Credit

How new-age lenders address the need gap with digital credit underwriting methods

What kind of models are being built by new-age lenders?

Access to credit is one of the most significant factors for the survival, growth, and productivity of any business. Many businesses in India do not maintain the requisite financial information imperative for a good credit appraisal and moreover have limited reach to lending institutions due to lack of relevant knowledge. Similarly, from the lending institutions’ perspective, lending to different types of businesses is a highly risky proposition, as every business has its unique set of complexities. This interplay between demand and supply side challenges leads to widening of the credit gap. Furthermore, traditional credit appraisal methods have their own challenges, especially in unprecedented situations such as the current COVID-19 crisis. As physical distancing becomes the new normal, paperless, contactless, digital loans will gain greater significance.

Opportunity taken by new-age lenders

By leveraging cutting-edge digital technologies, data analytics, and proprietary underwriting algorithms, new age lenders can assess vast volumes of data, both conventional and unconventional in nature, of prospective borrowers. Such in-depth access to borrower information allows new-age lending platforms to assess the creditworthiness of a borrower accurately even in the absence of financial records. This enables seamless access to credit and financing opportunities to those who are new to this.

Fintech startups have been at the forefront of digital loans. In the last few years, easy internet access and the rapid adoption of smartphones have altered the way SMEs address their business needs. Manual credit underwriting processes started being replaced by digital underwriting due to the availability of rich, alternate data. Innovative, disruptive technologies have led to greater accuracy in credit risk models. The Government of India and the RBI have also undertaken several initiatives for digital India. The financial services industry is swiftly evolving and moving from the traditional ‘one size fits all’ approach to a more ‘tailor-made’ approach.

Alternate Credit Scoring

Alternate Credit Scoring is a popular model which goes beyond traditional parameters employed by the Bureau and helps in accessing a potential consumer’s digital footprint to determine creditworthiness. Many digital lending institutions have been using some form of the Alternate Scoring model to take credit decisions effectively. This model uses technology to assess various factors such as online shopping, bank balance, payment history of utility bills, travel history, and spending patterns of the loan seeker. For instance, an amalgamation of online selling platforms and digital lenders to provide instant finance at the point of sale helps all participating entities – the seller, aggregator, buyer and financier. This application is made possible by building sophisticated credit underwriting models based on dynamic platform-specific data and evaluation of buyer behaviour such as purchase pattern, average ticket size of spend, frequency of orders etc. The advent of digital banking and GST has also helped in building smart credit underwriting models. An interplay between these two sources and verification of information from external organizations leads to a high trust and reliability on the underlying models.

The biggest beneficiaries of the alternate credit scoring method are consumers who are new to credit. First time borrowers are now able to avail loans irrespective of lack of scoring data on traditional channels. Lenders too can utilize alternate credit scoring in order to boost their penetration in previously unexplored geographies such as semi-urban and rural areas while keeping risk low. The basis remains the same for alternate credit scoring methods as well – ability, intent, and stability of the customer in repayment of the loans advanced.

Enhanced creditworthiness, unique customer experience, boost to the credit underwriting process, customized customer solutions, realtime user data and assessment, elimination of human bias are some of the major benefits of the Alternate Scoring model.

Ecosystem based lending

Another innovative alternative fintech lending solution is that of ecosystem-based lending. Businesses are invariably keyed into bigger supply chains, whether as suppliers or customers. Digital lending platforms are now collaborating with large corporate organizations to use the internal ecosystem of the organization that exists within these supply chains. Doing so not only enables them to more accurately underwrite borrowers from the supply chain cycle but also deliver highly-customized and quick financing solutions at their point of need. Here is a glimpse of the functionality. As the lender is part of the ecosystem, the lender can use a cash flow escrow as a collections mechanism while it also serves as an underwriting tool. This works in tandem with the buyer of the product or service, as the money used for purchase is directly credited into the escrow managed by the lender. This construct enhances exposure with calculated risk for the lender while facilitating a seamless experience for the buyer and seller.

Faster credit helps these businesses to grow and be dynamic, as these ecosystem-based loans can be availed during the financial transaction between the engaged parties within the supply chain, with the transaction being the guarantee as well. This form of financing fosters growth at unit level for the businesses and for the supply chains, stimulating economic activity at a larger scale.

Extensive support from the Government and regulators in India has boosted the digital journey of the Indian Economy. This digital transformation is likely to continue with the adoption of open banking, AI-driven data intelligence and distributed ledger technology. All this has provided digital lenders the opportunity to serve borrowers with quick and timely credit.

DQINDIA Online | dqindia

Mudit Agarwal, Head – Credit, Capital Float

 

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