India is a land where every month brings a new reason to celebrate. Festivals are woven into the very fabric of our lives — vibrant threads of joy that unite communities and spark waves of happiness across the nation. Yet, beyond these celebrations lies a deeper rhythm: one where culture drives commerce and tradition fuels economic growth.
From Ugadi to Diwali, each festive season ignites demand, shapes retail strategies, and propels India's economic momentum.
Explore our latest KGS Report to discover how festivals influence GDP, transform industries, and offer powerful insights for policymakers and businesses worldwide.
It's a compelling read on how culture and economy move in perfect harmony.
With the Social Security (Central) Rules, 2026 coming into effect, employers should revisit their creche obligations. Section 67 of the Code on Social Security, 2020 (“Code” for brevity), read with the Rules, requires eligible employees to receive creche support, either through a compliant facility or, where permitted, a monetary allowance.
Employers must make a creche facility or permitted alternative available to eligible employees. They need not set up their own creche and establishments may use a common creche facility or tie up with an existing creche, if the applicable conditions are met.
The creche should be available within a 1-kilometre radius of the workplace. Before engaging an external or shared facility, the employer should verify that this distance requirement is satisfied.
The Rules also permit a monetary allowance instead of a physical creche facility. This should be structured as an allowance and not a reimbursement, meaning employees should not be required to submit bills or proof of actual creche expenses. The statutory minimum is ₹500 per month per child.
At a minimum, the benefit must be extended to
Employers may extend it to other employees as well, but limiting the benefit only to female employees would not meet the minimum requirement under the Rules.
Yes. The Rules require majority employee agreement to the creche or allowance arrangement. Employers should circulate a creche policy, obtain acknowledgments and maintain records of acceptance. Unanimous consent is not necessary.
The Rules do not expressly exclude remote employees. However, if the benefit is linked to a workplace-based creche, employers may have a reasonable basis to limit it to onsite or hybrid employees, if the policy clearly states this.
The creche requirement places a clear responsibility on employers to provide a compliant facility or permitted monetary alternative. Policies should cover location, eligibility, consent, payment structure and any limits for remote employees.
India's restructuring landscape has changed sharply in the past eighteen months. The Income-tax Act, 2025 replaced the 1961 statute from 1 April 2026, the Ministry of Corporate Affairs has widened the fast-track merger route, the Competition Commission of India (CCI) is bedding down a deal-value-based regime, and the Reserve Bank of India (RBI) now allows banks to fund acquisitions. The real challenge lies in how these regimes interact.
Together, these reforms reward careful sequencing: choosing the NCLT or fast-track route with tax consequences in view, aligning CCI clearance with financing conditions, and structuring leverage to satisfy both RBI covenants and tax scrutiny. Coordinating these workstreams from day one means faster closings and fewer surprises.
What does it mean to “bring money back to India”? Most will describe a single event. But under the Foreign Exchange Management Act (FEMA), it's actually two: realisation and repatriation. The difference? Realisation refers to the moment a resident's claim to foreign exchange turns into money actually received, and repatriation, the subsequent act of bringing that money into India through banking channels.
The gap between the two – in time, in documentation, and in regulatory consequence — is where most FEMA contraventions quietly occur.
FEMA doesn't insist that every foreign exchange balance land in India instantly. Residents are permitted to maintain specific foreign currency accounts abroad:
These exceptions exist precisely because forcing immediate conversion of every foreign exchange receipt would be commercially disruptive.
Outside these carve-outs, however, the default rule under the Foreign Exchange Management (Realisation, Repatriation and Surrender of Foreign Exchange) Regulations, 2015 still applies. Amounts due to a resident must be realised and, unless specifically exempted, repatriated within the prescribed period.
The realisation-repatriation gap applies with equal force to both capital and current account transactions. Whether the money at stake is an export invoice falling due on the current account, or a disinvestment falling due on the capital account, FEMA draws no distinction on account of the transaction's nature — only on whether the two-step discipline of realisation followed by repatriation has actually been observed.
The lifecycle plays out identically across both:
Realisation is about the counterparty's obligation being discharged — money has actually changed hands. Repatriation is about what the resident then does with it — surrendering it to an Authorised Dealer, converting it to rupees, or crediting it to a permitted account in India.
A transaction can be realised without being repatriated (money received and simply parked abroad, whether the same is allowed or not), but it cannot be repatriated without first being realised.
Where a resident inherits foreign bank balances, securities or property from a person resident outside India, FEMA doesn't force an immediate unwind. Certain foreign currency holdings may continue to be retained, subject to conditions often through an RFC account.
What doesn't automatically follow, though, is a repatriation holiday: income earned on inherited assets, and proceeds on their eventual sale, generally still fall back into the realisation-repatriation framework unless a specific permission applies.
Realization and Repatriation may form part of the same transaction, but FEMA treats them as distinct obligations. For export, the distinction is often less visible because proceeds are ordinarily received through Indian Banking Channels, nevertheless, Export proceeds must nevertheless be realised and repatriated within the prescribed period. For exports on or after 1 October 2026, this is 9 months from the date of export, or 12 months where the export is invoiced and/or settled in INR, under Reg. 5(1) of the FEMA (Export and Import of Goods and Services) Regulations, 2026, as amended on 22 September 2026. The AD bank can extend this for sufficient and reasonable cause.
For overseas investments, the separation is more evident. A dividend, disinvestment consideration or other entitlement would be considered realized when due, however as per the Overseas Framework, such dues are required to be repatriated to India within 90 days of becoming due.
Similarly, Resident Individual are required to repatriate any foreign funds earned or parked abroad within 180 days, unless this funds are reinvested in FEMA permissible instruments
The takeaway for businesses is simple: don't treat "money received abroad" as the finish line. Realisation only closes half the obligation. Repatriation closes the other half, and FEMA tracks failures on both. Put simple, realization answers whether the money has been received, repatriation answers whether it has been brought back to India, or otherwise dealt with in a manner FEMA permits. That distinction may appear technical, but it lies at the center of India’s foreign exchange framework.
Ask anyone who has built a valuation model how much of the work was thinking and how much was formatting, and the answer is usually uncomfortable. Technology is steadily taking over this part of the job, and that is a good thing. The harder question is where the line falls between what a tool can do and what still requires a professional judgement.
Valuation work has been quietly automating for some time, and the pace has picked up in recent times.
Data collection is the most visible change. Screening for comparable companies, pulling financial statements, extracting trading multiples, and building peer sets can now be done in minutes using market data platforms and screening tools rather than days of manual compilation.
Model building has become largely templated. Firms maintain standardised DCF and comparable company models where the mechanics are pre-built and only the inputs change. Sensitivity tables, scenario toggles, and output summaries generate themselves.
Document processing has improved sharply. Financial statements, agreements, and tax orders can be read and structured automatically, reducing the manual data entry that used to consume a meaningful share of an engagement's budget.
Report drafting has followed. Standard sections covering methodology descriptions, limiting conditions, and industry overviews are increasingly assembled from libraries rather than written from scratch each time.
The gains are real, and they concentrate in a few areas.
Speed is the obvious one. Work that previously took a week can often be completed in a day.
Consistency improves. A firm using standardised models applies the same structure, the same conventions, and the same checks across every engagement. This matters for quality control and for peer review.
Error rates fall. Formula errors, broken links, and transcription mistakes are a genuine risk in manually built spreadsheets.
Coverage widens. When screening comparables is cheap, a valuer can consider a wider peer set and test more scenarios rather than settling for the first workable option.
The limitations are equally clear, and they cluster around judgement.
Selecting comparables is the most obvious example. A screening tool can return thirty companies matching an industry code and a revenue band. Deciding which five are genuinely comparable requires understanding the subject company's business model, customer concentration, geographic exposure, and stage of maturity.
Normalisation adjustments cannot be automated in any meaningful sense. Deciding whether promoter remuneration is above market, whether a related party rental is at arm's length, or whether a bad debt write off is genuinely one off requires knowledge of the business and its context that no dataset contains.
Assessing management projections is similarly resistant. A model will discount whatever cash flows are entered into it. Judging whether those projections are achievable, whether the revenue assumptions align with market reality, and whether the margin expansion is credible is the actual valuation work.
Company specific risk assessment is judgement throughout. Key person dependence, customer concentration, regulatory exposure, and litigation risk all affect value, and none of them can be read off a screen.
For unlisted Indian companies, the constraints are sharper than the general case suggests.
The available data is thin. There are no observable market prices, comparable transaction data is often unavailable, and where listed peers exist, they typically differ substantially in size and structure. Automation is most powerful where data is abundant, and here it is not.
Financial information quality is variable. Reported financials in closely held companies are shaped by adjustments and ownership arrangements, which means the inputs feeding any automated process require manual assessment before they can be relied upon.
The adjustments that matter most are qualitative. Discounts for lack of marketability, control premiums, and key person risk are exactly the areas where judgement dominates and where a mechanically generated output carries the least weight.
Technology has genuinely improved valuation work by removing a substantial amount of mechanical effort and reducing avoidable error. What it has not done is reduce the need for judgement, and in some respects it has increased it. When the mechanics become effortless, the quality of a valuation rests even more heavily on the assumptions selected and the reasoning applied.
For work on unlisted Indian companies, where data is limited and adjustments are largely qualitative, the professional contribution remains the substance of the engagement rather than an overlay on top of it.
Automation handles the parts of valuation that are repetitive, rule based, and data driven, and it handles them well. It does not select comparables, assess whether projections are realistic, decide what normalisation adjustments are appropriate, or evaluate company specific risk. Those remain professional judgements, and they are what a valuation report is actually being relied upon for. The practical approach is to automate aggressively where the work is mechanical, validate every output rather than trusting it, and recognise that the signature at the end of the report carries the same weight whatever tools were used to prepare it.
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