Why Data Structuring is Critical to the Growth Of India’s BFSI Sector?

Data structure Key to the Success of India's BFSI sector - Fintech CXOs, Entrepreneurs

India is growing into a data-rich digital economy in financial services and insurance. Data Structuring according to business, tech leaders are vital to the success of Indian Banking and Financial Sector. The emergence of data-rich digital economy has opened tremendous opportunities for fast-growing ventures in the sector to build data models that translate into a strong foundation for growth.

This was the chorus in a discussion about the emerging data structuring best practices in the Banking, Financial Services, and Insurance (BFSI) sector were leaders from fintech and insurtech companies at the Digital Pioneers Club CTO Roundtable series, hosted in association with Google Cloud.

Present at the discussion were Sabyasachi Goswami, Chief Business Officer, Perfios Software Solutions; Rahul Bhargava, Chief Technology and Product Officer, InCred; Prajakt Deolasee, CTO, TurtleMint; Saurabh Arora, Co-founder, Plum Benefits and Mitesh Agarwal, Director, Customer Engineering, Google Cloud India.

A sector-wide digital transformation

The fact that Indians have shifted to carrying the mobile instead of the wallet or a debit or credit card is a strong indication of the transformation in consumer behaviour and digitisation of the sector, shared Perfios’ Sabyasachi. He noted that financial transactions and payments have undergone a massive transformation and that solutions like digilocker and Unified Payments Interface (UPI) have had a positive impact on the sector. The National Payments Corporation of India (NPCI) data showed that UPI transactions stood at Rs 3.29 lakh crore in September with the number of transactions at 1.8 billion. Sabyasachi added that the sector is now moving towards a paperless economy and is in the right direction.

Echoing similar sentiments, but in the medical insurance space, Plum Benefits’s Saurabh highlighted the high acceptability of digital procurement of health insurance worth thousands of crores. “In the last one and a half years, about 1,000 corporates purchased health insurance with Plum and not even a single sale has taken place via in-person meeting. So this is the extent of digital transformation we are witnessing” he said.

In financial services and insurance, India is developing into a data-rich digital economy. And this has created enormous opportunity for fast-growing companies in the area to develop data models that will serve as a solid basis for future growth.  

Leaders from fintech and insurtech businesses debated new data structure best practices in the Banking, Financial Services, and Insurance (BFSI) sector at the Digital Pioneers Club CTO Roundtable series, held in partnership with Google Cloud. Sabyasachi Goswami, Perfios Software Solutions’ Chief Business Officer; Rahul Bhargava, InCred’s Chief Technology and Product Officer; Prajakt Deolasee, TurtleMint’s CTO; Saurabh Arora, Plum Benefits’ Co-founder; and Mitesh Agarwal, Director, Customer Engineering, Google Cloud India’s Mitesh Agarwal, Director, Customer Engineering, Google Cloud India’s Mitesh Agarwal. 

A digital shift that affects the entire industry 

According to Perfios’ Sabyasachi, the fact that Indians now carry their phones instead of their wallets or debit or credit cards is a major indicator of the sector’s digitalisation and transition in consumer behaviour. He stated that financial transactions and payments have experienced significant changes, with technologies such as digilocker and the Unified Payments Interface (UPI) having a favourable influence on the industry. According to data from the National Payments Corporation of India (NPCI), UPI transactions totaled Rs 3.29 lakh crore in September, with 1.8 billion transactions. Sabyasachi went on to say that the industry is progressing in the right path toward a paperless economy. 

Plum Benefits’ Saurabh echoed similar comments in the medical insurance industry, highlighting the strong popularity of digital health insurance procurement valued millions of crores. “In the last one and a half years. 

“Money has become a digital product in India,” Rahul continued, referring to the lending industry’s evolution. The digital acceleration in lending has been more in terms of digital documentation and customer acceptance of the process. “The backend operations in lending, where you’d need to collect papers from a consumer like bank statements or proof of identification, have been simplified with multiple layers available on digital platforms like IndiaStack,” he noted. There is no longer any justification for us not to have an end-to-end digital lending process.” 

Prajakt explained how developing foundational technologies has enabled growth in two directions: one, by enabling new ways to distribute insurance, and two, by enabling deeper penetration across insurance categories by cross-selling or upselling insurance products or selling small ticket insurance products. “We are in the business of delivering insurance,” he said of the former.  

The role of technology in the processing of large data sets 

Google’s Mitesh pointed out that all financial services, including banking, securities, capital markets, and insurance, share a core data layer, but each regulator examines it differently. He went on to say that the power of data comes into play when it comes to large-scale data processing and real-time data insights. “Whether you have fast insights from your own data or external data that exists anyplace,” he remarked, “I believe Google has innovated a lot.” While ML models have been used to capture client intent in the financial services industry in the past, he says it’s intriguing to see how this intent can be married to the actual transaction in the digital realm to help provide a customised experience.  

Data structure flaws in the lending and insurance industries 

According to Perfios, 40% of Indian clients are new to credit. Sabyasachi stated that, for credit bureaus like Open Credit Enablement Network (OCEN), GST has played an important role in giving access to mainly organised and sanitised data, but there are substantial gaps that need to be addressed. For one thing, he pointed out that most fintech companies are attempting to organise solely client data. The most important missing link is the organisation of data connected to internal systems, such as procedures and workflows. 

“If a financial institution has to look at data structure, it may be divided into several categories.” One, what are the data structures necessary in a certain process? Second, what data sets are necessary in a workflow? Three, from the viewpoint of the client experience and the product itself, what data structure is required? “I believe it will be pointless until we handle all four buckets,” he added, “because you’re only attempting to solve one bucket, which is about consumers.” 

Rahul, too, emphasised the need of data architecture in the context of loans. He believes that as part of open banking, a decent set of APIs, microservices, or primitives should be made public, allowing fintech businesses to collect data from hundreds of sources and combine it in an easy-to-use consumer-friendly process. 

While the pandemic pushed digital adoption in the health insurance industry, it could only have a minor influence owing to a lack of suitable processes in place, according to Saurabh. He explained how hospitals have suffered as a result of insurers’ lack of data architecture in their procedures. He went on to say that the existing healthcare industry’s lack of codification of diagnoses and treatments has resulted in a fraud analytics gap. “There is no universal coding system for diagnosis or therapy, nor for the payments associated with such therapies,” Saurabh explained. He also mentioned that insurance regulators don’t have access to real-time data, and that uncoded data limits analytics throughout the ecosystem. This has a detrimental impact not only on insurance companies and hospitals, but also on users. 

“How can we have comprehensive health insurance coverage if our processes are inefficient?” he asked, posing an important question. 

“The COVID-19 epidemic forced the health insurance business to digitise,” he said, “but we are still in a stage where our systems are maturing.” We still have a few years until the systems all come together and create a highly efficient health-care ecosystem.” 

Mitesh went on to discuss data structuring potential and how Google Cloud solutions link search trends and intent with an API ecosystem and the entire AI portfolio around vision, voice, and vernacular to create that data-rich customer experience.