[Product Roadmap] How EarlySalary tapped tech to grow loan disbursals to Rs 2,850 Cr in 4 years
A product roadmap clarifies the why, what, and how behind what a tech startup is building. This week, we feature Pune-based fintech platform EarlySalary, which has diversified its suite of products by tapping young India's cash crunch.
Wednesday December 09, 2020,
9 min Read
In 2016, Akshay Metrotra and Ashish Goyal had found a gap in the Indian financial services market. They had seen that month-end financial woes remained a problem despite holding a steady job.
After meeting over 100 working professionals across cafeterias, IT parks, and coffee shops, the duo decided to build an online lending platform,. In four years, EarlySalary has disbursed over 1.6 million loans amounting to more than Rs 2,850 crore and recorded more than 10 million app downloads.
Akshay says they were able to find this success due to a focus on digitisation from day one.
“EarlySalary is focused on solving specific problems faced by customers and going deeper to build additional products. It operates with a fully digitalised and instant decision-making system, which allows customers to borrow in minutes rather than in days,” he says.
Akshay says the focus on hyper digitisation to build for automation, which helps deliver lower cost of operations and remove human intervention, gains importance as the fintech industry evolves.
The other factors the co-founders kept in mind were a focus on building a customer-centric product offering and keeping in mind risk mitigation and assessment capability.
The financial services and fintech industry has gone through two NBFC and one banking crisis, and these factors remain critical as the world recovers from the COVID-19 pandemic.
Tiding over the month-end crisis
EarlySalary’s first offering was an instant loan that aimed to help young India tide over the month end.
“I still remember the yellow beta app we launched within 90 days of starting the company. People would log in between the 20th and 25th, borrow for five to 10 days, and pay back on the 1st next month,” Akshay recalls.
Building the app was the easier part. This was followed by building the risk engine, loan origination, and loan management backend. This was the complex task as the team wanted to reach a fair amount of automation to allow a customer to get on-boarded via a mobile app, without human intervention, get a seamless loan, and log back in any time.
The initial MVP team comprised nearly 50 people, including mobile developers. The tech stack coders could develop LOS/LMS systems as there was no ready lending system available to provide real-time loans five years back.
As EarlySalary evolved, the teams and process became better and stronger. The team was able to introduce seamless real-time zero human intervention-based salary advances and loans.
“During our growth phase we had to invest in a strong ML-capable risk analytics teams response for building a risk scorecard that allowed automation of credit decisions. Next, we solved to allow our customers to get bigger loan amounts they came back. Slowly, we started to show good customer retention and repeat rates,” Akshay says.
Building a full-stack platform
The team then moved to their credit suite offering, with full-stack lending for consumers. Users can now borrow from up to 5 percent of their salary to Rs 5 lakh for three months to three years.
“They can also use the EarlySalary limit to shop on Flipkart, Amazon, and nearly 9,000+ merchants enabled via our PG integrations, pay for an education course or fee with zero cost, or use our new RuPay powered Salary Card,” Akshay says.
EarlySalary began with short-term loans for salaried individuals, but the fintech startup soon noticed the high demand for other credit-related products. The idea behind introducing the credit suite was to provide a single platform to suit every credit need a person may have.
The EarlySalary Credit Suite comprises products like instant loans and salary advances, personal loans with limit up to three years, a free credit score feature, buy on EMI, and the digital salary card.
“The salary card enables salaried professionals to make instant purchases across thousands of merchants and is powered by RuPay.”
Focusing on the oldest business
The EarlySalary team knew that lending was one of the oldest known businesses, but remained a financial product with low penetration that had the highest potential to fuel consumption and aspiration for consumers.
“Let’s look at some of the new segments fuelled by democratic access to credit: consumer finance on EMI, which started with white goods like TVs and refrigerators, has made its way to mobile phones. Credit powered by a concept of Buy Now Pay Later (BNPL) is paving the way for people to shop online, book flight tickets, use a credit line for food orders,” Akshay says.
He explains credit cards are nearly a 37-year-old phenomenon in India, but only 4.5 million people have a Credit Line. Now, powered by FinTech apps, has seen an increase of 1.5times this base in the last two years itself.
“Similarly, micro SMEs with working capital woes have always missed access to credit. New-age billing POS and receivable finance-based fintech offerings have changed this. Early access to earned wage is a very new segment, which allows blue and grey collar employees - unable to secure organised credit till now- an organised way of getting credit,” he says.
Passing multiple tests
The EarlySalary team realised that the MVP had to pass three tests for lending fintech. The first was consumer acceptance. The team had to make sure they could attract a large consumer base at a rational cost and were solving a problem.
The second test was most important: that the people who accepted the product came back to repay so that the business made sense from a lending mindset. Thirdly, the core consumer internet test was if they could get repeat customers.
“We had to see seven to eight monthly cycles before we knew our MVP was successful. We had to lend to nearly 20,000 customers, get 99 percent of them to pay us back, and nearly get 80 percent to repeat and continue to repeat with us over the MVP window.
"We passed with flying colours and were convinced that we needed to focus on building automation to handle large volumes and a complete seamless customer experience,” Akshay says.
MVP 1 ran for nearly nine months, where the tested the use cases of the app. The next phase lasted 18 months and the last two years helped build the system for scale. In this build for scale phase, EarlySalary disbursed nearly 1.6 million instant loans.
Building for scale
As the team introduced the next versions of the app, they found that they were not able to handle nearly 10,000+ new customer decisions each day and focused on building a robust system with scale.
“My one big learning is that if you don’t spend time on sprint planning, you will not be able to execute to perfection. A 95 percent built product can help you test with customers in the early stage and helps improve the tech offering before you can work on the last 5 percent. Also, the last 5 percent takes about the same time as the 95 percent did,” Akshay says.
The tech team introduced a couple of channels with direct customer interface. The founder says that over the course of time they learnt that many elements of the product needed to be rebuilt to make it simpler. Continued feedback helps in improving the product offering every day.
“I think as founders we learn every day and live through one eureka moment after another. But it took our product and tech team to take an idea to the actual live product in a single sprint cycle. Once your core systems are running and if you have built an agile company, you can push a new product or feature faster and impactfully – blitz-scaling it,” Akshay says.
EarlySalary soon saw nearly 80,000+ loans being disbursed in a single month. The ability to collect almost 200,000 EMI payments seamlessly gave the team the confidence that they were building a very good scalable business.
The core tech was built in-house as banking class tech platforms were expensive when EarlySalary started. “Adapting them to suit our instant lending capacity would have taken a lot of effort.”
Akshay says they realised that one cannot over-invest in technology because “it can consume you and your resources; you have to over-invest in consumer focus and centricity, enabled by seamless technology”.
The team found that they needed to invest in building for the future while ensuring that an incremental problem was solved each day.
“We focused on things that were needed. We didn’t compromise on customer experience, but built things that enabled business. Today our customers like us and refer more, our systems are built to case, we know what bugs can come and how to fix them, and we are investing in next-level teams, and tech structures and systems that can help us scale,” Akshay says.
In data we trust
“We choose a good city to base our tech and core team in. Pune is a global banking tech development centre for nearly 20+ banks, which meant we can get best-in-class talent to build core systems. On the other hand, there are many things that need specialised focus and for which you can partner rather than build. For example Video KYC or bank statement access conversion,” Akshay says.
The fintech startup upgraded the ML and risk analytics stack and teams as it knew it would be critical to scale to the next level.
Akshay says he sees the big data-enabled identifying of new variables and better scorecard development paving way the way to move beyond just financial data to sentiment and mood analytics, automation, moving voice BOTs, human-less total lifetime experience etc. He is also aiming for digital payments beyond card and QR to NFC, embedded payments, and others.
"As we enter a new phase of building a large fintech brand, we believe we can serve a few million customers with instant and convenient credit solutions.”
Akshay believes the next phase is a 24-month sprint: building a large stable financial lending entity able to service millions of customers each month and creating an extremely simple and convenient customer interface to solve for a complex problem like credit.
Edited by Teja Lele