Why a Current Account is Crucial for Businesses

current account

Setting up a current account is one of the most important tasks you simply cannot skip while starting your business. It is very crucial for you to keep your business banking operations separate from your personal banking. 

Having a current account for your business helps you keep track of all your expenditure while simplifying your taxation process.

Before we get started, let’s understand what a current account is.

What is a current account

A current account is opened by businessmen, entrepreneurs, and more, who have to make a large number of transactions regularly. 

Since the volume of transactions, as well as the amount per transaction are generally high, no interest can be availed upon the balance. But, a current account helps with deposits, withdrawals, and contra transactions.

You can open a current account in any commercial bank.

Advantages of having a current account

The whole purpose of a current account is to facilitate entrepreneurs and businessmen to carry out their transactions seamlessly, on a day-to-day basis. 

Here are some advantages you could get by having a current account for your business. 

#1 Current account = any number of transactions 

One of the most important advantages of having a current account for your business is that there is no constraint on the number of transactions. You can transact any number of times at whatever frequency you need to. 

Plus, the upper limit for transactions is so high that you don’t have to worry about money movement at all! This enables your business to have maximum fluidity in terms of operations. 

#2 Keep your personal assets from your business

It is of the utmost importance to keep your personal and business assets disjoined.  It is always recommended you have a current account so you can track your cash inflow easily. This gives you a superior way of planning and managing your budgets. You also get a roundup on your expenditure.

Having a clean financial record allows you to organise your data, which can come in handy for taxes and deductions. Great bookkeeping is always a bonus!

#3 Current account makes your operations easy

Delayed transactions can result in unwanted hiccups. A current account is just what you need to keep your business operations running like a well-oiled machine! 

Your day-to-day transactions are carried out effortlessly and proficiently. Without any delays or jam-ups with your operations, you also get benefits like online banking. The speed of your transactions is usually high, which helps you maintain a good rapport with your vendors and customers!

#4 Current account translates to business legitimacy

Sure, we already talked about the importance of keeping your personal and business assets away from each other. But there is more. As a businessperson, you may write cheques or make online transfers to your vendors, partners, and more. It may seem unprofessional when you make payments from your personal account.

This is not entirely a deal breaker, but having a current account in the name of your business allows your payees to feel affirmed about you having a legitimate business.

#5 Reap extra benefits from your current account

Your current account has all sorts of other benefits that you would typically get from your savings account.  Based on your business, your bank will offer you free Demand Drafts, NEFT and RTGS transactions, Pay Orders, and more, other than the unlimited withdrawals and deposits you can make with your current account. 

Now that we have talked about nearly everything current accounts can help you with, let us break it to you. There is a whole lot more you can get with current accounts.

Introducing RazorpayX Current Accounts

What if we told you that you could get all the benefits we mentioned above, and then some more?  Traditional business banking is not the most efficient way to manage finances. And, several Razorpay merchants told us how suboptimal their business banking experience is.

We conducted a survey among 1500+ CxOs and spoke to 400+ merchants to understand their business banking experience.

  • 64% of companies believe their payment service providers are best equipped to solve their payment challenges as opposed to banks
  • 10x as many companies polled believe payment service providers innovate better than banks
  • 36% of businesses believe manual dependency and reconciliation are the biggest challenges in their current money management

During the survey, another significant problem that stood out was automating money movement. Businesses spend lots of time and money to get their financial operations moving without any trouble. And, with RazorpayX, we aim to put a stop with all problems around money movement.

We built RazorpayX Current Accounts to help you kickstart your journey towards an efficient and seamless business banking experience. The RazorpayX ecosystem provides you with effective end-to-end money movement capabilities, giving you real-time insights on your transactions.

Payouts via Dashboard and APIs

If you already have a current account in a bank, you surely know that API integration takes forever. With RazorpayX Current Accounts, you get APIs by default.

Integration takes very little time and you can start making payouts to your vendors, customers, partners, employees, and more, almost instantly. You can also make or queue your payouts using the RazorpayX Dashboard. 

Approval workflow

Although approval workflows are available with banks, they are quite difficult to set up. And once they are set up, changing them is very difficult since it is long and laborious, involving many documents.

With RazorpayX, approval workflows are very smooth, right from setting them up and changing them. All you have to do is raise a request and our Ops team will get them done in no time. 

Smart insights and reports

RazorpayX converts your financial data into information, and information into insights, so that you have a better overview of your money movement.  

  • View financial summaries of your transactions with customers, vendors, employees, etc.
  • Drill down views of transactions at a contact level and a category level
  • Instantly access/download financial reports and summaries of your contacts
  • Get data on real-time transactions that help you make better business decisions

Apps and integrations

This is one among other things that makes RazorpayX Current Accounts truly stand out from banks. RazorpayX comes with its own set of apps that give you value-added benefits.

Your business banking operations will be much smoother with apps like Vendor Payouts, Payout Links, and Payroll With these integrations in place, your current account will be 10x times more efficient than your average current account.

[ Suggested reading: RazorpayX – How Businesses can Simplify Payouts ]

The verdict

The real difference is how RazorpayX Current accounts comes with its own package of everything you could possibly need for smooth money movement. 

RazorpayX is your one-stop virtual CFO that you need to maintain everything in one place and keep your money moving efficiently.

The Day of the RDS Multi-AZ Failover

On a fateful Friday evening on December 2019, when a few of us were looking forward to packing their bags and going home, we got an alert from the internal monitoring tool that the system has started throwing unusually high numbers of 5xx errors.

The SRE team quickly realized that one of our main applications (called “API”) was not able to connect to its RDS (MySQL) database. By the time we could make any sense of the issue, the application came back up automatically and the alerts stopped.

Looking at the RDS logs, we realized that the master instance has gone through a Multi-AZ failover.

According to the SLA’s provided by AWS, whenever an instance marked as multi-AZ goes through a failure (whether it is a network failure, disk failure, etc); AWS automatically shifts the traffic to its standby running on a separate AZ on the same AWS region. The failover can take up anytime between 60 and 120 seconds, and this was the reason our master instance automatically came back up after around 110 seconds and the application started working without any manual intervention.

Replication failure

The API master instance has a set of 5 replica instances which are used to query different sets of workloads in various applications.

While the application stopped throwing errors and started working, we received another set of alerts stating that the replication on all the replicas had failed.

All the replicas displayed a duplicate-key error message. We immediately shifted all the traffic going to these replica instances to the master instance so that the application does not receive any stale data and display incorrect data to the users.

The drawback of moving all the traffic to the master was that all the heavier selects were also moved to the master, and the CPU load on the master instance increased by 50%. Hence, our immediate move was to recreate all the 5 replicas so that we can move the replica load back as soon as possible.

The new replica creation process internally creates a snapshot from the master instance of the current data and then starts a DB instance from that snapshot. The very first snapshot from a particular machine takes the snapshot of the entire data until now, but the subsequent snapshots are incremental in nature. In the past, we had noticed that these incremental snapshots take around 15-20 minutes for the API database.

While taking the snapshot, we experienced another reality-check. The process was taking more than the usual time that day. After an hour or so, when the snapshot creation was still in progress, we were forced to contact AWS tech support to check why the whole process was taking much longer that day.

The AWS tech-support informed us that since the master instance has gone through a multi-AZ failover, they had replaced the old master with a new machine, which is a routine. Since the snapshot was being taken from the new machine then and was the very first snapshot from the new machine, RDS would take a full snapshot of the data.

So, we had no other option but wait for the snapshots to finish and keep monitoring the master instance in the meantime. We waited six hours for the snapshot to complete and only then were we able to create the replicas and redirect the traffic back to them.

Once the replicas were in place, we assumed that the worst was over, and finally called it a night.

Data loss

Next day, on our follow-up calls with RDS tech support, we were told that it was not a usual occurrence that the replication crashes in scenarios of multi-AZ master failover, and there must be more to the incident than what meets the eye.

This is when we started looking at various reasons on why the replication crashed. After matching the database and the application trace logs for the time around the incident, we found that a few records were present in the trace logs, but not in the database. This is when we realised that we had lost some data at the time of failover.

Being a fintech company, losing transactional data actually meant losing money and the trust of our customers. We began digging the binary logs for that time frame and matching them with the data in the store. We finally figured out that the RDS database had been missing 5 seconds of data. Right after these 5 seconds, we had started receiving 5xx errors on our application logs.

Luckily, we could dig the exact queries from the binary logs, go through the sequence of events from the application trace logs and after an 8-hour marathon meeting, were able to correct the data stored in the RDS.

How Multi-AZ replication works

It was time for us to investigate why we even fell into this situation in the first place. To solve the puzzle, we had to find the answer to the following questions:

  • How does the RDS Multi-AZ replication work?
  • What steps does RDS take at the time of a multi-AZ failover?
  • Why was the data missing in the database?
  • Why did the replication crash?

We got on tens of calls with a number of RDS solution architects over the next week, and were finally able to connect all the dots.

 

In a Multi-AZ setup, the RDS endpoint points to a primary instance. Another machine in a separate AZ is reserved for the standby, in case the master instance goes down. 

The MySQL installed on the standby instance is in shutdown mode; and the replication happens between the two EBS. i.e., as soon as the data is written to the primary EBS, it is duplicated to the standby EBS in a synchronized fashion. This way, RDS ensures that any data written to the master EBS is always present on the standby EBS; and hence, there will be no data loss in the case of a failover.

At the time of a failover, the RDS goes through a number of steps to ensure that the traffic is moved over to the standby machine in a sane manner. These steps are listed below:

  1. Primary MySQL instance goes through a cut-over (networking stopped). Client application goes down.
  2. MySQL on the standby machine is started.
  3. RDS endpoint switches to the standby machine (new primary).
  4. Application starts connecting to the standby machine. Client application is up now.
  5. Old primary machine goes through a host-change (hard-reboot).
  6. EBS sync starts from the new primary instance to the new standby instance.

Looking at the process of failover, it seems pretty foolproof; and the replicas should’ve never gone through any duplicate errors and we should’ve never had any data loss. 

So, what went wrong?

Incorrect configuration variable

We found a MySQL configuration parameter innodb_flush_log_at_trx_commit, which is very critical for the seamless process of a failover.

InnoDB data changes are always committed to a transactional log which resides in the memory. This data is flushed to the EBS disk based on the setting of innodb_flush_log_at_trx_commit. 

  • If the variable is set to 0, logs are written and flushed to the disk once every second. Transactions for which logs have not been flushed to the disk can be lost in case of a crash.
  • If the variable is set to 1, logs are written and flushed to the disk after every transaction commit. This is the default RDS setting and is required for full ACID compliance.
  • If the variable is set to 2, logs are written after each transaction commit, but flushed to disk after every one second. Transactions for which logs have not been flushed to the disk can be lost in case of a crash.

For full ACID compliance, we must set the variable to 1. However, in our case, we had set it to 2. This means even though the logs were written after every commit, they were not getting flushed to the disk immediately.

After learning about this variable, everything suddenly became crystal clear to us. Since, we had set it to 2, the data was committed to the master instance but was not flushed to the primary EBS. Hence, the standby (new primary) never received this data; which is why we could not find it in the master instance after the failover.

But, why did the replicas fail? And, why was the data found in the binary logs?

Apparently, there is another variable called sync_binlog which when set to 1, flushes the data to binary logs immediately. As we had set it to 1 (which is correct), the data got written to the binary logs and replicas were able to read that data. Once the data was read, replicas ran those DML queries onto them and became in sync with the old master.

 

Let’s say, the auto-increment value of one of the tables was X. Application inserted a new row which got auto-increment-id as X+1. This value X+1 reached the replica, but not the standby machine. So, when the application failed over to the standby machine, it again entered a new row with auto-increment-id as X+1. This insert, on reaching the replica, threw the duplicate-key error and crashed the replication.

We went back to our old snapshots (incidentally, we had kept the snapshots of the old replicas before deleting them); and were able to prove that the lost data was present in the replicas.

Once our theory was proved, we immediately went to the master instance and changed the value of innodb_flush_log_at_trx_commit from 2 to 1; and closed the final loop.

Final thoughts

In retrospect, we’re glad that we dug deeper into the incident and how we were able to reach the root of the problem. The incident showed us that we were always vulnerable to data loss because of an incorrect setting of a configuration variable. 

The only silver lining is, however, that we learnt a lot about how RDS manages the Multi-AZ setup and its failovers. And, of course, we gained an interesting tale to tell you all!

Payroll Changes Due to Atmanirbhar Bharat Abhiyaan

Recently, the Atmanirbhar Bharat Abhiyaan package made headlines all across the country. The government announced major steps that will be taken to alleviate some of the impacts of the pandemic on the economy. 

The package involves fiscal policy and relief measures for various industries as the economic ramifications of the pandemic have left no sector untouched.

Read more: Highlights from the Atmanirbhar Package

How does Atmanirbhar prompt payroll changes?

As a part of the relief package, the government also introduced a few measures that will change payroll processing to an extent. Here are the major payroll changes in effect.

  • Reduction in EPF contribution
  • Minimised TDS rates 
  • Changes in Direct Tax (ITR filing deadline)
  • Selection of tax regime (Dual Tax Regime)

payroll changes atmanirbhar razorpay payroll

EPF contribution rate

Under the Atmanirbhar package, the EPF contribution rate of both employer and employee is reduced to 10% from the previous 12%. This is for all categories of businesses that come under the EPF & MP Act, 1952. 

This payroll change is introduced to aid both employers and employees of over 6 lakh businesses manage funds in a slightly relaxed manner.

As a result of the reduction in the EPF contribution rate, employees will have access to higher liquid funds because of higher take-home pay. This also helps lower the liabilities of employers to a certain extent.

This payroll change is applicable for the months of May, June, and July.

Note: The reduced EPF contribution rate is the minimum number for the period mentioned above. However, employers and employees can make higher contributions.

New TDS rates

During the Atmanirbhar package announcement, the government also called forth the new TDS rates. 

According to the announcement, there is a reduction in the tax deducted at source by 25% for all non-salaried payments. Dividend Income, interest on Fixed Deposit, and more fall under the category and the TDS rates are applicable at different levels. 

The new TDS rates have come to effect as of May 14th 2020, and will continue to be applicable for the financial year 2020-21. 

payroll changes atmanirbhar razorpay payroll

ITR filing deadline 

The Atmanirbhar relief package also pushed forward a change in filing Income Tax Returns. 

The government announced that there would be an extension for ITR filing deadline. Earlier, the ITR filing deadline was July 31st 2020, from which the due date is pushed to November 30th 2020. 

The extension in the deadline is a part of the earlier extension made for receiving Form 16 from March 31st 2020 to June 30th 2020. This is to ease some burden on the taxpayers for the financial year.

Tax regime selection (Dual Tax Regime)

Although not a part of the Atmanirbhar package, the Dual Tax Regime has also resulted in payroll changes. The regime brings prevalent changes in the way taxes are calculated from the financial year 2020-21. As opposed to the higher tax slabs with benefits and exemptions, the new tax regime is all about lower tax slabs, but without the benefits and exemptions.

  • The new income tax for employees whose income lies between ₹5 lakh and ₹7.5 lakh is 10% whereas according to the old regime, the income tax is 20%
  • The next slab is for the range between ₹7.5 lakh and ₹10 lakh, where the tax is 15% while the tax is 20% in the old regime
  • Employees with income between ₹ 10 lakh and ₹ 12.5 lakh would pay 20% tax, which is reduced from 30% in the old regime
  • Finally, for income over ₹ 15 lakh, the tax is 30%

Suggested reading: How to Choose the Right Tax Regime

Payroll changes – how to be compliant

Since there are multiple changes in payroll, it is absolutely important for businesses to be compliant. 

If you are dealing with payroll using spreadsheets or an outdated payroll software, it can set you back in more ways than one. Change management is one of the biggest troubles if you have to implement every single one of the payroll changes. This can limit your productivity since payroll processing is laborious and time-consuming. 

Next, your HR team will have to spend long hours every month to keep up. 

If you are wondering how you can manage payroll with minimum impact while being compliant, we have a solution for you.

Opfin is 100% compliant with payroll changes

Opfin is compliant with all the new regulations that have come about as a part of the Atmanirbhar relief package. You don’t have to worry about dealing with compliance ever again! 

It is also compliant with the Dual Tax Regime, allowing employees to choose their preferred regime during the time of their investment declaration for the financial year. 

Employees can see their projected taxes for the year based on their income and regime so that they can make an informed decision keeping their tax liabilities and savings in mind. Further, you completely automate your payroll process without any manual intervention.

Also read: Automate Your Payroll Process With Opfin

Don’t rely on outdated payroll software while you can carry out your payroll operations without any interruptions. Stay up-to-the-minute with changing regulations and compliance with Opfin while it does all the hard work for you.

2020 – The Year for Neobanking in India

RazorpayX - neobanking platform

Banks have been around forever. In India, the history of banking dates way back to 1750 BC. We have traditionally been dependent on banks for all of our financial needs, as individuals as well as businesses. 

Banks have offered us everything that we have required – from current or savings accounts to credit cards, various types of loans and also, insurance and investment plans. But with fintech startups, the dependency on traditional banks for these services is gradually decreasing, especially for businesses.

These new-age banking services providers are commonly known as neobanks. They are using technology to unbundle traditional banks. And how!

Lately, “neobank” has become somewhat of a buzzword in the fintech space. Quite a few neobanking platforms have emerged in the last few years, creating a storm at a global level. The term itself has gained so much momentum because of the media that it has become a hot topic.

Banking has moved forward in leaps in bounds in the past few years. The way businesses and individuals consume financial services has changed significantly ever since neobanking, API banking, and open banking became prominent in 2016. 

It’s no secret that traditional banks are on the front of increased competition from many arcs of the digital world. Neobanks are expanding rapidly, using state-of-the-art tech to win over customers, who demand simpler, faster, and more efficient financial services. In recent years, neobanks have become the next big thing in fintech. 

So, we wanted to bring you a snapshot of how neobanks are on the way to transform financial services globally. RazorpayX neobanking platform - RazorpayX - what is a neobankrazorpayx - neobanking platform

The expansion of neobanking platforms

Fintech startups all over the world, especially in banking and financial services have over 15 million consumers, out of which, over 50% of the consumers are acquired by neobanks. 

The incredible growth opportunity for neobanking platforms is sprouted by their low-cost business model, which has resulted in high adoption by small and medium-sized enterprises, as well as businesses with variable incomes and earnings, and businesses that embrace innovative tech. 

The speed of neobank adoption has intrigued investors, corporates, as well as venture capitalists all over the world. 

[ Read more: Everything You Should Know About Neobanks ]

Neobanking in India 

Globally, neobanks are entirely digitised. But, in India, regulations don’t permit 100% digitised banks. Fintech companies showcasing themselves as neobanks offer services that are built on top of traditional banking services. 

Regulatory framework for neobanks in India

Neobanks in India emerged as a comprehensive aid for banking and financial services, as well as for small and medium-sized businesses. But, RBI’s regulatory policies neither agree nor disagree with the factuality of fully digitised online banks – meaning, in India, neobanks aren’t 100% digital. 

Back in 2018, RBI kicked all forms of cryptocurrency to the curb, with an explanation that crypto transactions would be a threat to security. Also, other tech innovations like online currency and associated banking services appear to have come to a halt. This has put a damper on the tenacity of new business models since regulatory guidelines are muddled. 

However, in August 2019, RBI ushered in a new regulation for the testing of new fintech innovations in a restricted ecosystem, which is motivating for emerging fintech companies. 

Business banking with neobanking platforms

Neobanks have taken business banking to the next level on the grounds of their enormous range of offerings to businesses. 

Usually, businesses have to deal with dreary and dull processes involving payouts and disbursals. These processes take up many hours of manual effort owing to buggy software and complex infra systems. 

Neobanks are supported by the traditional banking infrastructure, and in return, neobanks help sell current accounts. With the partnership, neobanks provide all the benefits of traditional business banking, along with customised reports, flexibility for bulk upload, easier failure identification, scheduling of payouts, and so much more. And, RazorpayX is at the forefront of the banking revolution in India.

With RazorpayX, businesses can

  • Manage their contacts and end-to-end payout operations via powerful APIs
  • Get notified about their payout status and tracking codes through webhooks
  • Make 24*7 payouts, disbursals, and refunds through UPI, NEFT, RTGS, and IMPS
  • Recharge, store or transfer funds to their RazorpayX account for payouts
  • Offer 24*7 instant refunds and payouts to their customers and vendors etc., without any manual intervention
  • View financial summaries of all their transactions and drill down views of transactions at a contact level
  • Instantly access and download financial reports and summaries of their contacts
  • Get complete control and visibility of their finances with real-time summaries, without any help from financial analysts
  • Automate and execute payroll, compliance, and contractor payments with a dual tax regime compliant payroll software

The RazorpayX story

Traditional business banking is not the most efficient way to manage finances. And, several Razorpay merchants told us how suboptimal their business banking experience is. Since we were already spearheading payments, we thought about giving business banking a shot.

We conducted a survey among 1500+ CxOs and spoke to 400+ merchants to understand their business banking experience.

  • 64% of companies believe their payment service providers are best equipped to solve their payment challenges as opposed to banks
  • 10x as many companies polled believe payment service providers innovate better than banks
  • 36% of businesses believe manual dependency and reconciliation are the biggest challenges in their current money management

And so, we started our neobanking journey by creating a whole new platform on which we could build products and integrations. We created an entire API and dashboard payouts platform over a virtual account setup that merchants could use during the early access in 2018. As we scaled, we realised current accounts are the heart of the product to support higher volumes of transactions.  razorpayX dashboard - neobanking platform During our event FTX 2.019, we announced RazorpayX’s expansion into current accounts, payroll, and corporate credit cards. 

We built RazorpayX with Current Accounts in partnership with RBL Bank and included all standard banking services like cheque book, debit card, and accounting statements. For payroll, we acquired Opfin, a payroll and HR management software company, that also manages tax filing and compliance via a unified platform, without having to hire any external vendors.

We wanted to take this platform just a little bit further with Corporate Credit Cards.

We’re partnering with banks and networks to build corporate credit cards from the ground up that offer immense flexibility with limited-time credit period and auto-repayment for businesses. These cards powered by our credit intelligence engine can be used to make payments towards Google Ads, Facebook Ads, AWS, Business Travel, and so much more.

[ Read more: RazorpayX – How We Built a Startup in a Startup ]

The future of banking with RazorpayX

Online real money gaming is a forthcoming industry in India. The key aspect of making a great game that attracts a huge customer base is to ensure the game winners are rewarded, and really fast. The business model is all about providing its customers with instant gratification.

But, relying on netbanking and other manual payment modes are not the best way to go about disbursing the prize money to the winners. RazorpayX has helped companies like Mobile Premier League, RummyCulture, Pokersaints, and many more to transfer winnings immediately, and with ease.

The year for neobanking

There are over 42.5 million small and medium-sized businesses throughout India, constituting nearly 95% of the total industrial units in the country. But, only 47% of these businesses have been able to access tools for payments, disbursals, and other vital processes.

Furthermore, about 23% of SMEs use ERP software and CRMs. This means, there’s a huge market opportunity for neobanks, especially since they have a lot to offer. 

The gig economy of India has over 15 million contract workers and freelancers, who actively boost the growth of startups. And just like SMEs, only about 67% of the gig economy has access to innovative tech that helps with money management. Neobanks can help the gig economy by enabling independent workers with customer management and banking services.

Over the last 3 years, India has seen the rise of neobanks with 811 by Kotak, Yono by SBI, RazorpayX, Open, NiYo, and more. And, these neobanks have been successfully helping SMEs, large enterprises, and the gig economy with billing, cashflow management, disbursals, vendor management, and so much more.

Introducing Saved VPAs for UPI Payments through Razorpay

save upi vpa razorpay

UPI has become the most preferred payment method across India, but one problem that consumers still face is remembering their UPI Virtual Payment Address (VPA). Given the way VPAs are structured, it often also happens that they are entered incorrectly. 

We have observed this to be a major challenge when businesses on our platform accept UPI payments from their consumers. Nearly 20-25% of consumers enter an invalid VPA. Hence, to make your end user’s experience fast and seamless, we are happy to introduce the ‘Saved VPA’ feature on our Standard Checkout.

This feature will allow users to save their UPI VPAs so that they don’t have to enter the same again.The best part is that this feature is aligned to the existing Saved Card feature of Razorpay. So if you are already using the Saved Card feature, it will be really easy for you to understand and integrate. 

We have enabled the Saved VPA by default for all businesses on our Standard Checkout.

What problem will ‘Saved VPA’ solve? 

Let’s start with a simple question – Do you really remember all your UPI account VPAs? We know this is not easy. 

In the current scenario, the customer is asked to enter their VPA whenever they are carrying out a transaction via the UPI Collect flow (enter VPA to proceed). Data for users on IOS and desktop shows that 99% of UPI payments are done through the UPI Collect flow (the rest is UPI QR code). For users on Android, there are many apps/platforms where UPI intent (click on app to make payment) option is still not available. 

In all of these cases, the user has to enter his correct VPA address to make the payment. Let’s take an example: Rahul has created accounts in all the major UPI apps and has linked his 2-3 bank accounts with these UPI apps. Let say, his VPAs are: 

  • Google Pay: user_name@okhdfcbank (note: not just okhdfc), user_name@okaxis, name@okicici (note: not okicicibank) 
  • BHIM: Slightly easy to remember – phone_number@upi
  • PhonePe: phone_number@ybl or user_name@ybl
  • PayTM: phone_number@paytm

There are many other apps and platforms in the market for the user to register and create a VPA. The UPI VPA is different for different apps and platforms. No wonder then that someone like Rahul will end up taking a long time to make UPI Collect payments and often end up entering incorrect VPAs. 

No more incorrect VPAs

As the feature name suggests, Saved VPA allows customers to save their UPI VPAs so that they don’t have to enter the same again and again. The user has to just tap on his Saved VPA to initiate a new UPI payment. This feature helps in improving your overall user experience, reduces cart abandonment, reduces time taken by the user to complete the transaction, and improves payment success rate.

Initial insights have shown that the success rate for UPI Collect payment goes up by upto 15% with this feature.

Razorpay Saved VPA benefits:

  • VPA details are stored within a PCI secure vault
  • Removes the need for the businesses to store the VPA details
  • Ideal for businesses wanting to implement a quick checkout process for known customers
  • Seamless process to add and delete VPA details within the vault

USP: Global Saved VPA

  • Razorpay Standard Checkout allows users to store their VPA while carrying out a transaction for a business and can then be accessed (with login credentials) wherever Razorpay Standard Checkout is enabled, even with other businesses
  • For example: A user who is visiting Cure.Fit for the first time will be able to fetch and use his Saved VPA, if he has done a UPI transaction on any other business using Razorpay, like IRCTC.

For Server to Server/Custom UI integration, you will be able to fetch customer VPAs that were entered on your site or platform using local tokens.

How does this work?

  • You can save the details of a VPA entered by the user on Checkout
  • The entered VPA details are saved as tokens by Razorpay
  • On a repeat visit, while making a payment, the customer is shown all the generated tokens
  • The customer selects Saved VPA and completes the payment by just tapping on the shown VPA

Saved VPA is secured by PCI-DSS compliance 

  • Encryption through PCI-DSS compliance: First things first, Razorpay does not store your data as it is. Razorpay is PCI DSS compliant. The PCI Security Standards Council is a global organization that sets compliance rules for managing user data for all online payment systems. What this means for you is that your online transactions are encrypted to ensure there is no data interception
  • Tokenization to prevent exposure of data: The sensitive UPI information entered by the customer is stored and secured as “tokens” in Razorpay. This “token” is a unique set of characters that replace your original VPA address. This allows the payment to be processed without exposing your sensitive details
  • Consent to save: In case of Razorpay Standard Checkout, the customer’s explicit consent is taken to store the details. A checkbox is shown with the ‘Saved VPA’. option

Want to get this enabled for your business? Leave us a query here and we will get back to you. Not a Razorpay Customer? Sign up today for the ultimate payments experience!

Upgrade to a Dual Tax Regime Compliant Payroll Software this Financial Year

dual tax regime opfin

Earlier this year, the Finance Ministry of India introduced the dual tax regime, a whole new tax regime to the existing one, bringing in prevalent changes to the way taxes are calculated for employees from the financial year 2020-2021.  

Since the financial year has just begun, businesses need to quickly upgrade to a payroll software that is compliant with the dual tax regime and automate their payroll process.

Let’s talk a little bit about the tax regime.

As opposed to the higher tax slabs with benefits and exemptions, the new tax regime is all about lower tax slabs, but without the benefits and exemptions. The Union Budget 2020 allows employees to choose from the two options.

dual tax regime payroll software

  • The new income tax for employees whose income lies between ₹5 lakh and ₹7.5 lakh is 10% whereas according to the old regime, the income tax is 20%
  • The next slab is for the range between ₹7.5 lakh and ₹10 lakh, where the tax is 15% while the tax is 20% in the old regime
  • Employees with income between ₹ 10 lakh and ₹ 12.5 lakh would pay 20% tax, which is reduced from 30% in the old regime
  • Finally, for income over ₹ 15 lakh, the tax is 30%

The perks of the new income tax regime

Lower taxes

Your employee can take home more money than before under the new tax regime since the taxes are reduced. Meaning, your employee need not exclusively invest in tax saving schemes.

Fewer compliances 

The new tax regime is very straightforward compared to the old regime. Except for NPS, savings interest from the post office, and PPF, benefits, and exemptions are cut off, making the tax filing process much simpler.

Flexible investments 

With the new tax regime, your employee can personalise their investments that provide better fluidity to withdraw their money.

Like we mentioned before, the benefits and exemptions are nearly cut off. HRA (House Rent Allowance), housing loan interest, investments like life insurance, provident fund, etc. (Section 80C investments), medical insurance, education loan interest, savings bank interest, and leave travel allowance are removed.  

What exemptions are still available in the new regime

  • Leave encashment on retirement
  • Scholarship received for education
  • Funds received on VRS up to ₹5 lakh
  • Maturity amount and short term withdrawals from NPS
  • Pension commutations
  • EPF
  • Death, retirement benefits

How to choose between the two income tax regimes

Your employee should consider both the advantages and disadvantages of the new tax regime in comparison with the old one. They should calculate their deductions, income after taxes, and the total tax for their annual income, based on both the regimes. 

This will help them understand what works for them the best. 

How the new income tax regime will impact your payroll 

Payroll compliance is absolutely important, especially when there is a change in regulations. Having an out-of-date payroll software will definitely not help you with change management and will limit your productivity since payroll can be largely time-consuming if done manually. 

Also, let’s not disregard the fact that your HR team will have to spend hours and hours every month to keep step with compliance, whereas they could be contributing to the business. 

If you’re wondering what can help your business minimise impact, let’s introduce Opfin, a payroll software that will put an end to all your payroll processing troubles. 

Opfin is compliant with the dual tax regime. The payroll software allows your employee to choose their preferred regime during the time of their investment declaration for the financial year. 

They can also see their projected taxes for the year based on their income and regime so that they can make an informed decision keeping their tax liabilities and savings in mind. dual tax regime Your employee can then file their declarations and edit them based on their regime. Opfin also recommends a breakup predicated on their salary, so that they’re aware of the benefits of both regimes. 

This helps you completely automate your payroll process without having to worry about the dual tax regime compliance, without any manual intervention.

[ Suggested read: Automate Your Employee Salaries with Opfin ]

Opfin for all your payroll needs

Relying on outdated payroll software will create a big setback for your business.

Opfin will help you carry out your business operations without any interruptions since the software scales itself and helps you stay up-to-the-minute with changing regulations and compliance. 

Using Machine Learning to Detect Fraud: Introduction

machine learning fraud prevention e-commerce free trial software

The last couple of decades have seen the rise of e-commerce throughout the world, and both merchants and customers are now able to experience a level of comfort in dealing and shopping that could only be imagined before. For the merchant, this means easier showcasing of goods, 24×7 operation, a chance to expand their global outreach and so much more. Unfortunately, it isn’t just the stores that have evolved, major problems that shop owners used to face in the pre-internet era such as fraud have evolved too.

Fraud is a much less talked about facet of e-commerce which has a large impact on the revenue of a business. E-commerce businesses across different industries have seen up to 40% of fraudulent orders on a regular basis.

Types of fraud

E-commerce frauds happen on Cash On Delivery (COD) as well as prepaid orders. One common type of fraud is the Return To Origin (RTO) fraud where the customer initiates a return on receiving the product and either using it temporarily, swapping it with a faulty/damaged product or denying that they ever received the product. Payment frauds related to credit cards, where the customer initiates a chargeback on receiving the product and denies having made a purchase with the card in question, are also quite common. Other types of e-commerce fraud include promo code abuse, where a single customer signs up multiple times on an app to avail discounts using promo codes, and account takeover, where a fraudster gains access to a customer’s account and purchases multiple items on the customer’s behalf.

return to origin orders e-commerce flow

However, it would be a gross underestimation to think that e-commerce frauds are limited to these types. Frauds are ever-evolving and new ways of defrauding come up more often than one would imagine.

The data age

Traditionally, tech solutions to problems centred around fixed rules for solving problems. For example, to tackle e-commerce fraud, one of the rules we can create is, “if the mobile number and pin code of the customer doesn’t seem correct, declare the order as a fraud”, which roughly translates to (note that this is just an example and more rigorous checks can be carried out),

if (no. of digits in mobile number != 10) then
  if (length of pincode != 6 or no. of digits in pincode != 6) then 
    reject order;

This seems like a good way to tackle this problem, but this has several issues, the most important one being that we don’t really know what rules to build and apply. While active research is being carried out to solve such problems, something like e-commerce fraud is ever-evolving and hence, no fixed set of rules will ever be able to cover all fraud cases.

This is where data-based solutions come in. These involve recording and analyzing data over a period of time and trying to figure out patterns in the data that would provide enough insight to come up with a solution. 

Large companies record mind-boggling quantities of data every day, given that we as end-users turn to the internet for much of our daily activities. As early as 2017, for instance, in every minute of an average day, Google conducted 3.6 million searches, Skype users made about 1,54,200 calls, Netflix users streamed 69,444 hours of videos and Instagram users posted 46,740 photos. By 2018, over 2.5 quintillion bytes of data was generated each day of the year. As of 2020, it’s estimated that about 1.7 MB of data is generated by every single person on Earth every second, and all of it is being stored. The age of data is upon us.

Implementing rule-based solutions for complex and ever-changing problems such as e-commerce fraud is not feasible and hence data-based solutions are preferred for such problems.

Hence, it is no surprise that data-based solutions have become the most popular ways of tackling the e-commerce fraud problem. Specifically Machine Learning, a concept closely related to Artificial Intelligence (AI) is employed these days to try and solve this problem.

The basics of Machine Learning

How does ML work

Machine Learning (ML) is a set of algorithms that can actively recognize patterns from large amounts of data and use these patterns to predict a certain parameter – in this case, whether a given order is fraudulent or not. Machine Learning has been around for a while now – since the later part of the 20th century but only came into mainstream programming in the 2010s.

On a broad level, ML algorithms can be classified into supervised and unsupervised algorithms. Both kinds of algorithms require many examples (data records) to learn any useful patterns. The difference is, supervised ML algorithms require labels for each data sample while unsupervised ones don’t. A popular example of a supervised ML problem can be rent prediction; we can provide a dataset containing various attributes pertaining to the area, location, number of rooms, size of rooms, etc. of the house and label each house with its corresponding rent.

A supervised ML algorithm can learn how these attributes affect the rent of the house. An example of an unsupervised algorithm can be learning from user behaviour and giving recommendations based on their liking. Detecting e-commerce frauds is mostly a supervised classification problem, given that a dataset with orders and labels (fraud/not fraud) would be available.

To sum it all up,

Supervised Machine Learning algorithms require labelled samples to learn from data, while Unsupervised ML algorithms don’t need labels to learn from data.

Further, this problem is a classification problem, in which the output can be one of a predefined set of values called classes (‘fraud’ and ‘not fraud’ in this case), as opposed to a regression problem, where the output can be a range of real numbers (say ‘10.0’ to ‘100.0’). A classification problem in which the number of output classes is equal to 2, as in this case, is called a binary classification problem, as opposed to a multi-class classification problem, where the number of output classes is more than 2.

The working of ML models varies according to what algorithm is used to implement the model, however, all supervised models follow a certain pattern of working. The very basic idea of a model is that it would learn a function mapping between the inputs ‘X_i’ and the output ‘Y’ using the examples given to it. The complexity of the function that a model can learn varies according to the algorithm. For instance, an algorithm like Logistic Regression would end up learning a much simpler mapping as compared to a Multi-Layer Perceptron. This function is called the Hypothesis. A sample hypothesis for a model operating with two features ‘X_1’ and ‘X_2’ can be:

 h(X) = W_0 + W_1*X_1 + W_2*X_2

This is a fairly simple hypothesis that is used by a model like Linear Regression. The figure below demonstrates how a simple hypothesis function like a line can do well in a binary classification task if the points from the two classes are already separate. The blue and orange points represent two separate classes. Points on the left side of the hypothesis would be marked as ‘blue’ and those on the right as ‘orange’. This would mean that most of the points could be classified correctly using this kind of a hypothesis.

In case the data is more complex, i.e. the points from both classes are more “mixed” with each other, a more complex hypothesis function will be needed.

using machine learning for fraud hypotheses

At the core of the algorithm is a loss function, which tells the model if it is learning correctly or not. The objective of the training process is to minimize the loss function as much as possible. For each sample that the model sees, it provides an estimation of what the value of y can be for that sample. If the estimation is close to the real value, the loss function is minimized, else it increases, thereby ‘penalizing’ the model. For each update in the loss function, the parameters ‘W_0’, ‘W_1’ and ‘W_2’ are updated in such a way that the next estimation is closer to the real value. Hence, the model learns the mapping between the features and the labels.

Training an ML model involves iteratively updating certain parameters such that a loss function is minimized. The set of parameters which gives the minimum value for the loss function are used to predict the target variable for new samples.

The general process of building and using a Machine Learning model is simple enough to understand. We gather data (in this case, a dataset of recent orders) with multiple features (in this case, for instance, order date, order time, price of the product, information about the product, user account details, etc.) and label each of these as true if they are fraudulent and false if they are not. An ML model is then iteratively trained on this data and tested on a hold-out set (also called the test set), which is never shown to the model during training (more on this later). If the model performs well on the test set, we decide to use the model to predict the order status of future orders. 

using machine learning for rto orders ecommerce

Now, once a new order is passed to the model, it can predict if the label for this new order would be true or false. This being said, the model would not output a value saying ‘true’ or ‘false’ exactly, it would output the probability of the order being fraudulent, i.e., ‘P(fraud)’. It would now be up to us to set a cutoff on the probability that would work for us. This is explained in more detail in the next blog.

Why use ML for this problem

In a nutshell, the reason why ML-based solutions for e-commerce fraud detection are gaining popularity fast is that we as humans cannot fathom how each factor in the e-commerce ecosystem might be affecting the fraudulence of a particular order. We know that there are a lot of factors that might hint at an order being fraudulent, for instance, a user might have made an abnormally large amount of orders in the past few minutes, or the user has entered a monkey-typed address in the address fields or the user has skipped over the basic information needed for an order to be delivered, which will result in an RTO. We cannot, however, evaluate each factor and determine their contribution towards the fraudulence of that order manually.

To prove this point, consider that we take a traditional approach towards solving this problem. We would eventually come up with a set of rules that will determine if an order is fraudulent or not. For example,

if (X_1) then
   if (X_2 and X_4) then 
       …

The rule is far more complex than we as humans can write in an affordable amount of time. On the other hand, Machine Learning models can come up with such rules in a very short amount of time and hence reduce cost, time and manual labour on this task.

Another reason is that these rules can be dynamic and can change over time. Fraudulent users keep changing their tactics to avoid getting caught and novel ways of committing fraud keep coming up from time to time. Giving valuable resources into creating rules only to change them over time is a very cumbersome and wasteful task, and ML provides a far more comfortable solution.

There’s more to come!

This is only the first of the four-part blog series on how Machine Learning can be used to effectively detect fraud in e-commerce. The next instalment of this series would focus more on the technical aspects of which algorithm to choose for this Machine Learning task and which features can be created for the task of detecting e-commerce frauds. Stay tuned for more!

Decoding Payroll – Why Businesses Should Automate Employee Salaries

RzorpayX opfin payroll software

Payroll is one of the most important financial operations a business carries out, no matter the size of the company. For businesses, it’s crucial to ensure that their employees are being paid without any delays.

Having a smooth, reliable, and error-free payroll process directly reflects upon the morale and the financial stability of the business. 

But, do you trust your payroll process to be the best?

What is payroll?

Payroll is the total amount of fees paid by a company to its employees, contractors, and other workers. It’s an organisation’s biggest disbursement, not to mention, the most time consuming human resource task.

Payroll is typically processed over a specific period of time. Organisations differ in the way they process payroll. While the process is different, they all need to work in a highly organised system, be updated with the latest rules and regulations, and a highly structured plan. 

Why your business needs a payroll software

Payroll processing is long, tedious, and so time consuming that it takes away your efforts from other important business tasks. Processing payroll by yourself means never-ending administrative and tax-related responsibilities.

Plus, you need to be somewhat of an expert in tax law and payroll if you don’t want any run-ins with the IT department. Using a payroll management software will help unscramble the process so you can focus on what’s important. Razorpayx opfin payroll software Businesses end up spending too many hours on manual efforts on payroll processing every single month. A payroll software enables you to spend these hours on something more productive. Processing payroll manually is not simply time consuming, but is prone to human error, too.

You have to take into account salary structure, working hours, overtime, vacation days, etc, making manual calculations as complex as can be. 

What you need in a payroll software

You can find two types of offerings in the market today. 

SaaS tools

There are a few tools available that are mostly focused on effective processing. These tools help with salary disbursal and compliance fees like PF, PT, TDS, and more.

This does not mean your entire payroll is automated, someone still has to oversee the process and the disbursal, while making sure compliance is upheld.

Payroll agencies

Several agencies provide services where you outsource your payroll process. These agencies collect your employee database along with all the details they’ll need to calculate their salaries. They either process it manually or using their inhouse tool.

You’ll need to approve the calculations so that they proceed to pay your compliance You need the best of both offerings to have a fully functioning and automated payroll system. 

Opfin – a payroll software that has decoded payroll processing

If you’re wondering what’s so different about Opfin, let’s break it to you.

Opfin works on a Direct Deposit model in which Opfin processes payroll, as long as you maintain your balance. Think of it like a wallet you deposit your money into using which your payroll is carried out. It’s designed to be highly intuitive and easy to use, that takes away all the redundant steps. 

The upside is, you don’t have to worry about TDS, PF, ESI, and professional taxes, ever again. Plus, your employees are always paid on time! Next, you can pay your contractors and pay TDS automatically. Opfin deals with quarterly filings, form 16s, and 24Q.

Opfin gives more power to your employees by allowing them to claim their reimbursements and tax exemptions on their dashboard, based on which their monthly payroll is adjusted automatically. 

Who is Opfin for

A business should be able to carry out its processes without having to interrupt them for payroll.  Opfin helps you track attendance, time and leave management, along with vendor and contact payments.

So, any business that is looking for a non-intrusive payroll processing, needs Opfin. 

Chargeback Fraud Setting Back E-commerce Businesses: Is There a Way Out?

chargeback fraud ecommerce razorpay thirdwatch

Online e-commerce fraud needs no introduction. With the advent of modern technology, seamless payment modes and flexible regulations, processing online purchases is getting easier by the day.

However, this also has a dark side. It has become increasingly easier for cunning fraudsters to find loopholes in order to dupe online merchants. 

One such loophole is chargeback fraud, also popularly referred to as friendly fraud.

Unfortunately for us, there’s nothing friendly about friendly fraud.

What is chargeback fraud?

Chargeback fraud occurs when a consumer makes an online shopping purchase with their own credit card and then requests a chargeback from the issuing bank after receiving the purchased goods or services. 

Once approved, the chargeback cancels the financial transaction, and the consumer receives a refund of the money they spent. And the tricky part? When a chargeback occurs, the merchant is accountable, regardless of whatever measures they took to verify the transaction.

What can risk analysts do about chargeback fraud?

The primary goal for a risk analyst is to identify the source of a risky online payment and mitigate ways to overcome it. 

In order to do so, the analyst attempts to discover whether the order was placed by the authorized cardholder or a fraudster who’s using the legal cardholder’s information. 

Seems pretty straightforward, right? That’s the case for most scenarios, but not chargeback fraud.

For this small subsection, the authorized cardholder and the likely fraudster is the same person. This is known as friendly fraud and is nearly impossible to detect in a cash-driven market like India. 

Let’s now address some of the pain points that Indian business owners face while fighting chargeback fraud and the possible solutions that can be devised for the same. 

What are the types of chargebacks?

Though chargeback fraud is an umbrella of different activities, in order to mitigate it, it’s important to take a step back and evaluate the different disputes that a merchant can face from a chargeback. 

Actual fraud:

This is perhaps the most obvious reason for chargeback and the most common, too. A fraudulent customer used a legitimate cardholder’s information, made a purchase from a merchant and the merchant shipped the order to the fraudster. Upon reviewing their transaction statement, the authorized cardholder identifies a charge as illegitimate due to fraud and files a chargeback, requesting a refund.

Merchant error:

In this case, when the customer places an order on the website, the merchant either never ships out the order or ships out an item that was broken or different than described. This causes the frustrated customer to file for a chargeback compensation.

Friendly fraud:

A chargeback or friendly fraud is the reversal of payment made through debit/credit card by the user, which is debited directly from the bank account of the e-commerce seller. Chargeback enables the consumer to get his/her money back and protects them from fraudulent sellers online.

Under what cases can a consumer file for a chargeback?

There are numerous instances in which chargeback can be availed by the consumers from e-commerce seller. These instances include:  

  • The Quality of the product or services received were not as advertised by the seller at the time of purchase.
  • The consumer claims that he/she has fallen victim to identity theft or has not sanctioned the purchase.
  • There has been some mistake in the Billing amount, or there are issues regarding duplicate billing of a purchase made.
  • The product or service purchased were not received by the consumer.

How is chargeback misused?

Chargebacks are created to protect consumers from deceitful sellers online, however, this option for refund has been grossly misused by fraudsters in recent years. Criminals have found loopholes in the chargeback process and intentionally misuse the option to swindle e-commerce businesses of millions in revenue!

A person commits chargeback fraud by authorising a credit/debit card transaction, receiving the product or service, and later filing a false chargeback request to get the item for free. Common chargeback frauds suffered by e-commerce sellers include:  

  • The purchased product or service received is claimed to be undelivered
  • The original transaction authorised is claimed to be unauthorised
  • The genuine product or service received is claimed to be faulty or deficient

What is the extended impact of chargeback on businesses?

E-commerce sellers are hit hard by chargeback frauds in the past years with the increase in digital payments and approval of credit card purchases. Online sellers not only lose a big chunk of their revenue to chargeback frauds, but their reputation and goodwill is also damaged immensely. 

The fraudulent consumers not only defraud the seller with false chargebacks but also end up leaving erroneous reviews and ratings, further injuring the business. In many cases, the bank in which the seller has its account ends up blocking the seller’s account thinking they are not genuine.

What’s the way out?

There are numerous ways through which e-commerce sellers can fight chargeback frauds; the simplest being a clear return and refund policy on the website or app. The business must keep clear records of each transaction performed, and copies of every bill or invoice sent. 

A more advanced and reliable solution is to leverage technology. In the era of skyrocketing advancements and artificial intelligence, the smartest way to deal with chargeback frauds is to use fraud prevention tools that can keep a record of everything without affecting your time.

How can Razorpay Thirdwatch help you?

E-commerce fraud prevention tools like Razorpay Thirdwatch enable online platforms to detect multiple kinds of frauds and abuses, including chargeback fraud in real-time. 

With AI that utilises the power of natural language processing and predictive analysis, Thirdwatch is able to detect fraud by scanning each transaction on hundreds of variables.

Razorpay Thirdwatch is a powerhouse that quarantines fake or fraudulent transactions by marking them ‘red’ and approves genuine transactions by flagging them as ‘green’ transactions. It also evaluates and maps every device through which a transaction is made, its own ‘fingerprint’ to check future transactions made through it.

E-commerce merchants need to be aware of the different frauds that cause losses and employ intelligent measures to detect and prevent them. With Thirdwatch, business owners can now focus on their growth and leave the hard labour to us!

Install Razorpay Thirdwatch today and simplify e-commerce like never before!

Will Your Salary Structure Change this April Due to the New Tax Regime?

new income tax slabs

I have to admit that when our Finance Minister announced the new personal income tax slabs in Budget 2020, I felt like it was a very good initiative to reduce tax outgo of the middle class and thereby, increase their disposable incomes.

However, after having taken time to compare the new income tax slabs with the current ones, I believe that the new tax regime might not be such a great idea. We also crunched some numbers from our Opfin payroll management solution to check if taxpayers will be able to save tax under the new regime. Unfortunately, data shows they won’t.

This is the first of the three reasons why we believe that most taxpayers should continue with the current regime.

No decrease in income tax outgo

Razorpay acquired a payroll startup called Opfin last year, which helps startups and enterprises manage tax filing and compliance for their employees. We looked at the data of salaried employees on this platform, anonymously, of course, to compute their income tax liability under the current and new regimes.

Here’s what we found:

  • 78% of these employees will get taxed more by an average of Rs 25,000
  • 85% of employees with an annual income of less than Rs 10 lakh will have to pay higher taxes, averaging Rs 13,750
  • 60% of the people in the income range of Rs 10 lakh to Rs 20 lakh, will pay an average of Rs 47,677 more tax
  • Among those earning more than Rs 20 lakh, 58% will have to shell out an average Rs 89,208 more

These calculations were carried out on taxpayers earning different levels of incomes and availing different types of tax exemptions. We believe this sample set is an accurate representation of Indian taxpayers, and data shows that the new regime will make them pay substantially more taxes.

Tax computation will become complicated

In her Budget speech, Nirmala Sitharaman mentioned that the new income tax regime has been introduced to ease the process of income tax filing for individual taxpayers. However, it seems like the new regime will only further complicate things.

Firstly, the current regime has 4 income tax slabs, while the new regime will have 7. This itself will require a higher number of calculations. Taxpayers will also need to compute their tax outgo in the current as well as new regimes to determine which one to select at the time of filing tax returns.

I don’t see how this will make tax computation any easier. Income tax filing is anyway something that taxpayers dread because of the various slabs, exemptions and forms involved in the process. Instead of incentivizing more people to file tax returns, the new regime might just end up deterring them. CAs will be happy, though.

Long-term savings will get discouraged 

Young India doesn’t save. Definitely not as much as it should. In fact, the younger generation is borrowing more than it can afford to pay back. Data shows that household borrowing is at an all-time high, while household savings are going in the opposite direction.

At a time when the government should promote long-term savings, it is discouraging taxpayers by giving them the option to forgo tax saving exemptions under the new regime. By design, tax saving investments encourage long-term investing because of the lock-in periods they come with. Taxpayers can also diversify their portfolio by using different tax-saving investments like ELSS funds, PPF, NPS, etc.

The forced nature of investing and staying invested through tax-saving investments is actually good for taxpayers over the long-term. But under the new regime, taxpayers won’t be incentivised to make tax-saving investments because they can’t avail exemptions. This will only hurt their long-term financial health.

Overall, we believe that the government needs to rethink the new income tax regime. With the economy doing poorly, it makes sense to increase disposable incomes. But that shouldn’t come at the cost of a decrease in long-term savings.

A version of this article was first published in YourStory.