<p>Micro, small and medium enterprises, or MSMEs have been consistent in driving India’s economic growth and creating millions of jobs. Their contribution is only increasing. Yet, most of these MSMEs face a significant challenge in accessing timely and affordable credit, a hurdle that can stifle their growth and sustenance. While the proliferation of data coupled with advanced technologies has brought in transformative changes in many industries; can data science redefine how NBFCs interact with MSMEs? With a plethora of possible use cases, data science is becoming a transformative force for MSME lending. By leveraging data science capabilities, NBFCs are now addressing the core issues of accessibility, inclusivity, and integrity, making the lending ecosystem more dynamic and customer-centric. </p>.<p><strong>Role of data</strong> </p>.<p>For MSMEs, every hour spent running around to get funds translates to lost opportunities in running their businesses. According to a Big 4 survey, 68% of small businesses want to operate digitally, and 55% prefer loan disbursals within seven days. These demands highlight the need for lenders to embrace data science tools that offer insights to enhance operational efficiency, and minimise the time and cost of credit delivery.</p>.<p>The digital revolution, bolstered by the account aggregator (AA) framework and digital public infrastructure (DPI), has been pivotal in this transformation. These frameworks enable NBFCs and fintechs to access diverse datasets seamlessly, allowing them to build accurate credit profiles, facilitate faster disbursals, and improve the borrower experience.</p>.Modi government to soon launch new credit guarantee scheme for MSME sector up to Rs 100 cr.<p><strong>Democratising credit access</strong></p>.<p>Democratisation of credit is one of the most significant outcomes of data-driven lending. MSME owners no longer have to chase lenders for funds, since the accessible and integrated data systems now empower NBFCs to assess creditworthiness in no time.</p>.<p>The availability of financial and behavioural data through platforms such as AA reduces dependency on traditional metrics and enables faster and reliable decision-making. Most companies have also put in place robust governance procedure to ensure that data used for decision-making is secure, accurate, and unbiased.</p>.<p><strong>Customer-centricity</strong></p>.<p>A customer-centric approach is the cornerstone of implementing data science successfully in the financial services sector. For MSMEs, this translates into lenders using data analytics to address their needs more effectively. By analysing real-time data of credit behaviour of a customer, NBFCs can move beyond traditional credit scoring methods to evaluate borrowers holistically, considering a wide range of behavioural and financial indicators. Advanced data analytics also empowers lenders to offer personalised solutions such as tailored loan terms, repayment schedules, and even interest rates to align with the specific requirements of individual businesses, also strengthening the overall customer experience.</p>.<p><strong>Governance and security</strong></p>.<p>Since the generative AI revolution began nearly two years ago, every organisation including financial institutions are increasingly adopting AI and ML, making it even more essential for data governance to take the front seat. Robust governance frameworks help to ensure that data models are reliable, fair, and free from bias. For NBFCs, this is particularly crucial as they often rely on models to underpin key decisions on lending, based on available data sets on customers. </p>.<p>One of the most important aspects is cybersecurity, which is an integral part of the data science unit. Financial institutions are often targeted by cybercriminals due to the huge amount of sensitive financial data that the organisations hold. Safeguarding this data is a critical concern.</p>.<p><strong>Conclusion</strong></p>.<p>The adoption of data science in lending has altered how NBFCs serve MSMEs. Seamless credit access empowers businesses to grow, while such an ecosystem helps the financial institutes focus on banking the underserved and unserved segments. As MSMEs embrace digitisation, adoption of data-driven solutions by NBFCs is not only reshaping financial services but also unlocking opportunities for millions of small businesses to thrive.</p>.<p><em>(The author is MD & CEO of NeoGrowth Credit)</em></p>
<p>Micro, small and medium enterprises, or MSMEs have been consistent in driving India’s economic growth and creating millions of jobs. Their contribution is only increasing. Yet, most of these MSMEs face a significant challenge in accessing timely and affordable credit, a hurdle that can stifle their growth and sustenance. While the proliferation of data coupled with advanced technologies has brought in transformative changes in many industries; can data science redefine how NBFCs interact with MSMEs? With a plethora of possible use cases, data science is becoming a transformative force for MSME lending. By leveraging data science capabilities, NBFCs are now addressing the core issues of accessibility, inclusivity, and integrity, making the lending ecosystem more dynamic and customer-centric. </p>.<p><strong>Role of data</strong> </p>.<p>For MSMEs, every hour spent running around to get funds translates to lost opportunities in running their businesses. According to a Big 4 survey, 68% of small businesses want to operate digitally, and 55% prefer loan disbursals within seven days. These demands highlight the need for lenders to embrace data science tools that offer insights to enhance operational efficiency, and minimise the time and cost of credit delivery.</p>.<p>The digital revolution, bolstered by the account aggregator (AA) framework and digital public infrastructure (DPI), has been pivotal in this transformation. These frameworks enable NBFCs and fintechs to access diverse datasets seamlessly, allowing them to build accurate credit profiles, facilitate faster disbursals, and improve the borrower experience.</p>.Modi government to soon launch new credit guarantee scheme for MSME sector up to Rs 100 cr.<p><strong>Democratising credit access</strong></p>.<p>Democratisation of credit is one of the most significant outcomes of data-driven lending. MSME owners no longer have to chase lenders for funds, since the accessible and integrated data systems now empower NBFCs to assess creditworthiness in no time.</p>.<p>The availability of financial and behavioural data through platforms such as AA reduces dependency on traditional metrics and enables faster and reliable decision-making. Most companies have also put in place robust governance procedure to ensure that data used for decision-making is secure, accurate, and unbiased.</p>.<p><strong>Customer-centricity</strong></p>.<p>A customer-centric approach is the cornerstone of implementing data science successfully in the financial services sector. For MSMEs, this translates into lenders using data analytics to address their needs more effectively. By analysing real-time data of credit behaviour of a customer, NBFCs can move beyond traditional credit scoring methods to evaluate borrowers holistically, considering a wide range of behavioural and financial indicators. Advanced data analytics also empowers lenders to offer personalised solutions such as tailored loan terms, repayment schedules, and even interest rates to align with the specific requirements of individual businesses, also strengthening the overall customer experience.</p>.<p><strong>Governance and security</strong></p>.<p>Since the generative AI revolution began nearly two years ago, every organisation including financial institutions are increasingly adopting AI and ML, making it even more essential for data governance to take the front seat. Robust governance frameworks help to ensure that data models are reliable, fair, and free from bias. For NBFCs, this is particularly crucial as they often rely on models to underpin key decisions on lending, based on available data sets on customers. </p>.<p>One of the most important aspects is cybersecurity, which is an integral part of the data science unit. Financial institutions are often targeted by cybercriminals due to the huge amount of sensitive financial data that the organisations hold. Safeguarding this data is a critical concern.</p>.<p><strong>Conclusion</strong></p>.<p>The adoption of data science in lending has altered how NBFCs serve MSMEs. Seamless credit access empowers businesses to grow, while such an ecosystem helps the financial institutes focus on banking the underserved and unserved segments. As MSMEs embrace digitisation, adoption of data-driven solutions by NBFCs is not only reshaping financial services but also unlocking opportunities for millions of small businesses to thrive.</p>.<p><em>(The author is MD & CEO of NeoGrowth Credit)</em></p>