and balanced risk-sharing between banks and NBFCs.

Reference – RBI/2025-26/139DOR.STR.REC.44/13.07.010/2025-26. Dated: August 6, 2025

Link – https://www.rbi.org.in/Scripts/NotificationUser.aspx?Id=12888&Mode=0

4. Reserve Bank of India (Non-Fund Based Credit Facilities) Directions, 2025

4.1 Introduction

RBI issued the Non-Fund Based Credit Facilities (NFBF) Directions, 2025 to consolidate all guidelines related to bank guarantees, standby letters of credit (SBLCs), and other non-fund based exposures. The framework strengthens due-diligence, standardises risk management practices and aligns NFBF norms with the updated capital, credit and exposure norms. These Directions come into force from January 1, 2026.

4.2 Summary

The Directions define all NFBF instruments including guarantees, SBLCs, performance guarantees, financial guarantees, co-acceptances, letters of comfort, bid bonds, shipping guarantees and similar contingent facilities. Banks must ensure that the creditworthiness of the applicant is established before issuing any facility. NFBFs can be issued only after proper appraisal, sanction under the bank’s credit policy, and execution of counter-indemnity or security documents.

Banks must ensure that NFBF issuance is linked to genuine underlying transactions. Guarantees or SBLCs cannot be issued for activities prohibited under FEMA, FCRA or any other law. Banks must avoid issuing “comfort letters” that create implicit financial obligations unless approved under board-approved policies. NFBFs for related parties must follow arm’s-length principles and stricter due-diligence.

Pricing must be risk-based, and banks should carefully assess the financial position and repayment ability of the applicant, taking into account past performance. For infrastructure, large exposures or project-related obligations, banks must ensure that the project is viable and implementation risks have been evaluated. Issuance of financial guarantees on behalf of NBFCs must follow the restrictions already specified under the bank–NBFC credit flow guidelines.

Banks must comply with exposure ceilings under the Large Exposure Framework (LEF). For capital adequacy purposes, NFBFs must be converted using appropriate Credit Conversion Factors (CCF) as per the Basel III capital framework. Banks must compute exposure on the higher of the amount guaranteed or the amount outstanding under related credit facilities.

Guarantees under Government-sponsored schemes, trade-related obligations, performance-based contracts and MSME-related projects must follow the specific programme rules but remain subject to the general due-diligence and risk-management criteria under these Directions. All NFBF portfolios must undergo periodic internal audit and supervisory review. Banks must disclose contingent liabilities transparently in their financial statements, including aging and risk characteristics.

4.3 Comments/Rationale

These Directions unify all earlier fragmented rules on guarantees and SBLCs, ensuring stronger credit discipline and better risk capture for contingent exposures. By aligning issuance, monitoring and capital treatment with Basel III norms, the framework improves prudential oversight, promotes transparency and mitigates risks arising from indiscriminate guarantees.

Reference Link: RBI/2025-26/140. DOR.CRE.REC.45/21.04.048/2025-26. Dated: August 6, 2025

Link: https://www.rbi.org.in/Scripts/NotificationUser.aspx?Id=12889&Mode=0

5. Reserve Bank of India (Interest Rate on Advances) (Amendment Directions), 2025

5.1 Introduction

RBI has issued amendments to the Interest Rate on Advances Directions, 2016, and aligned changes to the Floating Interest Rate Reset Circular (2023) and associated FAQs. The objective is to improve borrower transparency, allow flexibility for interest rate choices, and help banks retain customers through fair and non-discriminatory pricing adjustments.

5.2 Summary

A new provision has been added to the Interest Rate on Advances Directions allowing banks to reduce certain components of the spread for any loan category before the mandatory three-year review cycle, provided such reduction is:

• justified,
• non-discriminatory, and
• in line with the bank’s Board-approved policy.

This flexibility is intended to support customer retention while maintaining transparent interest rate practices.

Amendments have also been introduced in the Circular on Reset of Floating Interest Rate on EMI-based Personal Loans (August 18, 2023). At the time of rate reset, regulated entities (REs) may offer borrowers an option to switch to a fixed interest rate, based on the institution’s Board-approved policy.

The policy may define:

• eligibility to switch, and
• number of allowable switches during the loan tenor.

This enhances borrower choice and allows customers to shift from variable-rate volatility to fixed-rate certainty.

5.3 Comments/Rationale

The amendments increase borrower flexibility, improve clarity in personal loan reset practices, and enable banks to adjust spreads fairly to retain customers. They reduce rigidity in interest rate policies while preserving transparency.

Reference Link: RBI/2025-26/83–DOR.CRE.REC.51/13.03.00/2025-26

Link: https://www.rbi.org.in/Scripts/NotificationUser.aspx?Id=12902&Mode=0

6. Reserve Bank of India (Lending Against Gold and Silver Collateral) – (1st Amendment) Directions, 2025

6.1 Introduction

RBI issued amendments to the Lending Against Gold and Silver Collateral Directions, 2025 to clarify certain restrictions, especially relating to loans for purchase of gold and loans against primary gold/silver. The update also aligns earlier circulars into the Master Direction framework. The amendments take effect from October 1, 2025 for lenders who have already adopted the original Directions.

6.2 Summary

Banks and lending institutions cannot grant any loan or advance:

• for the purchase of gold in any form (primary gold, jewellery, ornaments, coins),
• for the purchase of financial assets backed by gold or silver (e.g., Gold ETFs, Gold Mutual Funds), and
• against primary gold, primary silver, or financial assets backed by primary gold or silver.

However, the amendment introduces an important exception: Scheduled Commercial Banks and Tiers 3 & 4 Urban Co-operative Banks may extend need-based working capital finance to borrowers who use gold or silver as a raw material or input in manufacturing or industrial processing.

Under this exception:

• the gold or silver used as raw material may also be accepted as collateral;
• banks must ensure borrowers do not use such finance for acquiring or holding gold/silver for investment or speculative activities.

This provision aims to support genuine industrial users—such as jewellery manufacturers—while preventing speculative or arbitrage-driven lending against gold/silver.

6.3 Comments/Rationale

The amendment improves clarity on what types of gold/silver-related lending are prohibited versus permitted. It preserves the policy stance against speculative financing while enabling legitimate working capital support for industries that use gold or silver as productive inputs.

Reference Link: RBI/2025-26/84–DOR.CRE.REC.52/21.01.023/2025-26

Link: https://www.rbi.org.in/Scripts/NotificationUser.aspx?Id=12903&Mode=0

7. Reserve Bank of India (Trade Relief Measures) Directions, 2025

7.1 Introduction

RBI has issued a special relief framework to support exporters affected by global trade disruptions. The Directions allow regulated entities to extend temporary moratoriums, deferments, extended export credit periods, and relaxed working capital norms, while ensuring asset classification continuity. The measures come into force immediately.

7.2 Summary

The Directions apply to Commercial Banks, Co-operative Banks, NBFCs (including HFCs), All-India Financial Institutions, and Credit Information Companies (for reporting-related provisions). Each regulated entity (RE) must frame a Board-approved policy stating eligibility and objective criteria for granting relief.

7.3 Eligibility Criteria

Borrowers qualify only if:

• They are engaged in export of sectors listed (e.g., chemicals, apparel, machinery, plastics, footwear, pearls & precious stones, electronics, metals, vehicles, furniture).
• They had outstanding export credit as on August 31, 2025.
• Their accounts were Standard on the same date. REs other than the sanctioning bank may rely on certification from lending REs to confirm eligibility.

7.4 Relief Measures

Moratorium/Deferment (Sept. 1 – Dec. 31, 2025)

• REs may grant moratorium on term loan instalments (principal/interest).
• For CC/OD facilities, interest recovery may be deferred.
• Interest continues to accrue but only simple interest applies; no compounding.
• Accrued interest may be converted into a Funded Interest Term Loan (FITL), repayable between April–September 2026.
• REs may reassess drawing power by reducing margins or revising limits during the effective period.

Extended Export Credit Tenor

• REs may allow up to 450 days for pre- and post-shipment export credit disbursed till March 31, 2026.
• For packing credit sanctioned on/before August 31, 2025 where goods could not be dispatched, liquidation may be permitted from:

1. 1. domestic sale proceeds, or
   2. substitution of export contract.

7.5 Asset Classification & Provisioning

Asset Classification

• Moratorium/deferment period is excluded for NPA counting.
• Such relief will not be treated as restructuring, avoiding automatic downgrade.
• After the relief period, normal IRACP norms apply.
• REs must report to CICs accordingly; CICs must ensure borrower credit history is not adversely impacted.

Provisioning

• For eligible standard accounts that were in default as on August 31, 2025, REs must create 5% general provision by Dec. 31, 2025.
• Provision may be adjusted against future slippages; any remaining balance must be adjusted/written back by June 30, 2026.

7.6 Disclosure & Reporting

• REs must maintain detailed MIS of reliefs provided.
• Fortnightly reporting (15th & month-end) must be submitted via RBI’s DAKSH platform.

7.7 Comments/Rationale

The framework cushions exporters from global trade shocks by offering temporary liquidity relief without penal asset classification. It ensures business continuity for viable export units while maintaining prudential discipline.

Reference: RBI/2025-26/96 – DOR.STR.REC.60/21.04.048/2025-26

Link: https://www.rbi.org.in/Scripts/NotificationUser.aspx?Id=12921&Mode=0

8. Reserve Bank of India (Commercial Banks – Credit Risk Management) Directions, 2025

8.1 Introduction

RBI has issued updated and consolidated Credit Risk Management Directions for commercial banks, covering appraisal standards, governance controls, statutory restrictions, exposure rules, UFCE assessment, country risk, valuation processes, and current account norms. These Directions replace earlier fragmented guidelines with a uniform framework.

8.2 Summary

Banks must adopt a Board-approved Credit Risk Management Policy, covering appraisal standards, sectoral limits, current account rules, valuation norms, and monitoring frameworks.

The post RBI Directions 2025 – PSL | Co-Lending | Credit Risk Updates appeared first on Taxmann Blog.

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Editorial Team – [2026] 183 taxmann.com 650 (Article)

Global IDT Insights provides a weekly snippet of tax news specifically related to Indirect Taxes from around the globe.

1. Mauritius Issues a VAT Guide for Foreign Suppliers of Digital and Electronic Services

Mauritius has issued a Guide for Foreign Suppliers of Digital and Electronic Services following amendments to the Value Added Tax Act introduced by the Finance Act 2025. The Guide explains the VAT obligations applicable to foreign suppliers making supplies of digital and/or electronic services to persons in Mauritius under new section 14A of the VAT Act. The provisions bring these supplies within the scope of VAT, effective from 01-01-2026.

The guidance sets out the scope of digital or electronic services covered under Part III of the Tenth Schedule to the VAT Act; the compulsory VAT registration requirement; compliance procedures; the appointment of tax representatives; return filing; payment obligations; and related enforcement consequences. It applies to foreign suppliers without a permanent establishment in Mauritius, or whose place of abode is outside Mauritius, that supply digital or electronic services in the course of business to persons in Mauritius.

Key aspects of this guidance include:

(a) Digital or electronic services specified under the VAT Act are brought within the VAT net – Digital or electronic services covered include supplies of images or texts such as photographs, screensavers, electronic books and other digitized documents; supplies of music, films, television shows, games and programmes on demand; supplies of applications, software and software maintenance; website supply or web hosting services; advertising space on a website; online magazines; and distance maintenance of programmes and equipment. These services are specified under Part III of the Tenth Schedule to the VAT Act. Where supplied by a foreign supplier to a person in Mauritius, such services fall within the scope of VAT under section 14A.

(b) VAT must be accounted for on the earlier of invoice or payment – VAT charged or collected must be included in the VAT return for the relevant month or quarter based on the earlier of the date on which an invoice is issued or payment is received for the supply made to the person in Mauritius. VAT returns must be submitted electronically after the end of every taxable period within twenty days or such other time as may be prescribed. A list of taxable supplies made to persons in Mauritius must also be provided electronically at the time of filing.

(c) Monthly or quarterly filing depends on annual turnover threshold – Where the annual turnover of taxable supplies in Mauritius exceeds MUR 10 million, VAT returns must be submitted on a monthly basis. Where the annual turnover falls below this threshold, the foreign supplier may opt to submit VAT returns on a quarterly basis. VAT payments must be made electronically at the time of filing the VAT return.

(d) Foreign suppliers cannot claim input tax, and the reverse charge ceases upon registration – No input tax is allowable to a foreign supplier of digital or electronic services under section 21(2)(i) of the VAT Act. Once a foreign supplier is VAT registered in Mauritius, the reverse charge mechanism will no longer apply to digital and electronic services supplied to VAT-registered businesses. The registered foreign supplier must charge VAT and report all supplies made in Mauritius.

(e) Non-compliance attracts penalties and interest under the VAT Act – Failure to register for VAT, submit VAT returns, or pay VAT within the prescribed time renders the foreign supplier liable to penalties and interest as provided under the VAT Act. Assistance and clarification may be obtained from the MRA through the specified contact channels.

Source – Official Guide

Click Here To Read The Full Article

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Circular eF.No. IFSCA-TAS/3/2025-FSSRD, Dated: 24.02.2026

The International Financial Services Centres Authority (IFSCA) has released a consultation paper inviting comments from market participants, stakeholders and the public on the draft IFSCA (Financial Advisers) Regulations, 2026.

The draft regulations propose to establish a comprehensive regulatory framework for financial advisory services within the International Financial Services Centre (IFSC).

1. Objective of the Proposed Regulatory Framework

The proposed regulations aim to provide a structured framework for financial institutions operating in IFSC to engage IFSC Financial Advisers for rendering or soliciting financial services.

The framework seeks to:

• Strengthen investor protection beginning from the advisory stage
• Ensure greater transparency and accountability in advisory activities
• Align the IFSC ecosystem with global regulatory and fiduciary standards
• Facilitate responsible growth of advisory-led financial services

2. End-to-End Advisory Oversight

The draft regulations propose a structured advisory model that enables comprehensive regulatory oversight across the entire client journey, including:

• Initial client engagement and onboarding
• Risk profiling and suitability assessment
• Product recommendation and advisory support
• Execution through regulated intermediaries

This end-to-end oversight is intended to enhance investor protection, ensure suitability of financial products, and reinforce market integrity within IFSC.

3. Focus on Retail and Diaspora Investors

The consultation paper highlights the significant opportunity presented by the Indian diaspora and retail investor segment:

• The global Indian diaspora comprises approximately 35.4 million overseas Indians
• Overseas Indians remitted around USD 135.46 billion to India during 2024–25
• Investments by diaspora investors into GIFT IFSC-based funds have exceeded ₹60,998 crore (approx. USD 7 billion)

Retail and Non-Resident Indian (NRI) investors typically require enhanced engagement, financial education, and personalised advisory support. Access to regulated IFSC advisers capable of delivering transparent, fiduciary-oriented, and multi-product advice can significantly improve investor confidence and participation.

4. Enabling Scalable and Accountable Advisory Networks

The proposed framework is intended to enable regulated IFSC institutions to expand retail and diaspora outreach through structured advisory networks while maintaining:

• Institutional accountability
• Clearly defined activity boundaries
• Robust supervisory and compliance safeguards

This balanced approach aims to support growth in advisory-led financial services without compromising regulatory discipline or investor protection.

5. Invitation for Public Comments

IFSCA has invited comments and suggestions from stakeholders, market participants, and the public on the draft regulations. Feedback received during the consultation process will help refine the proposed framework and support the development of a globally aligned and investor-focused advisory ecosystem within IFSC.

Click Here To Read The Full Circular

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Press Release, dated 23-02-2026

The Central Board of Direct Taxes (CBDT) has issued a press release regarding amendments to the India–France Double Taxation Avoidance Convention (DTAC). During the recent visit of the President of France to India, the Governments of India and France signed an Amending Protocol to update and strengthen the existing tax treaty framework between the two countries.

1. Taxing Rights on Capital Gains from Shares

The Amending Protocol provides full taxing rights in respect of capital gains arising from the sale of shares to the jurisdiction in which the company whose shares are transferred is a resident.

Accordingly, capital gains from the transfer of shares will be taxable exclusively in the country of residence of the company, providing clarity and certainty in taxation of cross-border share transfers.

2. Deletion of Most-Favoured-Nation (MFN) Clause

The Protocol removes the Most-Favoured-Nation (MFN) Clause from the existing DTAC Protocol.

This deletion resolves all interpretational and implementation issues associated with the MFN clause and simplifies the treaty structure between India and France.

3. Revised Taxation of Dividends

The Amending Protocol revises the taxation framework for dividends by replacing the earlier uniform 10% tax rate with a split-rate structure:

• 5% Tax Rate – Applicable where the beneficial owner holds at least 10% of the capital of the dividend-paying company
• 15% Tax Rate – Applicable in all other cases

This change aligns dividend taxation with prevailing international treaty standards.

4. Modification to Fees for Technical Services (FTS)

The definition of Fees for Technical Services (FTS) has been modified to align with the definition contained in the India–US Double Taxation Avoidance Agreement.

This alignment is expected to enhance consistency in treaty interpretation and reduce disputes relating to the characterisation and taxation of technical service payments.

5. Expansion of Permanent Establishment (PE) Scope

The scope of Permanent Establishment (PE) has been expanded by introducing provisions for Service PE.

This expansion reflects the growing importance of cross-border service activities and ensures appropriate taxation of service-based business operations.

6. Strengthening Exchange of Information and Tax Cooperation

The Amending Protocol updates the provisions relating to Exchange of Information in line with international standards. It also introduces a new Article on Assistance in the Collection of Taxes, which will:

• Facilitate seamless exchange of tax-related information
• Strengthen cooperation between Indian and French tax authorities
• Improve enforcement and recovery of tax claims across jurisdictions

These changes are intended to enhance transparency and administrative cooperation between the two countries.

7. Incorporation of BEPS MLI Provisions

The Protocol incorporates the applicable provisions of the Base Erosion and Profit Shifting (BEPS) Multilateral Instrument (MLI) into the DTAC.

These provisions had already become applicable following the signing and ratification of the MLI by both India and France. Their incorporation into the treaty ensures alignment with global anti-tax avoidance standards and provides greater clarity in treaty application.

8. Conclusion

The Amending Protocol represents a significant update to the India–France DTAC, aligning it with international tax standards, enhancing certainty in cross-border taxation, strengthening administrative cooperation, and supporting a more transparent and robust tax treaty framework between the two countries.

Click Here To Read The Full Press Release

The post India–France Amend DTAA | Residence Country Gets Capital Gains Tax Rights appeared first on Taxmann Blog.

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Press Release; Dated: 20.02.2026

The International Financial Services Centres Authority (IFSCA) and the Indian Institute of Corporate Affairs (IICA) have signed a Memorandum of Understanding (MoU) at the IFSCA Headquarters in GIFT IFSC. The MoU formalises cooperation between the two institutions across areas relevant to the development and governance of the IFSC ecosystem.

1. Areas of Collaboration

The MoU establishes a framework for collaboration in key domains critical to the growth and regulatory strengthening of IFSC, including:

• Corporate Law
• Sustainable Finance
• Environmental, Social and Governance (ESG)
• Cross-Border Transactions
• Corporate Restructuring
• Research and policy-oriented activities relevant to IFSC

This collaborative framework is intended to support capacity-building and knowledge development aligned with the evolving needs of the international financial services ecosystem.

2. Training, Knowledge and Advocacy Initiatives

Under the MoU, IFSCA and IICA will jointly undertake a range of initiatives, including:

• Training and capacity-building programmes
• Knowledge-sharing and research initiatives
• Advocacy and outreach events

These initiatives aim to strengthen regulatory processes, enhance governance standards, and support professional and institutional capability within the IFSC framework.

3. Strengthening Regulatory and Governance Standards

The partnership is expected to contribute to improved regulatory effectiveness and governance practices within IFSC by leveraging IICA’s expertise in corporate affairs and policy research alongside IFSCA’s regulatory and institutional mandate.

Overall, the collaboration seeks to reinforce the IFSC ecosystem through structured knowledge exchange, professional development, and policy-oriented engagement.

Click Here To Read The Full Press Release

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1. Facts

Zenith Manufacturing Limited, hereinafter referred to as “the company”, is engaged in the manufacture of industrial equipment and prepares its financial statements in accordance with Ind AS.

As per its approved Remuneration Policy, the company pays a performance incentive to its senior management team, including the CEO and CFO. The incentive is computed as 4% of annual EBITDA, subject to the condition that EBITDA exceeds Rs. 40 crore.

The policy, however, states only that:

“Incentive shall be calculated at 4% of annual EBITDA.”

The policy does not clarify whether EBITDA is to be computed before or after charging the performance incentive expense.

For the financial year ended 31 March 2026:

• EBITDA before charging performance incentive (as per draft financials) is Rs. 50 crore.
• Estimated incentive at 4% amounts to Rs. 2 crore (if calculated before charging incentive).
• Statutory audit is completed in May 2026.
• Post-audit adjustments reduce EBITDA (before incentive) to Rs. 47 crore.
• The Board formally approves the incentive payout in June 2026.

While finalising financial statements for the year ended 31 March 2026, management faced the following issues:

(a) Whether a constructive obligation exists as at 31 March 2026 despite board approval being pending?

(b) Whether EBITDA for incentive computation should be considered before or after charging the incentive expense, given the policy is silent?

(c) Whether EBITDA can be reliably estimated before completion of audit adjustments?

2. Relevant Provisions

Ind AS 19 – Employee Benefits

Para 11

An entity shall recognise a liability when an employee has provided service in exchange for employee benefits to be paid in the future.

When an employee has rendered service to an entity during an accounting period, the entity shall recognise the undiscounted amount of short-term employee benefits expected to be paid in exchange for that service:

(a) as a liability (accrued expense), after deducting any amount already paid. If the amount already paid exceeds the undiscounted amount of the benefits, an entity shall recognise that excess as an asset (prepaid expense) to the extent that the prepayment will lead to, for example, a reduction in future payments or a cash refund.

(b) as an expense, unless another Ind AS requires or permits the inclusion of the benefits in the cost of an asset (see, for example, Ind AS 2, Inventories, and Ind AS 16, Property, Plant and Equipment).

Para 19

An entity shall recognise the expected cost of profit-sharing and bonus payments under paragraph 11 when, and only when:

(a) the entity has a present legal or constructive obligation to make such payments as a result of past events; and

(b) a reliable estimate of the obligation can be made. A present obligation exists when, and only when, the entity has no realistic alternative but to make the payments.

Ind AS 37 – Provisions, Contingent Liabilities and Contingent Assets

Para 14

A provision shall be recognised when:

(a) an entity has a present obligation (legal or constructive) as a result of a past event;

(b) it is probable that an outflow of resources embodying economic benefits will be required to settle the obligation; and

(c) a reliable estimate can be made of the amount of the obligation. If these conditions are not met, no provision shall be recognised.

Click Here To Read The Full Story

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Case Details: Tvl. C. Ragupathi Contractor vs. Deputy State Tax Officer - [2026] 183 taxmann.com 556 (Madras)

Judiciary and Counsel Details

• Krishnan Ramasamy, J.
• Sudalai Muthu N. for the Petitioner.
• R.Suresh Kumar, AGP for the Respondent.

Facts of the Case

The petitioner challenged the impugned assessment order. He submitted that he was not aware of the issuance of the show cause notice (SCN) uploaded on the GST portal and that the original of the said notice was not furnished. It was further contended that the impugned assessment order was passed without affording any opportunity of personal hearing. The petitioner relied on Section 169 of the CGST Act and submitted that the lack of effective service rendered the proceedings and order unsustainable. The matter was accordingly placed before the High Court.

High Court Held

The High Court held that sending a notice by uploading it on the GST portal constitutes sufficient service; however, where there was no response from the taxpayer, the jurisdictional officer under CGST should have strictly explored alternative modes of service, preferably by way of RPAD. The Court observed that the failure to provide such opportunities resulted in ineffective service to the petitioner. Consequently, the impugned assessment order confirming the demand was set aside, and the matter was remanded. It directed that the assessment be reconsidered in accordance with the provisions of Section 169 of the CGST Act and the Tamil Nadu GST Act.

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Case Details: Deputy Commissioner of Income-tax vs. Bhupinder Singh Bhalla - [2026] 183 taxmann.com 465 (Delhi-Trib.) (TM)

Judiciary and Counsel Details

• Mahavir Singh | Vice President (As a third Member), Vimal Kumar | Judicial Member & Brajesh Kumar Singh | Accountant Member
• Jitender Singh, CIT-DR for the Appellant.
• Somil Aggarwal, Deepesh Garg & Dr Rakesh Gupta, Advs. for the Respondent.

Facts of the Case

Assessee-individual sold agricultural land and invested sale proceeds in the purchase of three agricultural lands. While filing the return of income, the assessee claimed exemption under section 54B. During the assessment proceedings, the Assessing Officer (AO) denied the exemption on the ground that the land was not used for agricultural purposes.

The matter reached the Delhi Tribunal.

ITAT Held

The Tribunal held that the assessee had established that the land was assessed to land revenue, as was evident from the Khasra/Girdawri and Halqa Patwari report. Even the land was assessable under the Delhi Land Revenue Act, and the competent authorities, i.e., the Sub-Divisional Magistrate, Kalkaji District, and the Deputy Commissioner/Collector (South) Saket, passed an order that the land was primarily used for agricultural purposes.

Further, it was noted that the Assessing Officer and the revenue relied on the report of the Inspectors who visited the premises and reported that no agricultural activity was carried out. These Inspectors clicked photographs of the property, but they never informed the assessee of the visit, and it appeared to be a discrete enquiry conducted by them without informing the party. The authenticity of this report and the photographs reproduced in the assessment order were specifically discarded by the assessee. Even otherwise, the Inspectors’ Report was dated 28-12-2018, whereas the point of transfer of land was dated 07-12-2015. Thus, the report of the Inspectors and consequent photographs cannot be taken into consideration while adjudicating this issue, as it was without any evidence contrary to the facts on record.

In the instant case, the character of this land, as on the date of transfer, was agricultural land, and the revenue records also prove that the agricultural land was put to use. Moreover, this is supported by the assessee consistently declaring agricultural income, and the quantum of agricultural income cannot be the reason for disallowing the claim of deduction under section 54B. The assessee proved that the land is agricultural in nature and was used for agricultural activity as per the records. The revenue had not discharged the onus of disproving the same.

List of Cases Referred to

• ITO v. Babita Gupta [2023] 147 taxmann.com 317 (Delhi-Trib.)
• S. Sundaramurthy v. Pr. CIT [2020] 113 taxmann.com 341/269 Taxman 107 (Madras).

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