BharatPe to provide a superlative experience to customers

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Aanchal Ghatak
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Regardless of the social and economic challenges that businesses may face in the future, they will require a clear roadmap for the use of new technologies if they are to survive and thrive. The use of cutting-edge technologies and digital experiences to improve corporate processes, objectives, and strategies while enhancing workflow and customer experiences is known as digital transformation.


We spoke to Ritesh Srivastava, Chief Data Scientist, BharatPe about his views on digital transformation strategy and more. Excerpts from an interview:

DQ: How has your company been performing over 2022? Elaborate. 

Ritesh: Over the years, our innovative products have been at the forefront of disrupting the nation's fintech ecosystem helping us expand exponentially across the length and breadth of the country.


Started in 2018, the company has grown at a very fast pace. In FY22, the revenue grew 169% to Rs 321 crores from Rs 119 crores in the previous fiscal. The average monthly disbursal rate for loans (merchants and consumers) has risen to about Rs. 1,200 crore, and we have facilitated loans of about Rs. 4,500 crore in FY 2021–22. We aim to reach Rs. 15,000 crore on the merchant and consumer loans this year. Profitability is our key focus and we aim to turn profitable in the next few months.

Additionally, we will also keep making investments in our newer verticals including our ‘Buy Now Pay Later’ product, postpe, and POS, BharatSwipe. 

DQ: How are you keeping up with the ever- increasing demands for digital transformation?


Ritesh: At the organizational level, we believe in moving fast to keep pace with changing consumer needs and fast-growing digitization. To support this, the tech team follows ‘Agile’ development practices that help us launch new products/features in a shorter span of time. At BharatPe, we also make heavy use of cloud-based infrastructure to help us scale our systems fast, so as to keep pace with our business growth. The outcomes generated from our machine learning models are directly integrated into the business decision processes to enable real-time decisions.

DQ: How are you integrating customer experience into IT deliverables? How is it helping in advanced customer experience?

We consistently strive to provide a superlative experience to our customers. This is the reason why we have always stayed committed to build simple, easy-to-use, and secure fintech products that can cater to a large ecosystem of merchants and consumers across the country, including the last-mile areas.  As we gain insights on customer needs, we add new features and updates to improve our products further and make the experience favourable for our customers. 


DQ: How are you managing growing cybersecurity, and data privacy threats?

Our AI/ML-based, auto-adaptable, fraud and risk engine prevents frauds and social engineering activities in real-time, based on a multitude of risk factors and other social & behavioural parameters. We have a 24/7 customer support system that takes immediate action on any suspicious activity reported and prevents the occurrence of fraud. This feedback is fed real-time into the engine to further enhance its continuous deep learning due to the ability of the ML algorithms to learn from historical patterns and recognize them in future transactions. With the ability to find sophisticated fraud traits, our fraud and risk engine has shown excellent results in detecting anomalies/outliers and reporting any suspicious activities in real-time.

DQ: How are CTOs, CDOs and CIOs seeing advancing organizational use of data as key to reaching enterprise objectives?


Ritesh: As a CDO, I feel that organizations should focus on developing advanced and mature data platforms that analyze data in real time and organize it to form a single source of truth that can be democratized across departments and leveraged to predict accurate outcomes. Today, data is one of the biggest enablers for a business as one has access to a lot of business nuances, trends, etc.

Also, the role of a CDO is evolving to become more strategic in nature as he plays an instrumental part in fostering the development of an open and transparent data culture that cuts across organisational and functional boundaries. Also, the CDO is expected to become an integral part of the strategic advisory team as he can equip the leadership with in-depth insights on what's working well for the business, as well as current and future trends.

DQ: How is the digital adoption and employee training in your company?


Ritesh: At BharatPe, we train employees on a range of skills to equip them with the latest digital practices and software being used in the industry. As a practice, we also encourage employees who are experts in a particular field to conduct workshops and sessions in their areas of expertise.

DQ: What will be the trends in 2023?

Ritesh: In the upcoming months, chatbots will employ machine learning and AI to respond to frequently asked inquiries from clients in their native tongue and dialects, a task that call centres usually spend a lot of time and money performing. Fintech businesses can detect certain client questions and interaction patterns through the analysis of big data, and they can then utilize this data integrated into their chatbots.


The Gen Z consumers are heavily influenced by online shopping and e-commerce, frequently using the "Buy Now, Pay Later" (BNPL) option. The fastest-growing e-commerce online payment method in India is BNPL, which will account for 9% of the nation's overall e-commerce market share by 2024, according to the Global Payments Report by Worldpay from FIS. In the recent past, a number of companies have modified their business models to accommodate this new trend and are coming up with plans to address young consumers' demand for BNPL. I expect this category to grow in the year 2023 in India, a country where more than 50% of the population is under 30 years of age.

Another trend to look out for would be credit decisioning. Machine Learning algorithms analyze the loan applicant’s profile using a multiple of alternate data-led parameters to determine his borrowing capacity. This ML-led underwriting will further enable financial institutions to lend to new-to-credit customers who had never formally borrowed in the past.

Decentralized finance (DeFi) is an emerging financial technology that is based on secure distributed ledgers, similar to those used by cryptocurrencies. Decentralized finance (DeFi), which aims to make peer-to-peer transactions instant and free, addressing the current challenges of costly, slow international payments is expected to be back in vogue.