As the financial landscape continues to evolve, the traditional methods of assessing creditworthiness are being reshaped by the power of big data analytics. By harnessing vast amounts of data, lenders can make more informed and accurate lending decisions, reduce risk, and enhance the customer experience. This approach not only optimises the credit evaluation process but also opens new avenues for financial inclusion and innovation.
Leveraging Data for Smarter Lending
Jasmin Gupta, Chief Digital Officer, of Pahal Finance, and Founder, Meitmoney, discussed the fintech industry's rapid growth, noting India's high fintech adoption at 87 per cent, contrasting with challenges in data utilisation among traditional banks and NBFCs. She stressed the need to tap into diverse data sources, like geographic and demographic data, to enhance borrower assessments. Gupta highlighted NeoX's innovative credit evaluation model using social media and email data.
Gupta also showcased Baal Sangini, a successful women-focused lending app utilising data from 500,000 female customers. Despite barriers, she sees vast potential in India's smartphone penetration for expanding data-driven financial services to underserved groups. “When we want to bring the entire ecosystem together and talk about the entire financial ecosystem, I think it's very important for us to understand how all the players can leverage data for the best of the industry,” she added.
Grameen's DEEP Framework for Rural Financial Inclusion
Arindam Dasgupta, Interim Chief Programme Officer and Director of innovation in Digital Finance, Grameen Foundation for Social Impact, outlined Grameen's DEEP framework, focused on digitisation, enablement, ecosystem building, and tailored product design to boost financial inclusion in rural areas. Post-COVID, they shifted from Joint Liability Group (JLG) to individual lending, leveraging alternative data sources. They partnered with private banks, and Grameen introduced QR-based merchant acquisition in rural markets, using digital transaction trails for smarter credit decisions.
Dasgupta highlighted the success of the JLG model for women and advocated for transitioning to digital collateral using location and social media data to provide affordable credit, promoting economic growth and inclusion. “Our objective is to have a lesser, lower-cost credit for the bottom of the pyramid so that they grow and, as they grow, enter economic trade,” he added.
Empowering Women Entrepreneurs in Finance
Kalpana Ajayan, Regional Head, South Asia, Women’s World Banking, addressed the financial exclusion of women entrepreneurs, noting a global missed opportunity of USD 1.7 trillion due to their underrepresentation in lending. Despite comprising one-third of entrepreneurs, women often lack financial histories, complicating loan approvals. Kalpana's initiatives focus on removing gender bias in fintech lending decisions to mitigate algorithmic biases. She highlighted pervasive biases throughout the lending process, hindering women's access to credit from application to collection.
Ajayan emphasised the importance of gender sensitisation in fintechs and highlighted women's lower non-performing assets compared to men. Her projects, including the Prayas programme with SIDBI, aim to provide affordable credit and enhance digital financial capabilities tailored to women's needs, addressing their specific challenges and ensuring equitable access to financial services.
Leveraging AI and ML for MSME Lending
Suhail Khan, Senior Director of Business at BharatPe, emphasised the challenges in MSME lending, noting that less than 20 per cent of India's 63 million MSMEs have formal credit access. He highlighted the $600 billion credit gap, particularly for loans under 10 lakh, and stressed the role of digital payments, like QR enablement, in expanding credit access to smaller towns. His team utilises transaction data from QR payments to enhance loan underwriting and pioneers the daily installment (EDI) model for easier repayments.
Khan talked about AI and ML as a crucial aspect for improving underwriting accuracy by analysing transaction patterns and repayment behaviours, making credit assessment more precise over time. “The beauty of this whole ML thing is that the more data that we collect, the model trains itself, and that is why it is able to improve over a period of time. So, I think this is something that has worked, and this is something that is going to be the future as well," he added.
Innovations In Credit Card Technology
Prithwish Ray, Chief Business Officer of Hyperface, discussed how advancements in credit card technology are transforming underwriting, fraud management, and collections. He emphasised leveraging alternative data, such as purchase patterns, to assess creditworthiness in areas where traditional income data is sparse, particularly in tier-two and tier-three cities. This approach aims to bridge the credit gap effectively.
Ray also highlighted the importance of ethical data practices and transparency in customer data usage to build trust. Technologies like real-time APIs enable quick verification processes, improving the overall customer experience by making credit more accessible and efficient, especially through innovations like credit lines on UPI. These strategies reflect a shift towards more inclusive and technology-driven approaches in the financial industry.
Impact Of Data On Banking
Gaurav Goel, National Head of Start-Up, Fintech, and New Economy Business at YES Bank, highlighted the transformative role of data in banking, emphasising how it has shifted traditional brick-and-mortar institutions towards data-driven financial models. He discussed how banks, as major data generators, are now able to reach previously underserved segments like gig economy workers, micro-entrepreneurs, and MSMEs.
He pointed out that by leveraging extensive data analytics, including alternate scoring methods, banks can now offer tailored credit solutions to demographics traditionally excluded from credit scoring, such as teenagers and housewives. This approach enhances efficiency in product delivery and customer service, ultimately fulfilling the goal of inclusive financial access in a cost-effective manner. “Data is expanding the scope of banking. Earlier, there was a very templated solution; now we have hyper-customised solutions," he added.
The panel discussion focused on how leveraging data and technology can democratise access to credit, particularly for underserved groups like gig workers and micro-entrepreneurs. They also highlighted the ethical use of technology to enhance financial inclusion and discussed innovative approaches.
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