FlexPay’s core operational strength lies in its proprietary AI-driven loan management system, enhanced by a data-rich Decision Engine, shared Anil Pinapala, Founder & Chief Executive Officer, Flexpay by Vivifi, in an exclusive interaction with Srajan Agarwal of Elets News Network (ENN).
With the proliferation of fintech apps in the market, what specific tips do you offer borrowers to help them distinguish genuine lending platforms like FlexPay from potentially fraudulent ones?
With the rising threat of illegal lending apps, borrowers have fallen prey to frauds thus leading to ambiguity in their minds on the genuineness of lenders. Both the lenders and borrowers have a responsibility to stay vigilant and follow the best practices in lending and borrowing.
To ensure that the choice of lender is legitimate, the borrowers should visit the website and ensure that the app belongs to a legitimate lender registered with the RBI or works with a Bank/NBFC registered with RBI. To protect borrowers’ interest, RBI has set various guidelines which Banks & NBFCs have to abide by. It is a mandate for all legal lending companies to clearly provide their Company Identification Number (CIN) and details of the Certificate of Registration (CoR).
Secondly, during loan application, borrowers should ensure that they carefully read the terms and conditions, understand the fine print, i.e., the repayment terms and the cost of accessing the loan. This is to ensure that they are making a well informed decision, with full transparency. A few red flags to look for, that can help determine a fraudulent lender are lack of transparency in loan interest amount or fees, pressurising the applicant to act immediately and the promise of a guaranteed approval without looking into the creditworthiness.
Further, the legal lending apps also list a Grievance Redressal Mechanism and are required to adhere to various regulatory guidelines on KYC and Collection Practices which are designed to protect the borrowers. Borrowers can also look at reviews from other customers on app stores to get an insight into their experience. It is imperative that they follow this checklist and make a final decision based on in-depth research and understanding of the kind of loan that they are going for.
In a financial landscape dominated by traditional banks, what do you see as the essential role of fintech lenders like FlexPay? How do you bridge gaps that traditional banks can’t or won’t fill?
Fintech lenders like FlexPay play a vital role in today’s financial landscape dominated by traditional banks. We aim to bridge gaps that traditional banks often cannot or are unwilling to address.
Firstly, fintech lenders enhance accessibility to financial services, extending credit to individuals and businesses who might not meet the strict criteria set by traditional banks, thereby promoting financial inclusion and leveling the playing field. Secondly, digital lenders bring efficiency to the lending process by harnessing advanced technology and data analytics, expediting loan approvals and disbursements. Furthermore, offering a degree of personalisation that is often lacking in traditional banking. Through innovative use of data and AI, we assess creditworthiness more comprehensively, serving individuals with nontraditional credit solutions.
Additionally, we strive to foster innovation in financial services, introducing new products and technologies to enhance our offerings, ultimately benefiting consumers.
The fintech lending space is highly competitive. What unique strategies is FlexPay employing to distinguish itself and gain a competitive edge in the market?
The objective of the organisation has been to write a loan to a customer that has been marginalised by financial institutions across the country and do so profitably. The MFIs have been able to offer loans to a section of the society, banks & large financial institutions have been able to lend to prime consumers or lend against the security of an asset, but there is a large section of Indians who have no security to offer and have the ability & intent to be trustworthy, but they needed a validation. We believe that we had the wherewithal to be the organisation that understood this large lower-middle class and middle-class Indians in cities, towns and villages across India to lend to, recover from and continue to bank with. We built our apps to be super simple for a user to understand their available credit, draw credit, make payments or repay their obligations.
We are India’s only open-ended revolving line of credit for salaried individuals. We are also India’s only scan and pay with credit option for any purchases at over 12 MM registered merchants in India.
What are some of the key obstacles that FlexPay has faced in the fintech lending industry, and how have you strategised to overcome these challenges?
The challenge on initial implementation was onboarding the semi-literate users. While most of the competition is super fixated on simplifying the user flows and gamifying the apps, we looked beyond this challenge to support the underserved / unserved customer base by building the first video based on-boarding application that uses natural language processing to identify the users needs and propose the product for them along with assisting them complete the application flows.
The other challenge that we have overcome is informal employment and the nature of assessment for these borrowers. While these are banked individuals, their salary credits are not consistent in dates / amounts and supporting infrastructure to assess their employment or employability are not sound. We built a model that helps us assess the borrower’s intent to repay and their ability to repay. We offer sachet size limits to these customers to help us understand their patterns and roll-out faster credit raises to performing individuals.
The borrowers understood the product well and adapted quickly to usage of the app. We take pride in our philosophy of Truth-in-Lending and our RBI compliant on-boarding process which is inclusive of a full video KYC of the borrower and take each borrower through our MITC (most important terms & conditions), and a key facts statement that gives them a full perspective of credit that they are about to utilise. This ensures that there is full transparency to the borrower and helps in building responsibility with the borrower base.
Once Vivifi started to gain traction, the digital lending eco-system in India had to face the scourge of illegal (mostly Chinese) lending apps that didn’t follow any law of the land and indulged in coercive collection practices while charging customers over 200%-300% interest rate. When this occurred we were at the forefront of the fight explaining the difference between legal, licensed lenders like Vivifi and the illegal apps to our customers, Media, Regulators, Law Enforcement and Indians at large. Our activism was rewarded with the Digital Lending Rules by the RBI, which has made it easier for the customers to identify legal licensed lending apps while giving them control of their own data and bringing in full-disclosure of credit costs with transparency in agreement terms.
Can you elaborate on how FlexPay is using technology to enhance the loan repayment process, thereby making it easier for borrowers to manage their debts? Also, how are you leveraging that technology to streamline the loan disbursement process, making it more efficient and user-friendly?
FlexPay’s core operational strength lies in its proprietary AI-driven loan management system, enhanced by a data-rich Decision Engine. Underwriting the financially stressed, credit starved, underserved, unserved user group, we had to look beyond the obvious markers which were the reasons for them to be outside the fold of formal credit. We devised algorithms that looked for any reasons that a small loan can be offered to the individual instead of looking for reasons to deny the loan application. We used data from the following sources to build a composite score. – phone while NOT reading contacts or messages (SMS or email) – bank account (using NBFC-AA) – bank statements (OCR based analysis of transactions) – bureau data (including, but not limited to score) – application data – CKYC, NSDL etc., that are available to regulated entities. The composite score gave us the ability to establish the recurring income of the borrower, their intent to repay and their ability to repay. Using this we wrote loans to customers typically labelled as “HIGH RISK” and educated them that credit expanded with their repayment history.
The last significant element that helped in onboarding new customers was the focus on education of responsibility of the borrower in repaying their dues by making the process cumbersome and making the customer undertake all the steps by themselves. This process establishes the seriousness of the loan on the customer and a 2-way video KYC which provides us with facetime in the digital onboarding process where the MITC (most important terms & conditions) and customer responsibilities are explained in detail.
In line with the dedication to Truth-in Lending, FlexPay offers credit products with transparent disclosures, ensuring that all loan terms, such as interest rates and repayment schedules, are communicated upfront. Moreover, we take borrower empowerment seriously, providing financial literacy resources and guidance on budgeting and responsible borrowing.
Our in-house built software products rely on India stack, NPCI based infrastructure and in-house built AI/ML algorithms to identify the customer, offer them credit and manage their transactions.
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