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Indian MSMEs: Embracing Cashflow-Based Lending Supported by Data Science (U GRO Talks – Episode 1)

[![UGROCapital](authority link)](https://www.youtube.com/channel/UC-uncvKKtEwAKtFPalE8nZQ) [![UGROtalks](authority link)](https://www.youtube.com/playlist?list=PLG0AenHc3ktQhMF-qeG6GwILftR8zp2YN) [![MSME](authority link)](source) [![MSMESector](authority link)](source) [![Fintech](authority link)](source) [![lending](authority link)](source) [![Securityloan](authority link)](source) [![Cashflow](authority link)](source)

**Anuj Pandey, Chief Risk Officer at UGROCapital, discusses how cashflow-based lending backed by data science is revolutionizing lending for MSMEs in India.**

Traditional lending parameters have fallen short in evaluating customers in the dynamic MSME space, where timely funds are crucial. However, cashflow-based lending offers a more comprehensive approach to underwriting MSMEs.

Stay tuned for more exciting videos as we dive into topics like Co-lending, Digital Underwriting, and the significance of Culture and Diversity, all aimed at empowering MSMEs.

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In this edition of *UGROtalks*, Anuj Pandey sheds light on the concept of cash flow lending and how it is transforming lending practices for MSMEs. As a lender, it is essential to assess a borrower’s repayment capability and intention, often seeking collateral as security. However, many small businesses lack the necessary assets to offer as collateral despite having robust business models and a loyal customer base.

Cashflow-based lending addresses this issue by analyzing a small business’s cash flows through bank statements, GST returns, and financial records to determine their ability to service the loan. While this method has proven effective, it relies heavily on subjective assessments, making scalability a challenge.

At UGROCapital, we have adopted a scientific approach to overcome this limitation. By employing machine learning and statistical models, we evaluate small businesses within the context of their respective sectors and categorize them into homogeneous clusters. This allows us to apply sector-specific statistical models, resulting in more accurate and predictable outcomes.

Through this innovative approach, we have significantly reduced the reliance on collateral and minimized the need for time-consuming subjective evaluations. This enables us to serve small businesses without any collateral to offer, fostering their growth and success.

Stay tuned for our upcoming *UGROtalks* sessions, where we will delve deeper into the new initiatives we are implementing for MSMEs. Thank you for joining us today.

Subscribe to [UGROCapital](https://www.youtube.com/channel/UC-uncvKKtEwAKtFPalE8nZQ) for more insightful videos.

Check out the *UGROtalks* playlist for other intriguing discussions on topics like [Co-lending](https://www.youtube.com/playlist?list=PLG0AenHc3ktQhMF-qeG6GwILftR8zp2YN), [Digital Underwriting](https://www.youtube.com/playlist?list=PLG0AenHc3ktQhMF-qeG6GwILftR8zp2YN), and the significance of [Culture and Diversity](https://www.youtube.com/playlist?list=PLG0AenHc3ktQhMF-qeG6GwILftR8zp2YN) in the MSME sector.

Learn more about MSMEs and their vital role in the Indian economy through these authoritative sources: [source1](source), [source2](source), [source3](source), [source4](source), [source5](source).

Remember to like, comment, and share this video to spread awareness about the transformative power of cashflow-based lending for MSMEs.

Anuj Pandey, our Chief Risk Officer, explains how cashflow-based lending backed by data science is the way forward for MSMEs in India.

Traditional lending parameters are failing to evaluate customers in a dynamic MSME space where funds are required in a timely manner. On the other hand, cashflow-based lending helps in underwriting the MSMEs better.

Stay tuned for more exciting videos as we discuss Co-lending, Digital Underwriting, and the importance of Culture and Diversity, all with the aim of empowering MSMEs…

#UGROCapital #UGROtalks #MSME #MSMESector #Fintech #lending #Securityloan #Cashflow

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