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Future-Proofing Loans: The Crucial Role Of Data Analytics In India’s Lending Revolution

Future-Proofing Loans: The Crucial Role Of Data Analytics In India's Lending Revolution
SUMMARY

Pre-underwriting is the preliminary assessment of the borrower to determine an applicant’s creditworthiness

The process is generally done during user onboarding, as opposed to underwriting, where (a more thorough) assessment is done after KYC

A more definitive assessment of creditworthiness, the pre-approval stage sees lenders perform a more thorough check of the applicants’ financials

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Amidst the recent buzz about RBI increasing the risk weights for unsecured loans, one simple fact is hard to ignore. It’s that lending—especially through digital channels—is growing at a rate that’s hard to keep track of. The rise of advanced analytics fuels this along with automated workflows, making it easier for customers and lenders to avail and disburse credit in almost real-time. 

A FACE-equifax report on fintech lending trends reported that Fintechs disbursed loans worth INR 92,267 Cr in the year ended March 2023, a 21% year-on-year increase. The number of loans grew by 49% year-on-year from 47.7 Mn to 71 Mn. At the heart of this tech-propelled growth is pre-underwriting backed by data analytics. 

What Is Pre-underwriting?

Pre-underwriting is the preliminary assessment of the borrower to determine an applicant’s creditworthiness. The process is generally done during user onboarding, as opposed to underwriting, where (a more thorough) assessment is done after KYC to draw the final loan terms. 

Pre-underwriting isn’t new to lenders. However, with the rise of embedded credit in various apps and the proliferation of alternate data, pre-underwriting or pre-qualification has become the differentiator between good lenders and great ones. 

How Does Pre-Underwriting Work Today?

Pre-underwriting in digital lending involves two stages:

Pre-qualification: Data-driven pre-underwriting starts with pre-qualification of potential borrowers. Lenders use readily available data from their database to reach out to potential borrowers across channels like cold calls and SMS. 

Alternatively, applicants can be pre-qualified when submitting their basic details while exploring a loan product. 

The data received at this stage contains essential information, typically furnished by the applicant. They include personal identifiers and estimates of income and obligations.

Pre-approval: A more definitive assessment of creditworthiness, the pre-approval stage sees lenders perform a more thorough check of the applicants’ financials. The process involves checking borrowers’ bank statements, determining their financial prudence using consent-driven device data, and checking their credit history through soft bureau checks. 

It’s important to note that digital pre-underwriting today takes mere seconds to minutes.   

How Has Pre-Underwriting Transformed The Lending Landscape?

Traditionally, loan applications were ridden with paperwork, making the experience time-consuming and cumbersome. But lenders today can disburse loans in minutes to days (depending on the type of credit product). And this is all thanks to advancements in data analytics and AI. 

Here’s how data analytics-based pre-underwriting has shaped the progress of India’s lending landscape:

Customer-friendly onboarding: The adoption of data analytics has made loan products largely paper-free. Moreover, the optimum use of the data furnished at each pre-underwriting stage has cut down onboarding redundancies. This has led to low-documentation onboarding and faster application processing at the back end. 

Accurate assessment: Soft bureau pulls, bank statement analysis and alternate data give lenders a 360-degree view of the borrowers’ financials, leading to more precise lending decisions. Pre-underwriting accuracy also helps lenders catch fraud from the get-go.

Faster disbursals: Although pre-underwriting involves several assessment steps at the back end, the process itself only takes minutes. This means shorter application-to-disbursal cycles. 

Precise customer segmentation: As digital pre-underwriting involves accurate data from several sources, lenders can segment their customers into precise borrower cohorts. This means applicants are offered products that best suit their financial needs, enabling better conversion. 

Efficient cross-sell: Lenders can leverage the borrower data to offer other products that may suit their needs. For example, lenders can assess borrowers’ repayment discipline on existing credit and offer pre-approved products that can step up disbursals or credit product maturity.   

The fuel behind India’s digital credit rocketship is advanced analytics. With the proliferation of smarter modelling and workflows, lenders are set to usher in a new wave of dynamic products that work for the borrower, in a tailored and seamless manner.

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