Kindly share Credifin’s key solutions portfolio and how does Credifin differentiate itself from other NBFCs offering similar lending services in rural and semi-urban areas?
Credifin is a leading provider of EV loans (eRickshaw and eLoaders), LAP and MSME focused lending solutions to the underserved communities across 13 states and UT.
Our approach is fundamentally different than other NBFCs in our category. We follow a credit focused, customer-oriented model tailored to the unique needs of underserved communities.
We go beyond traditional credit checks to deeply assess both the credibility of the borrower and the economic viability of the loan. Our goal is to ensure that every loan we extend is a tool for empowerment, not a burden.
We focus on real data, local market conditions, and the customer’s earning potential to ensure that they are not driven by unrealistic expectations, but by practical, achievable outcomes.
Ultimately, we strive to ensure that every customer is better off after taking a loan from us, owning more, earning more, and building lasting financial resilience.
How did your background in investment banking and risk consulting influence Credifin’s financial architecture?
My background in risk consulting and financial consulting has significantly influenced Credifin’s financial and operational design. Having a deep first hand knowledge of the performance patterns of various financial institutions, we’ve been able to build products that are not only financially sound for the company, but also really beneficial for the customer.
Over time, we’ve developed a much deeper understanding of customer behaviour and their unique financial needs. This insight has not only helped us refine our products but has also strengthened our credit evaluation framework and risk management processes.
In addition, our approach enables us to collaborate with a wide range of institutions, some of which may not traditionally operate within the financial services space but offer solutions that are highly relevant and valuable to our customers. These partnerships allow us to create a more holistic support system, delivering benefits that go beyond just credit and contribute meaningfully to the customer’s financial journey.
For instance, we recently partnered with a fintech player to provide instant QR code generation for our borrowers. This allows small business owners to receive digital payments directly into their bank accounts, many for the first time. While this may not yield immediate financial returns for us, it significantly empowers the customer by digitising their cash flows, enabling better record-keeping, and increasing their access to formal financial services.
These seemingly small innovations have a compounding effect: they build trust, improve repayment behaviour, and reduce fraud risk. More importantly, they help our customers become a part of the digital economy, which is ultimately central to financial inclusion and resilience.
What performance metrics are tracked at the branch level and how are they standardised across states?
We track a wide range of performance metrics at both the branch and individual levels. Our in-house technology platform manages loan origination, collections, and performance monitoring. It allows us to generate both quantitative and qualitative reports, giving us a 360-degree view of performance.
For example, each sales executive is evaluated across 22 distinct data points—capturing not just volumes and outcomes, but also quality of engagement and compliance. Because the system is built in-house, it’s highly flexible; we can generate real-time or historical reports as needed, and compare performance across executives, branches, or states.
We’ve also embedded AI capabilities locally within our platform, enabling dynamic, on-demand reports tailored to any individual, branch, or metric. This not only helps us track current performance with precision but also provides predictive insights to guide future business planning and expansion
How does the company integrate with India Stack APIs like Aadhaar, DigiLocker, and UPI for disbursal and monitoring?
We’ve seamlessly integrated with over 20 API stacks, including Aadhaar, DigiLocker, UPI, Account Aggregators, and more—each with multiple vendor redundancies to ensure near-zero downtime and maximum operational efficiency.
For instance, through Account Aggregator APIs, we can instantly access verified bank statements, eliminating the risk of forged documents and significantly reducing turnaround time. This not only enhances risk control but also improves customer experience by removing the need for manual paperwork.
We also leverage eKYC, digital signatures, and QR-based payment systems to streamline disbursals, simplify onboarding, and ensure compliance—all while maintaining speed, security, and scalability.
What are the criteria that determine the MSMEs eligible for loans under the women entrepreneur initiative?
Under our Women Entrepreneur Initiative, MSME loan eligibility is primarily determined by the applicant’s existing income, rather than projected or incremental income. This approach ensures that loan repayment does not place undue financial pressure on the borrower from day one.
By mapping a customer’s current cash flow, we ensure that her existing income is sufficient to comfortably service the EMI. The additional income generated through the business loan is then seen as a means to improve her quality of life and strengthen the overall profitability of her enterprise.
This model promotes responsible lending while empowering women entrepreneurs to grow sustainably ensuring that every loan becomes a step forward, not a burden.
Has Credifin implemented any AI/ML solutions for credit scoring or fraud detection? If yes, how are they trained for rural lending?
Credifin has developed in-house AI/ML solutions for credit scoring and fraud detection, specifically tailored for rural and semi-urban lending. These models are trained on a rich dataset built from the historical and ongoing performance of our field teams, as well as the decision patterns of our credit managers. The algorithm is self-learning—it continuously evolves based on real-time inputs, improving its ability to identify risk factors and assess loan applications accurately.
However, it’s important to emphasize that these AI/ML tools serve as decision support systems and not as decision makers. They act as a ‘second brain’ for our credit team – providing recommendations, flagging inconsistencies, and minimizing human error. Final loan approvals remain a process led by our sales team, ensuring contextual judgment and local understanding are always part of the decision.
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