Rainfall derivatives have arrived in India. We need 3 steps to make them work

The new RAINMUMBAI contract covers the monsoon months and makes a payout based on the occurrence and magnitude of predefined weather conditions. It’s different from insurance.

26 May, 2026
The Print

This is the time of the month when large parts of India wait desperately for some sign of the monsoon. Many businesses carry monsoon risk on their books. Too much or too little rain can cause lots of damage.

So, when the NCDEX issued a circular last week announcing a Liquidity Enhancement Scheme for Mumbai Rainfall Futures (ticker: RAINMUMBAI), one naturally got excited. The contract covers the monsoon months and makes a payout based on the occurrence and magnitude of predefined weather conditions. This is different from insurance, which compensates for actual loss. It’s the beginning of a market for monsoon risk, and it is about time India had one. How will the RAINMUMBAI contract actually work?

Imagine you run a mid-sized construction company in Mumbai with a large infrastructure project underway. Your July budget, which factors in some predictable rainfall, assumes your crew works 20 days, unlike the usual 25 days in non-monsoon months. But if July is an unusually heavy rainfall month, your workers cannot be on site, and your losses increase.

With RAINMUMBAI, you can buy a July futures contract that is structured to pay off when Mumbai’s measured rainfall in July exceeds a certain level, say 700 mm, for the month. The measurement has to come from a designated source such as the India Meteorological Department (IMD). If July ends up getting much higher rain than normal, say 800 mm, your futures position settles at a gain, and offsets the costs you are bearing. If the month turns out to be drier than expected, with rainfall at 500 mm, your futures position settles at a loss.

Let’s say the contract is priced at 700 mm, meaning the market expects 700 mm of July rain. Each millimetre of rainfall above or below this entry price is worth a fixed rupee amount: say Rs 500 per mm per lot. And you buy one lot at 700 mm. If the actual rainfall is 820 mm, then your profit is (820-700) x 500 = Rs 50,000. If the monsoon is 500 mm, then your loss is (500-700) x 500 = Rs 1,00,000. But this may be offset by the fact that your workers were able to pull off the 25 days of work, and your revenues are on track. You may think that it’s a price worth paying for the hedge.

Who is selling this futures contract? The NCDEX contract proposes a designated market maker (DMM): a professional trading member who commits to being present in the market continuously, posting prices at which they will both buy and sell. This is a serious operational commitment. In exchange, the DMM receives an incentive that changes depending on their presence. Over time, there may be traders on both sides of the market.

Derivatives and climate change

The idea of derivatives to deal with weather-related risks started around 1999. The Chicago Mercantile Exchange listed the first Heating Degree Day futures in September that year. The derivative essentially prices how cold a winter will be, measured by how many degrees each day’s temperature falls below 18 degrees Celsius, the point at which people start turning on their heaters. If it is a warm winter, people won’t turn on their heaters, and the gas utility would lose revenues.

Cooling Degree Day contracts, which measure how many degrees each day’s temperature rises above 18 degrees Celsius, followed in January 2000. While these were initially tools for gas utilities and energy traders, they gradually came to be used by businesses from breweries to construction companies. Temperature gave way to rainfall, wind speed, frost days, and snowfall.

Outstanding weather derivatives are estimated at $25 billion. However, the vast majority of these are bilateral contracts between banks, energy traders, insurers, and corporates, away from any exchange, without transparent pricing or centralised clearing. India has enormous potential to become a sophisticated user of weather derivatives, given its agricultural dependence, its growing urban economy, and its acute climate vulnerability.

What will it take to make this work?

First, more details are needed on the contract’s tick size, lot size, and the precise index formula. But this is most likely to be addressed shortly.

Second, the issue of measurement must be resolved. The contract rests on all parties to the transaction agreeing on how much rainfall there was in a month. One may rely on the IMD, but if it is slow to publish or unavailable at relevant geographies, the contract could get into trouble. If another weather station provides a different estimate, disputes may arise. Hence, the exact data source, the measurement methodology, the backup in case of data failure, and the dispute resolution mechanism if participants challenge the settlement value need to be discussed ex-ante. Uncertainty about the contract’s data source when the market is trying to attract its first participants has the potential to damage its development.

Third, the market can take off only if there are both sides to a transaction. Someone has to benefit from low and heavy rainfall to trade with each other. While the existence of the market maker solves this to an extent, it will not work if liquidity does not develop.

Most derivatives serve a narrow constituency—a nickel futures matters to metal traders, a crude oil futures to refiners and energy companies. But occasionally, a product emerges that is truly macro, whose movements ripple across the entire economy. For India, and perhaps only for India, the monsoon has that quality. It moves agriculture, power, inflation, rural incomes, and government finances all at once. If RAINMUMBAI ever matures into a deep and liquid market, it would be one of India’s most consequential financial instruments.

Want to save Alphonso mango from heatwave? Start with open data

The Maharashtra government must fund activities that can develop, certify, and rapidly multiply climate-resilient mango cultivars, along with other agricultural products.

28 April, 2026
The Pint

We may look forward to the mango season with delight and anticipation. Yet, the mood is sombre among Alphonso farmers. A recent report suggests that Alphonso production in Sindhudurg is down 85-90 per cent this season. Production is down in Ratnagiri by roughly 70 per cent, and in Raigad, by 60 per cent.

The farmers are haggling with the Maharashtra government over compensation amounts, and may reach a compromise at some point. But the Alphonso crisis represents the proverbial canary in the climate-change coal mine, with estimates suggesting that climate change could shave 3-10 per cent off GDP by the end of the century. This requires a serious policy response on climate adaptation.

The climate contract

Each cultivar—a plant variety bred to hold on to specific traits each time it is grown—has a climate contract. It demands certain conditions to flourish. The Alphonso mango needs 300 hours of direct sunlight in October to trigger flowering, colder conditions for flowering and fruiting, and subtropical or tropical climates, with optimal temperatures between 24 and 30 degrees Celsius, for the fruits to mature. Every farming year has fluctuations: a hot February, a late monsoon, or a stray hailstorm. The relevant question is whether the current changes are just fluctuations around a stable mean, or whether the underlying process itself has shifted. The evidence is increasingly suggesting the latter.

First, Konkan summer temperatures have shifted upward to 33 degrees Celsius in February and March. The monsoon has become more erratic and delayed, and arrives in sudden bursts instead of the steady drizzle. An increase in sea temperatures has led to cyclones, which are now rapidly intensifying in a historically calm region. Storms such as Tauktae and Biparjoy used to be once-in-a-generation events. They are now becoming the new normal, arriving at exactly the moment when the Alphonso is most vulnerable. The plant cultivar is now facing a climate it has not evolved for.

While our focus today may be the Alphonso, the climate contract is being rewritten across the Indian landscape: wheat in Punjab, coffee in Coorg, apples in Himachal, and paddy in the deltas. Each of these confronts a serious threat to its viability under status-quo farming techniques, even as the changing climate opens possibilities yet to be explored.

Public policy in climate adaptation

What has the climate contract got to do with economics and public policy, you might ask. Once you accept that the underlying process has changed, the policy response has to fundamentally change, too. Traditionally, India has resorted to a policy of compensation, either directly through fiscal transfers or through crop-insurance type products that make payments after a pre-specified event. But both of these break down if the change is structural instead of a mere fluctuation. If we keep following the same practices under different climatic conditions, we will keep debating compensation amounts every year. In the new normal, compensation does not make for a sustainable strategy. We need a shift in the way we have been organising our production, infrastructure, and consumption. This is the central objective of climate adaptation.

One could argue that farmers (or other private sector companies) are incentivised to figure this out themselves and plant cultivars that are more resistant to climate change. Markets have solved parts of this problem before. The private sector can develop new plant varieties or hybrid seeds and earn money from them. Farmers’ cooperatives can fund things together. Policy merely needs to ensure that the incentives for individuals and firms to innovate remain clear.

But there are some parts of the job the market is unlikely to take on. For example, evaluating which cultivar to switch to requires knowledge of what the climate will look like in a specific village. This, in turn, requires field trials to run consistently across agroclimatic zones for several years and databases that record the flowering of plants against weather logs, among other things. The state has a role to play in funding activities that can develop, certify, and rapidly multiply climate-resilient mango cultivars, along with other agricultural products.

Finally, climate-resistant farming depends on open data. Figuring out which mango trees survive a heatwave needs a lot of information. Every reading from a weather station, result from a farm experiment, and soil test from a village needs to be recorded. Currently, a lot of this data either doesn’t exist, sits locked away in some government office, or is recorded in formats that don’t talk to each other. The data must be collected properly, stored in a standard format, and made free for anyone to use, from scientists trying to breed a tougher crop to officers advising farmers to agriculture startups building apps. Any serious plan to adapt to climate change has to start by treating farm and weather data the same way we treat roads, electricity, or the internet: as essential infrastructure the nation depends on.

The plight of farmers in Konkan is not national news. But it is a warning for Indian agriculture under a changing climate. Adapting to climate change requires measures such as seed libraries, soil databases, and 20-year farm experiments. The longer we mistake compensation for adaptation, the more harvests will fail, because the climate they were built for is fast changing.

RBI is going out of its way to compensate fraud victims. It doesn’t have the mandate

The RBI may consider evaluating the structural reasons why banks do not invest in fraud protection.

14 April, 2026
The Print (with Pratik Datta)

Most of us in India have now become accustomed to authorised push payment (APP) frauds—such as phishing emails, or threats of digital arrests—where customers are tricked into making the transfer themselves. Reports suggest that there were around 28 lakh cyber frauds in 2025, amounting to Rs 22,931 crore.

On 6 March 2026, the Reserve Bank of India released a proposal under which victims of such frauds, involving gross loss up to Rs 50,000, could receive partial compensation—85 per cent of the net loss or Rs 25,000, whichever is lower. The mechanism, however, is available only once in a customer’s lifetime. Most strikingly, the RBI itself would bear 65 per cent of the compensation cost, with the remainder split between the sending and receiving banks.

While one can understand the policy instinct of bringing such transactions into a compensation net, there are serious concerns about its design.

Difficulties in the proposal

First, there’s a practical problem of verifying whether the transaction was indeed fraudulent. The burden of proof for customer eligibility lies with the bank, but this requires that banks have the data, the systems, and the incentive to check. When 65 per cent of the cost is borne by the RBI—at least once in the customer’s lifetime—the bank will have limited incentive to conduct rigorous due diligence.

More troubling is the moral hazard. The draft covers cases where customers shared credentials, downloaded malicious software, or were “tricked into willingly sending money”. Consider a scenario where two parties collude: one transfers money to the other, then claims it was fraud. The transferred funds are returned; the RBI still compensates the claimant. The National Cyber Crime Reporting Portal (NCCRP) has already received approximately 28 lakh complaints in 2025. Adding a financial incentive to such complaints will only add to the number.

Additionally, how will the RBI know that it’s a “once in a lifetime” claim for an individual? A customer who has already claimed compensation under this scheme could, without a robust tracking mechanism, attempt to claim again through a different bank account or after a KYC update. Alternatively, either the bank, the RBI, or the NCCRP will have to set up additional systems to verify the once-in-a-lifetime status. There is no guarantee that a bona fide customer, once defrauded, will not face the situation ever again. What then happens to the compensation of such a victim?

The deeper question that the RBI must confront is whether this is really the mandate of a central bank? The RBI’s mandate is inflation targeting and financial stability, not consumer insurance. When the RBI steps in as a direct compensation source, it conflates two entirely separate functions: systemic oversight and retail-loss socialisation. These should be kept apart.

The RBI’s own sunset clause acknowledges the awkwardness: it states that compensation will be reviewed after one year to ‘reduce or eliminate’ the RBI’s share. If the design intention is ultimately to remove the RBI from this equation, why put it there in the first place?

International experience

A comparison with international frameworks is instructive. It is in contrast to the RBI’s proposal.

The United Kingdom addressed APP fraud through the Financial Services and Markets Act 2023, which empowered the Payment Systems Regulator to require payment service providers to reimburse customers. The UK model mandates full reimbursement — up to £85,000 per claim — with the cost split 50:50 between the sending and receiving payment service provider.

There is no role for the Bank of England in absorbing any portion of the cost. Payment Service Providers (PSPs) can refuse reimbursement only on two grounds: proven customer fraud or gross negligence, and the burden of proof rests with the PSP. There is no lifetime claim limit; a genuine victim can claim again. In this set-up, those who control the payment infrastructure bear the cost of its failures.

The policy thus incentivises the payments industry to invest further in end-to-end fraud prevention. Brazil, which operates PIX, an instant payment system created by the central bank, requires financial institutions to implement mandatory fraud-screening mechanisms and impose strict timelines for complaint resolution and fund recovery. Critically, the cost of fraud falls on the institutions, not the regulator.

This proposal should not be implemented

The problem of digital fraud is significant and deserves our attention.

But the current proposal is open to abuse, and places the burden of liability exactly in the wrong direction: the RBI bears most of the cost, while banks—who are best placed to prevent fraud at the network level—bear the least.

The central bank neither has the mandate nor the institutional capacity to run a consumer compensation mechanism. The RBI may also want to consider evaluating the structural reasons why banks do not invest in fraud protection.

In today’s policy environment—with zero Merchant Discount Rate (MDR) and National Payments Corporation of India’s (NPCI) centralised control over UPI product design—banks have little incentive for building better fraud detection. Because they don’t earn from UPI transactions, they can’t differentiate the product. The result is a classic underinvestment problem that compensation by the RBI cannot fix.

Why shielding consumers from rising fuel prices can backfire

IOC, BPCL, and HPCL have lost about Rs 20,000 crore due to the fuel price freeze. These losses will accumulate on balance sheets, raise borrowing costs, and circle back to the govt as contingent liabilities.

31 March, 2026
The Print

Brent crude has surged toward $120 a barrel since the US-Israeli strikes on Iran began, with analysts warning of the price reaching $150 or more if the conflict persists. Natural gas prices in Asia and Europe have risen 54 per cent and 63 per cent, respectively, in the week following the opening strikes. Jet fuel has surged $200 per barrel, diesel almost $180 per barrel.

When supply falls sharply and demand does not, a rise in prices is the obvious response in a market economy. This was Europe’s experience in 2022 — it let prices rise, taxed firms that profited, and undertook some redistribution. In India, petrol and diesel prices have barely moved.

The government has held the line absorbing the difference through oil marketing companies and implicit fiscal transfers. This begs the question: is shielding consumers from price signals actually protecting them, or is it simply deferring the cost, distorting the market, and ultimately leaving them worse off?

When a supply shock hits

It is worth beginning with first principles. When a supply shock hits, and less of the commodity is available, consumers need to reduce their consumption, producers need to find ways to bring more of the scarce good to market. These millions of individual decisions get coordinated through the price.

Consider a simple example: When onion prices spike, you do not need a government advisory telling you to use fewer onions. You substitute, and reserve onions for the dishes where nothing else will do. A trader somewhere calculates that the higher domestic price now makes importing viable. Supply rises, demand compresses, and the market finds a new equilibrium. This takes time, and there is hardship and chaos in the short run. But this actually leads to coordination of millions of independent decisions, each responding to the price, which produces an outcome that no allocation committee could have implemented.

When oil prices rise, this is exactly the mechanism that would play out. On the demand side, it will lead to adjustments that preserve supply. For example, households may undertake lesser travel, industry may switch fuels, and make efficiency investments. On the supply side, every alternative starts to look more viable, drawing in investments and innovation, which had earlier seemed too costly.

The arguments against price rises

If the case for allowing prices to rise is this straightforward, why does the Indian state reflexively reach for the price cap? Two arguments are typically made. Let us consider each.

The first argument runs as follows: the poor spend a disproportionate share of their income on energy, and allowing prices to rise unchecked is effectively taxing those least able to pay. However, when governments suppress fuel prices, the poor do not benefit disproportionately. Fuel subsidies in practice flow overwhelmingly to the middle class and the wealthy, who own more vehicles, consume more diesel, and run larger businesses. A flat price cap is a subsidy to everyone, but a larger subsidy in absolute terms is to the affluent. Further, since the supply shock remains, scarcity manifests itself in long queues, in rationed allocations, and in the black market price that the poor, with no connections to help jump the queue, ultimately end up paying.

The second argument places the blame for rising prices on speculators. It suggests that prices are not rising because oil is genuinely scarcer, but because speculators are hoarding the oil, or trading on futures markets, and artificially inflating them. However, a speculator who bets on rising prices and is correct is actually providing early information that allows consumers and businesses to adjust sooner. Capping prices to punish speculators destroys this information, leaving the market blind, precisely when it most needs to see. Suppose the argument is physical hoarding.

But hoarding is profitable up to a point. Storage costs money, oil degrades, and the hoarder’s entire bet depends on selling before prices reverse. So if prices were to rise, they would actually discipline the hoarder. Capped prices not only eliminate the profit opportunity that would induce the release of stocks, but also the signal that would have drawn in competing supply.

Impact on oil firms

If international prices have risen, and retail prices are not reflecting that increase, who is bearing the brunt? The major cost is being borne by India’s state-owned oil marketing companies, with their marketing margins turning negative owing to the rise in international prices. Reports suggest that IOC, BPCL, and HPCL have lost about $2.25 billion (about Rs 20,000 crore) due to the fuel price freeze. These losses will accumulate on balance sheets, raise borrowing costs, and ultimately circle back to the government as contingent liabilities. The government recently slashed the Special Additional Excise Duty (SAED) on petrol and diesel by Rs 10 per litre each, with the intention of keeping the retail price in check. This gives some relief to the oil companies, but takes away the government’s spending kitty, which will probably have to be made up by increasing other taxes.

A supply shock, not of our making, is upon us. When a supply of say 100 units goes down to 60 units, there is always the question of who gets the supply? The choice is whether this allocation happens through prices, which distribute the burden across millions of decisions simultaneously, or through the state, which leads to fiscal stress, balance sheet deterioration, and eventual crisis. The gains to GDP are greater with adjustments through the price system.

Now is India’s chance to reform its electricity system—utilise the energy crisis

India’s states have vastly different electricity needs. Tamil Nadu has high wind penetration and Rajasthan has abundant solar irradiance. A one-size-fits-all procurement template cannot work.

17 March, 2026
The Print

The US-Israel strikes on Iran have triggered a serious energy crisis for India, which imports more than 85 per cent of its crude oil, and about 50 per cent of its natural gas. Brent crude has surged past $100 a barrel, and the Strait of Hormuz — through which over half of India’s crude imports and most of its LPG transit — is effectively closed to commercial shipping. The government has rationed gas supplies to hotels and restaurants.

While we would have preferred to avoid this crisis, policymakers should use this opportunity to initiate systemic reforms to accelerate India’s energy transition. Getting there requires five reforms in India’s electricity system.

Free the price system

India has a long history of controlling energy prices. Petrol and diesel prices have been frozen for extended periods whenever global crude prices rise, as they have right now. The instinct is to shield consumers from price shocks.

Similarly, India’s electricity sector is riddled with price distortions. Agriculture and domestic consumers are heavily subsidised, while commercial and industrial (C&I) users pay inflated tariffs. Costs do not disappear because the government chooses not to pass them on. They show up in the balance sheets of oil companies, ballooning discom losses, deferred infrastructure investment, low innovation, and fiscal deficits—ultimately financed by the very consumers the freeze (or the subsidy) was meant to protect.

More importantly, in the long term, real-time, cost-reflective tariffs are essential for a renewables-heavy grid. When the sun is shining, there is abundant solar power and electricity is cheap to produce. In the evening, when solar generation fades and demand peaks, expensive coal plants kick in and the cost of supply jumps. If prices reflected this variation in real time, demand would adjust.

For example, factories would shift energy-intensive processes to cheaper solar hours, EVs would be charged during the day, and households could shift several chores to daytime. Demand-side adjustments can help make the transition to renewables cheaper and faster. We have almost none of these today.

Free power purchase agreements from price rigidity

When a company builds a solar or wind farm, it needs a buyer for the electricity it will produce. In India, this is overwhelmingly a state-owned distribution company — the entity that delivers power to your home and factory. The two sides sign a power purchase agreement, or PPA: a long-term contract, often lasting 25 years, in which the buyer commits to purchasing electricity at a fixed price determined through an auction.

But this creates a problem. Technology costs and other inputs, interest rates, and grid conditions change. A price locked in in 2025 may look absurd by 2030. Yet, the distribution company is stuck buying at a price that may be far above what the market offers if costs fall.

These contracts need to be more flexible—allowing prices to adjust periodically to reflect market conditions, indexing them to costs that actually change, and giving both parties room to respond to a world that will look very different in a decade.

Free contracting from the one-size-fits-all template

When a state government wants to buy renewable energy for its people, it does not have the freedom to design an auction that suits its needs. The Union government prescribes standard bidding guidelines that all states must follow — specifying how auctions are conducted, how tariffs are structured, and what contractual terms are permissible.

Deviations from these guidelines must clear the hurdle of regulatory approval, which takes time and carries costs. But India’s states have vastly different electricity needs. Tamil Nadu has high wind penetration and an ageing thermal fleet; Rajasthan has abundant solar irradiance and cheap land. A one-size-fits-all procurement template cannot accommodate these differences. States should have the freedom to innovate in how they buy power.

Free buyers and sellers to trade with each other

Under current law, anyone who wants to buy and sell electricity needs a trading licence from the government. This rule was written two decades ago, when electricity trading meant large deals between state utilities — not the kind of small, flexible transactions that renewable energy makes possible today.

Imagine a factory with rooftop solar panels that generates more power than it needs at midday. It should be able to sell its excess generation to a trader who aggregates such surpluses and sells them to a neighbouring IT campus. Or a housing colony should be able to buy solar power from a generator and supply it to households within the colony.

A regulatory framework that allows small buyers and sellers—as well as intermediaries who facilitate such transactions—to transact directly, without needing a trading licence, would unlock entirely new markets for clean energy. More buyers and sellers would mean better price discovery, which in turn would signal investors where to build the next solar farm or battery storage facility.

Free the market for storage

Solar and wind are intermittent sources of energy— they generate when the sun shines and the wind blows, not necessarily when demand peaks. For renewables to provide reliable, round-the-clock power, large-scale energy storage is essential.

India’s current policy approach to storage is to bundle it with generation through firm and dispatchable renewable energy (FDRE) contracts, where a single developer must build both the renewable generation plant and the storage facility, and guarantee delivery at specified hours. This forces a vertically integrated model on what should be a competitive, unbundled market.

A far better approach would be to let storage emerge as an independent business. Standalone storage operators should be free to buy cheap solar power during the day — when prices should fall to near zero — store it, and sell it during evening and night hours when demand peaks and prices are high. This arbitrage is the natural business model for storage. It requires no subsidy, only a functioning price system, and would also be helped by removing the requirement for a trading license. The price spread between solar hours and peak hours is the revenue model.

Unbundling storage from generation, and allowing storage-only players to trade freely on energy exchanges would unlock private investment in batteries, pumped hydro, and other storage technologies far more effectively than any government mandate.

When Russia cut off gas supplies to Europe, there was a painful price surge. On the demand side, households and factories cut consumption, switched fuels, and invested in insulation and efficiency. On the supply side, LNG terminals were fast-tracked, renewable installations accelerated, and alternative suppliers rushed to fill the gap. Within 18 months, European gas prices had fallen back.

The price system was brutal in the short run but self-correcting — precisely because no government tried to freeze it. India should use the current crisis to extend the freedom of price movement to the energy sector. This should, in turn, be followed by the freedom to contract flexibly, the freedom to trade power across buyers and sellers, the freedom to build storage as a business, and the freedom for states to design their own path.

Why RBI’s draft rules aren’t enough to curb mis-selling of financial products

For too long, sales misconduct has been treated as an operational issue created by overzealous relationship managers. The elevation of the issue to the board level signifies that mis-selling is a governance failure.

03 March, 2026
The Print

Most of us have likely experienced a bank relationship manager encouraging us to buy insurance policies, mutual funds, and other products that we did not need, and definitely did not understand. The RBI has finally issued draft directions to curb the mis-selling of financial products. This is a welcome step, which was long over-due. The process of reform tells us two things — first that reform takes a long time, and is shaped by research, advocacy, and engaging with the government. Second, the process has just begun, draft directions have to become final, provide more clarity on enforcement, and then have to actually get implemented.

Until recently, while the RBI acknowledged mis-selling by bank staff, it considered it to be someone else’s problem. This has fundamentally changed. The draft directions under the Responsible Business Conduct framework, applicable to commercial banks, NBFCs, regional rural banks, cooperative banks, and all-India financial institutions, define mis-selling as follows, “…if it sells something unsuitable for the customer’s profile, provides misleading or incomplete information, completes a sale without explicit consent, or bundles additional products with a requested service.” This brings about some notable changes.

First, there is now a definition of what constitutes mis-selling. Products have to be “suitable” for the customer’s profile. For example, banks should now have to think twice before selling a life insurance policy to an 80–year–old person. Second, compulsory bundling — the purchase of one product made conditional on the purchase of another — is now prohibited. For example, several banks were making a loan conditional on buying an insurance policy. This will now not be allowed. Third, misleading practices such as “dark patterns”, “trick wording”, and “subscription traps” are also prohibited. Banks must now carry out suitability assessments before selling a product and must seek customer feedback within 30 days of a sale. Finally, the framework introduces post–sale safeguards. Besides seeking feedback, banks must also put in place structured monitoring and reporting systems. If mis-selling is established, the bank must refund the full amount and compensate the customer.

Importantly, the draft places primary responsibility for designing, approving, and overseeing compliance with these requirements squarely on the boards of regulated entities. Policies on suitability, sales practices, incentives, grievance redress, and monitoring must be board-approved, and boards are expected to exercise ongoing oversight.

The theory of change: data, research, and advocacy

How did we get here? This journey has involved three elements: data and research to establish the scale of the problem, advocacy to build a narrative for reform, and government engagement to translate evidence into policy.

The research trail goes back over a decade. In 2014, a research paper estimated that Indian policyholders lost approximately $28 billion between 2004 and 2011 on account of mis-sold life insurance products. The number put a rupee value on a problem that most people experienced anecdotally. A mystery shopping study of bank branches in Delhi, where auditors posed as customers seeking tax-saving instruments, found that private sector banks overwhelmingly recommended the high–commission product, typically an insurance policy, while public sector banks pushed fixed deposits to meet their own mobilisation targets. Banks rarely made voluntary disclosures on product features, costs, or risks. In 30 per cent of the cases, market-linked insurance products were falsely presented as carrying guaranteed returns. Research has also shown that agents systematically recommended products that earned them the highest commissions rather than those that best served the customer. Running alongside the research was sustained advocacy by journalists and commentators.

This body of evidence fed into government engagement. In November 2014, the Ministry of Finance constituted the Sumit Bose Committee to recommend measures for curbing mis-selling and rationalising distribution incentives in financial products. The Committee’s report, released in September 2015, identified the core problem: financial products were regulated by multiple regulators who did not coordinate strategies, the sales channel faced different incentive structures for identical products, disclosures were opaque, returns were not comparable, and costs were hidden. The Committee recommended, among other things, ending the practice of front-loaded commissions that created perverse incentives to push high–cost products. Finally, the RBI’s Report on Trend and Progress of Banking in India 2024-25 stated that mis-selling has significant consequences for customers and the financial sector, and that it would issue comprehensive instructions to curb such mis-selling.

Why this is not enough, and what must happen next

It is unquestionably a positive development that the ultimate responsibility for preventing mis-selling has been placed on bank boards. For too long, sales misconduct has been treated as an operational issue created by overzealous relationship managers, or poorly trained agents. The elevation of the issue to the board level signifies that mis-selling is a governance failure.

Placing the entire responsibility on boards has trade-offs. On the one hand, as Monika Halan has observed, this might mean that suitability and other requirements remain as boxes to be checked. Along similar lines, others have argued that the effectiveness of these reforms depends on defining key concepts such as “suitability” and creating robust consumer-feedback mechanisms.

On the other hand, if the RBI were to turn every aspect of customer protection into law with exacting standards, there would be little room for banks to interpret requirements differently. A highly prescriptive legislation can constrain flexibility. The next piece of the puzzle, therefore, is the question of incentives and enforcement. Unless bad behaviour is costly, firms will not redesign their incentive structures, and this may leave us exactly where we were before the directions.

This is where the role of data and research becomes even more important going forward. We need continuous and rigorous monitoring of whether the new rules are actually changing behaviour on the ground. We also need data on outcomes: are customers being sold more suitable products? Have refunds and compensation claims risen? Are banks restructuring their internal incentive frameworks? Without this evidence, we will not know whether the directions are working.

The journey from research to regulation is long and uncertain. We are at a point where the central bank has acknowledged the problem and proposed a framework. The next step is to ensure that the framework is robust, that it is enforced, and that we continue to generate the data and research that will keep the pressure for reform alive.

New CPI basket shows that India’s expenditure pattern has changed

The changes ensure that payments such as dearness allowance or pensions, that are linked to the CPI, will be more closely based on the true consumption baskets of households.

17 February, 2026
The Print

The government recently announced a revised Consumer Price Index basket. Inflation is the percentage change of the Consumer Price Index over time. Inflation statistics determine how we interpret growth, assess macro stability, and protect real incomes.

The Consumer Price Index (CPI) is the nominal anchor of macroeconomic policy. This makes the new basket an important development, one with implications for everything built around the CPI, such as monetary policy, pension indexation, and fiscal arithmetic. The benefits of this revision will be fully realised when the authorities publish a properly backdated series so that the new CPI can be compared with earlier data.

What has changed?

The basis for measuring inflation is the cost of a “basket” of goods and services that a typical household consumes (food, rent, mobile phone, laptop, fuel, transport, health, education, etc). The expenditure on these items is measured through a household survey. Each item is given a weight based on how much people spend on it. The base year is one which reflects the year of the survey. Once the basket is fixed, one can measure how much the basket costs every quarter, or every year, to know how much more expensive (or not) the same goods and services are.

It should be no surprise that the “basket” of a typical household changes. Twenty years ago, smartphones were perhaps not as common, and ten years from now, subscriptions to the latest AI models will be ubiquitous. A basket based on older consumption data would overweight items that matter less today and underweight items that now take up a larger share of household budgets. This means that we need a change not only in the items in the basket, but also the weight of each item.

For example, as a household grows richer, the share of expenditure on food declines, as the household is now spending on other goods— education, healthcare, digital goods, etc. A good statistical system, therefore, has to continuously update the consumption basket to ensure that it correctly represents what households consume.

The new CPI basket reflects these changes. For example, in the new basket, the weight of food has declined modestly, while items such as healthcare, education, transport, communication, and recreation have gained weight. There have also been methodological improvements in price collection, including greater use of digital systems and updated sampling strategies.

These are welcome changes. They ensure that when the RBI targets CPI inflation, it will be targeting the lived consumption experience of households. The changes also ensure that payments such as dearness allowance or pensions, that are linked to the CPI, will be more closely based on the true consumption baskets of households.

The importance of comparability

Updating the consumption basket is an important step. But it does create another problem—how do we compare inflation across time? If the basket of yesterday is different from the basket of today, the change in its price does not convey much information. Comparing the price of the “same” basket over time is fundamental to economic reasoning. A new basket may help us measure inflation for a few periods from now, but it doesn’t tell us how today compares to yesterday. And given that baskets will have to be over time, how does one ensure continuity?

As of now, the ministry has given us a linking factor used to connect India’s old CPI series (base 2012=100) to the new CPI series (base 2024=100). The linking factor scales the old CPI series so that it aligns with the new one at the point of overlap. With this, one can rescale the old series to understand what it would have looked like, had we used the new consumption basket. But providing a single linking factor has some disadvantages.

It assumes that the relationship between the old and new series in that year is representative of earlier years, which may not always be true. If the previous year was an abnormal year, then a one-year linking may not be representative of previous years. Further, since the weights of the components have changed (as food now has a smaller weight in the basket), a single linking factor cannot account for the changing influence of different groups on inflation trends.

There are ways to solve for this. For example, one could publish both series for a number of years. One could rebuild the old series entirely, possibly for a decade, instead of just scaling it. In doing so, it will be in line with best practices in other jurisdictions. For example, in the UK, the Office for National Statistics (ONS) updates the CPI basket frequently and revises weights using detailed expenditure data. It publishes continuous historical series and detailed methodological notes that convey how historical comparability is preserved.

The Australian Bureau of Statistics (ABS) has moved toward more frequent reweighting, increasingly using national accounts data to ensure that the CPI reflects current spending patterns. The ABS maintains historical series and links them carefully, with adequate explanations on the impact of revisions. The Ministry of Finance should institutionalise a system to revise more frequently in smaller steps so that large discontinuities can be avoided.

The new CPI basket is a step in the right direction. It recognises that India of today is not the India of a decade ago. While we update the series, preserving continuity and comparability is equally important.