Paperless lending decoded: How exactly it happens?

Today, if you need a loan, all you need to do is log onto a digital lending platform, do minimal paperwork, and your application gets instantly approved (or rejected). It only takes a couple of hours or days from there for the loan amount to finally get disbursed into your account. All of that without needing you to leave the comfort of your home!

Now, if only you could remember the hassles involved while availing loans during the years gone by– the exhaustive paperwork, circling multiple government departments for documents, personal interview with the loan officer, needless red-tapism, and whatnot – and even then, ultimately getting your loan application rejected, the feat that online lending platforms have been able to achieve simply looks remarkable. When you further bring the fact into the picture that these online platforms, despite being time-effective, are also cost-efficient and have been able to keep their NPAs (Non-Performing Assets) at historic lows vis-à-vis the broader industry, a curious fascination develops around how are these platforms able to extend the swift, paperless lending experience with such an intense precision?

The answer lies in wide-ranging technologies and a cutting-edge approach that these digital lending platforms leverage.

Harbinger of a New Era: How Digital Lending Platforms are taking Lending to the Future?

The most basic difference that digital lending platforms have is in the approach that they have adopted. They do not rely on collaterals to back a loan, neither do they demand exorbitant interest rates in order to counter higher cost of credit. All they rely on is their proprietary technology and are extending its merits to low-to-medium income groups as well as MSMEs – or the bulging bottom of pyramid that often remains bereft of credit.

To help understand better, here’s a stepwise insight into what moves behind the curtains when anyone avails a loan via a digital lending platform:

-Time is a Precious Commodity: As soon as someone presses the ‘Submit’ button on the screen, the digital lending platforms, without wasting a moment, source all the relevant data via multiple data repositories. This includes data from applicable government sources (via PAN Card, Aadhaar Card, etc.) and other alternative data sources. All of the submitted documents, which are in an image format when submitted, are instantly converted into readable digital format using a range of technologies such as Intelligent Word Recognition (IWR), Intelligent Character Recognition (ICR), and Optical Character Recognition (OCR). This approach saves considerable time and gives more data points to the backend system of digital lenders.

-In-Depth Analysis: This data is used to analyze the creditworthiness of a loan-seeking candidate based on various parameters established by the digital lenders. They examine the data over hundreds of parameters ranging from the region of loan origination (given different NPA ratios across different geographical regions) to the social footprint of a candidate (including the government services that he or she avails to confirm legitimacy) to come up with a prudential lending decision. They also check credit history, if available, to check if there has been a delinquency earlier.

-The Tech Behind: Some of the technologies used by digital lenders for their analysis include:

Big Data: Using sophisticated technologies such as Big Data, digital lending platforms are able to establish and find out correlations that are directly or indirectly related to a loan-seeking candidate. For instance, say the applicant is associated with a particular market vertical that is in the midst of turmoil. It is highly likely that its repercussions will eventually affect the loan applicant, thereby affecting his or her creditworthiness. These takeaways are mined through voluminous data flowing into the digital lending platforms via their data sources as well as applicants.

Artificial Intelligence: Such insights are taken off to another level by using Machine Learning, a subset of the AI technology. With Machine Learning, digital lenders are able to draw useful insights automatically and create use cases without any manual programming. The technology specifically focuses on key parameters that could either positively or negatively impact loan applications and dynamically changes its approach as per the market conditions. If it was a loan officer, it would be the one that constantly learns from each and every loan application that it approves and has no predispositions.

-Disbursement: Finally, since this approach is still relatively novel, all findings are checked at least once by a manual resource to avoid errors. This is the only process that substantially adds to the overall Turnaround Time (TAT). Once the findings are reviewed, the amount is finally disbursed to the beneficiary.

The cutting-edge approach enables digital lenders to process higher number of applications and experience economies of scale. This, alongside almost negligible errors and omissions as well as relatively much lower NPAs, translates into lower cost of credit – whose benefits are immediately transferred to consumers.

So, when there will be a level playing field between digital lenders and their traditional counterparts (banks) on the regulatory front, it is beyond doubt that Digital Lenders will be able to extend even lower interest rates to borrowers while experiencing negligible bad loans. Let us eagerly wait till then.

-by Manish khera, founder and CEO for Happy.