Why PayTM is winning the payments “battle” in India

For the last one year or so, ever since I started using IMPS at scale, and read up the UPI protocol, I’ve been bullish about Indian banks winning the so-called “payments battle”. If and when the adoption of electronic payments in India takes off, I’ve been expecting banks to cash in ahead of the “prepaid payments instruments” operators.

The events of the last one week, however, have made me revise this prediction. While the disruption of the cash economy by withdrawal of 85% of all notes in circulation has no doubt given a major boost to the electronic payments industry, only some are in a position to do anything about this.

The major problem for banks in the last one week has been that they’ve been tasked with the unenviable task of exchanging the now invalid currency, taking deposits and issuing new currency. With stringent know-your-customer (KYC) norms, the process hasn’t been an easy one, and banks have been working overtime (along with customers working overtime standing in line) to make sure hard currency is in the market again.

While by all accounts banks have been undertaking this task rather well, the problem has been that they’ve had little bandwidth to do anything else. This was a wonderful opportunity for banks, for example, to acquire small merchants to accept payments using UPI. It was an opportune time to push the adoption of credit card payment terminals to merchants who so far didn’t possess them. Banks could’ve also used the opportunity to open savings accounts for the hitherto unbanked, so they had a place to park their cash.

As it stands, the demands of cash management have been so overwhelming that the above are literally last priorities for the bank. Leave alone expand their networks, banks are even unable to service the existing point of sale machines on their network, as one distraught shopkeeper mentioned to me on Saturday.

This is where the opportunity for the likes of PayTM lies. Freed of the responsibilities of branch banking and currency exchange, they’ve been far better placed to acquire customers and merchants and improve their volume of sales. Of course, their big problem is that they’re not interoperable – I can’t pay using Mobikwik wallet to a merchant who can accept using PayTM. Nevertheless, they’ve had the sales and operational bandwidth to press on with their network expansion, and by the time the banks can get back to focussing on this, it might be too late.

And among the Prepaid Payment Instrument (PPI) operators again, PayTM is better poised to exploit the opportunity than its peers, mainly thanks to recall. Thanks to the Uber deal, they have a foothold in the premium market unlike the likes of Freecharge which are only in the low-end mobile recharge market. And PayTM has also had cash to burn to create recall – with deals such as sponsorship of Indian cricket matches.

It’s no surprise that soon after the announcement of withdrawal of large currency was made, PayTM took out full page ads in all major newspapers. They correctly guessed that this was an opportunity they could not afford to miss.

PS: PayTM has a payments bank license, so once they start those operations, they’ll become interoperable with the banking system, with IMPS and UPI and all that.

Moving towards a cashless economy

In any transaction, the process of payment is a pain. It is a necessary step, of course, in that payment is what completes the transaction, but the process of payment is not something that adds any value to the transaction. If money could be magically be transferred from buyer to seller at the end of a transaction, both transacting parties would be happy.

In this context, any chosen method of payment, be it cash or credit card or cheque or bank transfer, involves some degree of pain for the transacting parties.

In case of cash, there’s the problem of counting out the money, cross checking it, finding exact change, being able to handle currency without the fear of being robbed, and making sure the currency is not counterfeit. Cheques have a credit risk, since they can bounce, not to speak of the time it takes to write one, and the time it takes for the money to get transferred.

Bank transfer requires parties to have bank accounts, and the ability of transacting parties to tell each other their account details. Credit cards have the most explicit pain of transaction – the transaction fees the merchants need to pay the acquiring bank – apart from the time and pain of swiping, entering the PIN, etc.

The reason India has so far been a primarily cash economy is that the pain of transacting through cash has been far lower than the pain through other means. Apart from the pains mentioned above, cash also has the advantage of anonymity, speed of transaction and ability to hide from the tax authorities.

So if we have to turn India closer to a cashless economy, as the current union government plans to do, we need to either increase the pain of transacting in cash, or reduce the pain of transacting through another means. The Unified Payments Interface (UPI), which was launched with much fanfare earlier this year but has spectacularly failed to take off, seeks to reduce pain of cashless transactions. The government’s efforts to get people open bank accounts through the Pradhan Mantri Jan Dhan Yojana (PMJDY) also seeks to reduce pain in non-cash transactions.

The government’s recent effort to withdraw legal tender of Rs. 500 and Rs. 1000 notes, on the other hand, seeks to increase the cost of transacting in cash – 85% of the current stock of cash in India needs to get banked in the next 50 days. This, however, is not a repeatable exercise – it can simply remove confidence in the rupee and drive people to alternate (formal or informal) currencies.

So what can be done to move India to a more cashless economy? The problem with small change has already played its part, with most auto rickshaw and taxi drivers in Mumbai supposedly willing to accept payment in digital wallets such as PayTM. If the stock for the new Rs. 2000 and Rs. 500 notes released is low, and most people have to transact using Rs. 100 notes, that will again increase the pain of transacting in cash, since the cost of handling cash might go up.

Perversely, if crime and robberies increase, that will again make people wary of handling cash. In fact, as this excellent piece in the New Yorker claims, the reason Sweden has moved largely cashless is that people got scared of handling cash after a series of cash robberies a few years ago. The cost of higher crime, however, means this is not a desirable way to go cashless.

It’s been barely three days since the new Rs. 500 and Rs. 2000 notes have been released, and there are already reports of counterfeiting in these notes. Given the framework I’ve proposed in this blogpost, it is not inconceivable that these rumours have been planted – when people become more wary of receiving large currency (thanks to the fear of counterfeiting), they want to reduce the use of such physical currency.

It’s perverse, I know, but nothing can be ruled out! As I’ve repeatedly pointed out, increased use of cash has a fiscal cost (in terms of printing and maintaining currency, apart from people not paying taxes), so the government has an incentive to stamp it out.



May a thousand market structures bloom

In my commentary on SEBI’s proposal to change the regulations of Indian securities markets in order to allow new kinds of market structures, I had mentioned that SEBI should simply enable exchanges to apply whatever market structures they wanted to apply, and let market participants sort out, through competition and pricing, what makes most sense for them.

This way, different stock exchanges in India can pick and choose their favoured form of regulation, and the market (and market participants) can decide which form of regulation they prefer. So you might have the Bombay Stock Exchange (BSE) going with order randomisation, while the National Stock Exchange (NSE) might use batch auctions. And individual participants might migrate to the platform of their choice.

Now, Matt Levine, who has been commenting on market structures for a long time now, makes a similar case in his essay on the Chicago Stock Exchange’s newly introduced “speed bump”:

A thousand — or at least a dozen — market structures can bloom, each subtly optimized for a different type of trader. It’s an innovative and competitive market, in which each exchange can figure out what sorts of traders it wants to favor, and then optimize its speed bumps to cater to those traders.

Maybe I should now accuse Levine of “borrowing” my ideas without credit! 😛


Intermediation and the battle for data

The Financial Times reports ($) that thanks to the rise of AliPay and WeChat’s payment system, China’s banks are losing significantly in terms of access to customer data. This is on top of the $20Billion or so they’re losing directly in terms of fees because of these intermediaries.

But when a consumer uses Alipay or WeChat for payment, banks do not receive data on the merchant’s name and location. Instead, the bank record simply shows the recipient as Alipay or WeChat.

The loss of data poses a challenge to Chinese banks at a time when their traditional lending business is under pressure from interest-rate deregulation, rising defaults, and the need to curb loan growth following the credit binge. Big data are seen as vital to lenders’ ability to expand into new business lines.

I had written about this earlier on my blog about how intermediaries such as Swiggy or Grofers, by offering a layer between the restaurant/shop and consumer, now have access to the consumer’s data which earlier resided with the retailer.

What is interesting is that before businesses realised the value of customer data, they had plenty of access to such data and were doing little to leverage and capitalise on it. And now that people are realising the value of data, new intermediaries that are coming in are capturing the data instead.

From this perspective, the Universal Payment Interface (UPI) that launched last week is a key step for Indian banks to hold on to customer data which they could have otherwise lost to payment wallet companies.

Already, some online payments are listed on my credit card statement in the name of the payment gateway rather than in the name of the merchant, denying the credit card issuers data on the customer’s spending patterns. If the UPI can truly take off as a successor to credit cards (rather than wallets), banks can continue to harness customer data.

Aswath Damodaran, Uber’s Valuation and Ratchets

The last time I’d written about Aswath Damodaran’s comments on Uber’s valuation, it was regarding his “fight” with Uber investor Bill Gurley, and whether his valuation was actually newsworthy.

Now, his latest valuation of Uber, which he concludes is worth about USD 28 Billion, has once again caught the attention of mainstream media, with Mint writing an editorial about it (Disclosure: I write regularly for Mint).

I continue to maintain that Damodaran’s latest valuation is also an academic exercise, and the first rule of valuation is that “valuation is always wrong”, and that we should ignore it.

However, in the context of my recent piece on investor protection clauses in venture investments (mainly ratchets), it is useful to look at Damodaran’s valuation of Uber, and how it compares to Uber’s valuation if we were to account for investor protection clauses.

“True value” of Indian unicorns after accounting for investor protection. Source: Mint

When Uber raised $3.5 Billion from Saudi Arabia’s Public Investment Fund earlier this year, the headline valuation number was $62.5 Billion. Given the late stage of investment, it is unlikely that the investor would have done so without sufficient downside protection – at the very least, they would want a “full ratchet” (if the next investment happens at a lower valuation, then they get additional shares to compensate for their loss). This is a conservative assumption since late stage (“pre-IPO”) investments usually have clauses more friendly to the investor, usually incorporating a minimum “guaranteed return”.

Plugging these numbers into the model I’ve built (pre-money valuation of $59 Billion and post-money valuation of $62.5 billion), the valuation of the put option written by existing investors in favour of Uber comes to around $1.28 Billion. Accounting for this option, the total value of the company comes out to $39.6 Billion.

Damodaran’s valuation, based on his views, principles and numbers, is $28 Billion. Assuming that investors and management of Uber are aware of the downside protection clauses and its impact on the company’s valuation, Damodaran’s valuation is not that much of a discount on Uber’s true valuation!

Regulating HFT in India

The Securities and Exchange Board of India (SEBI) has set a cat among the HFT (High Frequency Trading) pigeons by proposing seven measures to curb the impact of HFT and improve “real liquidity” in the stock markets.

The big problem with HFT is that algorithms tend to cancel lots of orders – there might be a signal to place an order, and even before the market has digested that order, the order might get cancelled. This results in an illusion of liquidity, while the constant placing and removal of liquidity fucks with the minds of the other algorithms and market participants.

There has been a fair amount of research worldwide, and SEBI seems to have drawn from all of them to propose as many as seven measures – a minimum resting time between HFT orders, matching orders through frequent batch auctions rather than through the order book, introducing random delays (IEX style) for orders, randomising the order queue periodically, capping order-to-trade ratio, creating separate queues for orders from co-located servers (used by HFT algorithms) and review provision of the tick-by-tick data feed.

While the proposal seems sound and well researched (in fact, too well researched, picking up just about any proposal to regulate stock markets), the problem is that there are so many proposals, which are all pairwise mutually incompatible.

As the inimitable Matt Levine commented,

If you run batch auctions and introduce random delays and reshuffle the queue constantly, you are basically replacing your matching engine with a randomizer. You might as well just hold a lottery for who gets which stocks, instead of a market.

My opinion this is that SEBI shouldn’t mandate how each exchange should match its orders. Instead, SEBI should simply enable individual exchanges to regulate the markets in a way they see fit. So in my opinion, it is possible that all the above proposals go through (though I’m personally uncomfortable with some of them such as queue randomisation), but rather than mandating exchanges pick all of them, SEBI simply allows them to use zero or more of them.

This way, different stock exchanges in India can pick and choose their favoured form of regulation, and the market (and market participants) can decide which form of regulation they prefer. So you might have the Bombay Stock Exchange (BSE) going with order randomisation, while the National Stock Exchange (NSE) might use batch auctions. And individual participants might migrate to the platform of their choice.

The problem with this, of course, is that there are only two stock exchanges of note in India, and it is unclear if the depth in the Indian equities market will permit too many more. This might lead to limited competition between bad methods (the worst case scenario), leading to horrible market inefficiencies and the scaremongers’ pet threat of trading shifting to exchanges in Singapore or Dubai actually coming true!

The other problem with different exchanges having different mechanisms is that large institutions and banks might find it difficult to build systems that can trade accurately on all exchanges, and arbitrage opportunities across exchanges might exist for longer than they do now, leading to market inefficiency.

Then again, it’s interesting to see how a “let exchanges do what they want” approach might work. In the United States, there is a new exchange called the Intercontinental Exchange (IEX) that places “speed bumps” over incoming orders, thus reducing the advantage of HFTs. IEX started only recently, after major objections from incumbents who alleged they were making markets less fair.

With IEX having started, however, other exchanges are responding in their own ways to make the markets “fairer” to investors. NASDAQ, which had vehemently opposed IEX’s application, has now filed a proposal to reward orders by investors who wait for at least once second before cancelling them.

Surely, large institutions won’t like it if this proposal goes through, but this gives you a flavour of what competition can do! We’ll have to wait and see what SEBI does now.

Uber’s anchoring problem

The Karnataka transport department has come out with a proposal to regulate cab aggregators such as Uber and Ola. The proposal is hare-brained on most  counts, such as limiting drivers’ working hours, limiting the number of aggregators a driver can attach himself to and having a “digital meter”. The most bizarre regulation, however, states that the regulator will decide the fares and that dynamic pricing will not be permitted.

While these regulations have been proposed “in the interest of the customer” it is unlikely to fly as it will not bring much joy to the customers – apart from increasing the number of auto rickshaws and taxis in the city through the back door. I’m confident the aggregators will find a way to flout these regulations until a time they become more sensible.

Dynamic pricing is an integral aspect of the value that cab aggregators such as Uber or Ola add. By adjusting prices in a dynamic fashion, these aggregators push information to drivers and passengers regarding demand and supply. Passengers can use the surge price, for example, to know what the demand-supply pattern is (I’ve used Uber surge as a proxy to determine what is a fair price to pay for an auto rickshaw, for example).

Drivers get information on the surge pricing pattern, and are encouraged to move to areas of high demand, which will help clear markets more efficiently. Thus, surge pricing is not only a method to match demand and supply, but is also an important measure of information to a cab aggregator’s operations. Doing away with dynamic pricing will thus stem this flow of information, thus reducing the value that these aggregators can add. Hopefully the transport department will see greater sense and permit dynamic pricing (Disclosure: One of my lines of business is in helping companies implement dynamic pricing, so I have a vested interest here. I haven’t advised any cab aggregators though).

That said, Uber has a massive anchoring problem, because dynamic pricing works only in one way. Anchoring is a concept from behavioural economics where people’s expectations of something are defined by something similar they have seen (there is an excellent NED Talk on this topic (by Prithwiraj Mukherjee of IIMB) which I hope to upload in its entirety soon). There are certain associations that are wired in our heads thanks to past information, and these associations bias our view of the world.

A paper by economists at NorthEastern University on Uber’s surge pricing showed that demand for rides is highly elastic to price (a small increase in price leads to a large drop in demand), while the supply of rides (on behalf of drivers) is less elastic, which makes determination of the surge price hard. Based on anecdotal information (friends, family and self), elasticity of demand for Uber in India is likely to be much higher.

Uber’s anchoring problem stems from the fact that the “base prices” (prices when there is no surge) is anchored in people’s minds. Uber’s big break in India happened in late 2014 when they increased their discounts to a level where travelling by Uber became comparable in terms of cost to travelling by auto rickshaw (the then prevalent anchor for local for-hire public transport).

Over the last year, Uber’s base price (which is cheaper than an auto rickshaw fare for rides of a certain length) have become the new anchor in the minds of people, especially Uber regulars. Thus, whenever there is a demand-supply mismatch and there is a surge, comparison to the anchor price means that demand is likely to drop even if the new price is by itself fairly competitive (compared to other options at that point in time).

The way Uber has implemented its dynamic pricing is that it has set the “base price” at one end of the distribution, and moves price in only one direction (upwards). While there are several good reasons for doing this, the problem is that the resultant anchoring can lead to much higher elasticity than desired. Also, Uber’s pricing model (more on this in a book on Liquidity that I’m writing) relies upon a certain minimum proportion of rides taking place at a surge (the “base price” is to ensure minimum utilisation during off-peak hours), and anchoring-driven elasticity can’t do this model too much good.

A possible solution to this would be to keep the base fare marginally higher, and adjust prices both ways – this will mean that during off-peak hours a discount might be offered to maintain liquidity. The problem with this might be that the new higher base fare might be anchored in people’s minds, leading to diminished demand in off-peak hours (when a discount is offered). Another problem might be that drivers might be highly elastic to drop in fares killing the discounted market. Still, it is an idea worth exploring – in my opinion there’s a sweet spot in terms of the maximum possible discount (maybe as low as 10%, but I think it’s strictly greater than zero)  where the elasticities of drivers and passengers are balanced out, maximising overall revenues for the firm.

We are in for interesting days, as long as stupid regulation doesn’t get in the way, that is.