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StashFin has adopted Engineering, Technology and Culture practices from bigtechs to fuel its digital acceleration:

StashFin, being a digital lending venture, has since 2016 been dedicated to transforming the traditional lending system by providing customers with a flexible credit line card, using a fully digital journey. Parikshit Chitalkar, Co-founder, says this has been made possible by the company’s relentless drive towards digitization of traditionally manual processes and employing advanced technology-based strategies to offer an unmatched level of convenience as well as financial freedom to the customers.”


When covid struck, StashFin accelerated the pace of adoption of digital technologies in its internal processes. When faced with the constraints of the lockdown, its teams were forced to look at each process, find fully digital alternatives and develop a completely online WFH suite for every employee. Parikshit pats his team for having risen to the challenges of a post-pandemic world and posting growth in all aspects of the business. “Today, our systems handle disbursal volumes of 100+ loans an hour. Our credit line card customers can load cash on their cards in a matter of 90 seconds from the StashFin app, with the freedom to use it 24×7 whenever and wherever they please to,” says he.


StashFin has managed to embed various technologies into its app and website. It has preferred to have a dedicated team, rather than outsourced vendors. Reveals Parikshit: “We have a 100% in-house technology and data science team that gives us the flexibility to integrate solutions into our products and services within a fraction of the time it would take a vendor to do so. In fact, of the 200+ employees we have today, 40% is part of our engineering, technology infrastructure and data science teams, who in turn work on AI, machine learning and cloud technologies dedicatedly.”

Early on, StashFin made the decision to keep all its technology buildouts in-house and that has paid dividends over time. “This provides us with a key competitive advantage in terms of agility and the ability to innovate. ‘Stashers’ (as we call ourselves internally) love it because they get to work on novel technologies, in sync with the business, and witnessing tangible results almost instantly. It has helped us build a culture that is unheard-of in traditional software development teams,” he says.


StashFin does have deep technical partnerships with the likes of AWS, Google, Cloudflare and NewRelic wherein it uses their resources to develop proprietary solutions either for incorporating into its products or for enhancing the work environment at the organization. Parikshit says a perfect example of this approach was seen during the lockdown period where the company successfully deployed a state-of-the-art WFH infrastructure based on a cutting-edge technology like DNS/Layer 7 VPNs and achieved 100% work efficiency for all employees in record time. “We are elated with what our team of passionate Stashers has achieved and we are completely focused and invested in our human capital for the long run.”


StashFin has deployed analytics to either increase revenues or improve the customer experience. Parikshit explains: “Given our size, the fact that we have built, deployed and now manage over 70 applications in production is pretty commendable. People are often taken by surprise by the extent of our builds, especially coming from such a small team. We are big proponents of adopting not only the latest technology trends but also nuggets of engineering culture from the likes of Facebook and Amazon, which we have been able to learn through our investor network.”

StashFin starts with the 3 aspects of analytics it builds on – credit risk, process optimization and data visualization. “Underlying is a strong data pipeline, and we try to drive a full data democracy where people and models alike can get all the data they want, real time,” says Parikshit, adding: “We are now working on building self-reinforcing models. We are in the business of ingressing large volumes of data and use it to make decisions, which results in value for our customers and teams alike. To facilitate this paradigm, we look at data in 4 distinct categories – data infrastructure, credit risk analytics, process analytics and data visualization. Each has a separate team with a clear mandate.”

Considering that all its products are exclusively digital, analytics has played a key role in rapid growth and success. The company has developed custom analytics solutions, data pipelines, model pipelines and data visualization systems to understand its customer base and the credit requirements and utilize those insights to drive business volume growth vide a superlative customer experience, all the while minimizing credit and default risk. The teams depend on hard data to make day to day decisions, thus equipping them with real insights into customers’ concerns and the ability to offer them practical solutions to resolve these concerns. All in all, it looks at both internal and external customers in the same light and hopes to add value to their lives at every step of the way.


It’s a very satisfying experience for a young engineer to build a feature in a couple of days, deploy it in production, watch how customers interact with the feature live sitting with the sales and customer support teams. Parikshit elaborates: “This kind of exposure unearths their true potential transforming them from just being coders to technologists who can solve real business problems with code, one of the many reasons why we have very low attrition. We are open to new talent who share a similar zeal, thirst for learning and want to participate in our growth journey.”

StashFin likes to celebrate wins and pay credit where it is due, and high performing individuals are rewarded and recognized. “Every Stasher or potential employee is egged on to find their fit in our lithe organization – be it sales, tech, operations, customer service or field executions and collections,” says Parikshit. “We realize that tacit knowledge and the right attitude is critical to a Stasher’s success, hence we promote a lot of lateral movement within the organization. However, we are always open to new talent who share a similar zeal, thirst for learning and who would want to participate in our growth journey by living the values and ideals that are the bedrock of our organization’s success over the past 5 years,” he adds.


StashFin offers loans in the range from Rs500 to Rs500,000 with repayment periods ranging from 3 months to 36 months. Its interest rates are from 11.99% APR (Annual Percentage Rate). But the rates may vary from case to case. All loans are repaid through EMIs via electronic payment system. Parikshit adds: Over the last financial year, we had recorded rapid growth. This growth has been brought about by the unrelenting focus on technological innovation, unmatched customer experience and risk management. It required us to scale our systems and we are now looking to scale our teams in sync with the growth opportunities ahead.”


Parikshit is of the view that when it comes to financial technology revolution in India, it is still in uncharted waters, as a country that is far ahead in many dimensions. For example, the payments revolution brought by UPI. There is nothing similar in terms of user experience, technological complexity and scale exists anywhere in the world, he says.

It is imperative that StashFin remains on the cutting edge of technology and data sciences while employing best business practices. It stays committed to its goal of introducing India to a new paradigm of financial services, rapidly progressing towards digitization of services with financial inclusion as the ultimate goal.

“This makes it imperative that a bulk of our learnings must come from within – via experimentation and continuous customer feedback,” says Parikshit, explaining further: “A lot of our capital investment will primarily be in Artificial Intelligence (AI) this year, especially on developing solutions using computer vision technologies and building neural networks for advanced fraud detection. We have been fine-tuning our Machine Learning (ML) models for credit risk assessment over the last year and will now deploy these on a larger scale to serve a broader segment of customers. We will also be expanding our mobile footprint to provide a larger bouquet of services to our customers.”

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