Upping The Lending Game With Digital

Soma Tah
New Update

Money can be borrowed from multiple sources, such as banks, non-banking financial institutions(NBFC), cooperatives, self-help groups, money lenders, and even friends and relatives for that matter.


Banks, financial institutions, cooperatives are supervised by the Reserve bank of India and provide loans at fixed rate and terms. But the loans taken from informal loan providers which comprise money lenders are not supervised by any regulatory body. They generally don’t provide loans at fixed terms and therefore, can charge exorbitant interest rates and can also go up to any extent to recover the money.

But, a greater percentage of low-income urban households still depend on this informal loan sector and there are specific reasons behind this phenomenon. For example, formal lenders such as banks can lend only to those borrowers, who have a job in the formal sector, or with steady and adequate incomes. Banks also need marketable assets as collateral for loans. Now, this has literally kept the formal loan providers out of reach from the borrowers who neither have irregular and uncertain incomes nor any marketable assets.

Also, getting access to the desired loan amount is no less than a harrowing experience for the borrowers. First, the traditional way of seeking loans from  banks and other financial institutions in India is fairly complex in nature. Second, formal lenders also use credit scores and physical verification process to determine the applicant’s creditworthiness, which is again a time-consuming and a tiresome process. It becomes even more difficult for first-time borrowers with a non-existent credit history.



With the rise of a digital economy, lenders have also realized that they need to respond to the consumers’ need for securing instant funds and to make the experience as frictionless as possible. The increasing smartphone penetration in the country with faster mobile internet and a supportive regulatory environment favouring innovations in the operating models of the lenders have also been instrumental for the growth.

The loan to GDP ratio in India stands at an abysmal 17 per cent and there’s a tremendous headroom for the digital lending institutions in India to grow. Boston Consulting Group (BCG) estimates that the total retail loans which could be disbursed digitally in the next 5 years could be over $1 trillion- a 5X increase from the current level of annual digital disbursements.


Innovative operating models have been adopted by the disruptors. BCG has also identified a few prominent models.

Independent platform: Lends to consumers directly without partnering with an incumbent bank. The underwriting is based on a host of readily available information.

Aggregator / Partnership model: Acquires consumers through various acquisition channels and lend to them by partnering with banks or financial institutions. They have a strong underwriting model backed by robust data and algorithms.


Peer-to-peer platform: Connects verified borrowers seeking unsecured personal loans with investors looking to earn higher returns on their investments.

‘Value+’ service in addition to a core service: Built around an existing business as a ‘value-add’ to consumers of such businesses.

In case of a product like secured lending/mortgages, due to the involvement of assets, complete digital processing is still a distant dream. But digital lenders are providing consumers with a simpler, less-paper borrowing experience by digitizing and automating the credit decisions and processing as much as possible. They are leveraging alternate data as a credit surrogate to provide credit to non-traditional borrowers. Most online lending platforms employ big data analytics and machine learning to assess data sourced from online social networks, transactional history, mobile phone records, to evaluate the creditworthiness of borrowers with little or no conventional credit information. This adds a significant edge to alternative lending with a stronger credit approval system for unsecured loans.



The government has undertaken some major initiatives towards creating a favourable ecosystem for consumers to access digital financial services and products. India has leapfrogged many advanced economies by setting up open architecture layers such as Aadhar, UPI, Bharat Bill Payment Systems and systems such as GSTN, TReDS and GeM which will go a long way in boosting digital and data-enabled lending in India as per BCG India report. India Stack, an infrastructure comprising APIs that support electronic authentication of customers’ Aadhar information, e-signatures, paperless e-KYC compliance processes have also played a critical role in boosting digital lending ecosystem in India. Along with this, information on GST returns has emerged as an effective tool for assessing SMEs and fulfilling their credit requirements in a seamless and timely manner.

By recognizing the Peer-to-peer (P2P) lending model, the RBI has not only facilitated the creation of an alternative credit ecosystem for borrowers and lenders but has also brightened the prospects of credit-deprived consumers and businesses in the country. The regulations introduced and the certifications given to recognized P2P lending companies or NBFC-P2Ps have also alleviated any doubts or fears that borrowers or lenders may have. This segment of alternative lending is expected to gather greater momentum in the future.


Alternative lending is the second most funded and one of the fastest growing segments in the Indian FinTech space, according to PwC Fintech India Report 2017. More than 225 alternative lending companies have been founded in India as of 2017 and around 10 per cent of India’s top 55 startups fall into this category.


P2P lending providers have been in India since 2014, but until last year there was no regulation around it which created a lot of confusion around the potential growth and security of P2P lending in India which is currently 200cr as per various industry estimates. The opportunity for growth in the Indian P2P lending space is massive, considering that more than half the country’s population lacks access to affordable credit. With the development of advanced technological architectures, P2P lending companies are growing at a greater pace than traditional financial institutions. There are around 12-15 online P2P lending platforms currently operating in the country with a combined loan book value of nearly $25 million. This value is estimated to reach around $4 billion over the next five to six years, said Surendra Kumar Jalan, Founder and CEO, OMLP2P.


“As an alternative to the traditional banking sector’s antiquated approach to lending – driven largely by CIBIL scores as the main underwriting methodology – the technology-driven P2P lending model offers benefits like decentralization, speed, transparency, and efficiency. The biggest reason an increasing number of Indians today prefer online lenders over banks and NBFCs is that the underwriting process is much more transparent, allowing even high-risk borrowers to secure funds in a hassle-free manner with minimum paperwork. Thus, unlike traditional banks, online P2P lending caters to a large number of consumers who do not have a credit history or a CIBIL score, but require access to affordable credit,” said he.


Human to Human interaction for loan application and eligibility check was a tedious task and that's what indicated the need for technology in between. Today, thanks to technology, an applicant can fill out a form remotely from anywhere and within a fraction of a minute can get the eligibility status from various banks and financial institution, and upon applying can get the loan amount disbursed into their bank account quickly.

Aditya Kumar, Founder and CEO, Qbera said, “The whole process of applying for a loan and obtaining it has become extremely simple in recent times, thanks to the emergence of AI, big-data analytics and blockchain. A simple area where these technologies come to use in understanding the credit health of customers through risk-assessment algorithms that make extensive use of big-data analytics and AI tools. As soon as a customer applies for a loan, the information on his/her credit profile is obtained from the bureau almost automatically, and approval is generated. Various aspects of the customers' profile are evaluated through big-data analytics and AI tools almost automatically determine the customer’s eligible loan amount by processing information contained in credit reports. In the present day, AI tools are also being extensively used to create seamless communication channels that promote improved customer engagement. “

Krishnan Vishwanathan, Founder and CEO of Kissht said, “Today, the kind of tech infra available has changed the way lending used to happen in the past. From identity verification to income verification, from address verification to understanding propensity to the future risk of lending, every single detail can be measured without the hassle of manual intervention quickly and accurately. As of today, it's faster, reliable and very secure. We use AI and ML to reduce down document burden for our new customers and help them avail a loan as quickly as possible. Our self-learning decision engine uses AI and ML to quickly understand the existing customers’ credit profiles and then assigns them with the best loan offer at the lowest rate possible.”

Manav Jeet, MD and CEO, Rubique Technologies said, “Rubique has leveraged ML and AI along with big data analytics to build a technology system that matches borrower with the right lender. Rubique integrates credit policy of the lender on its system and uses self-learning algorithms to provide custom offers to borrowers with high approval chances. Also, features like Rubique Confidence score and credit decisions engine built to assess the alternative data sources along with traditional data sources helps to provide real-time decisions and approval by integrating with the bank systems. Leveraging blockchain for Smart KYC solutions also paves in paperless future for customers to deal with multiple banks for different loan requirements.”

Dipesh Karki, CTO, LenDenClub said, “AI, ML, Analytics-based prediction modelling is growing stronger each day in the Indian financial ecosystem thus removing a lot of human errors which happen otherwise. As of now, we are using ML and Analytics for credit evaluation and default prediction. We started using analytical traits of borrowers for recovery management. In the past couple of years, we have reduced our defaults by 50 per cent even though our lending grew by 4 folds just by harnessing the right mix of technologies. We are also exploring various applications of AI and Blockchain in our current system. Our R&D team is working on building a blockchain based application to increase the system's efficiency. If the Indian ecosystem can introduce blockchain efficiently into bringing instant KYC solution, loan tracking, repayment tracking, the system will become more adaptable and remain robust.”

Rajat Gandhi, Founder and CEO, Faircent said, “Faircent has recently opened its API platform to developers. The open API platform will enable new FinTech entrants and offline businesses to leverage its extensive technological expertise to build new digital lending products and to integrate existing solutions into their offerings. This not only helps these businesses to save on the costs of building the entire tech infrastructure up from scratch but also enables them to launch and scale their operations faster. Intermediaries will be able to share the data collected with’s internal developers and partners through it, and can also do the same with third-party service providers such as FinTech companies, banks, NBFCs, and B2B lending firms. This data can then be used to construct value-added services, including mobile payment solutions, analytical dashboards, and more.”

Monish Anand, founder and CEO of Shubh Loans said, “The lending institutions have made the lending process very complicated. We are trying to simplify the process. We have made our app available in vernacular languages, so that people easily understand what’s exactly is their individual credit score, in very simple terms. We also help them understand where do they stand in their capacity and intention to pay loans, what are the areas they are weak on, what are the areas they are strong on, and how they can improve their credit score further. We have a licensing model for NBFCs and affordable housing companies to help them build credit and risk score for their set of customers. We are white-labelling our app and building a layer of a risk-as-a-service platform for them.”


Alternative lending is the second most funded and one of the fastest growing segments in the Indian FinTech space, according to PwC Fintech India Report 2017. More than 225 alternative lending companies have been founded in India as of 2017 and around 10 per cent of India’s top 55 startups fall into this category. The major contributors to the growth of this sector include a large amount of unmet demand for loans from MSMEs, with a gap of roughly $200 billion in credit supply, and a significant under-banked and new-to-bank population. Financial inclusion is also a top priority on the governmental agenda in India. Although with lower operations cost, faster decision making and better-quality risk decisions, this untapped opportunity can translate into greater profitability in the future for the digital lenders, the on-the-ground realities can be extremely challenging. The lenders who are seeking to offer responsible digital lending to the underserved need to be aware of the challenges, risks and design their products accordingly.

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