How Digital Lending Platforms Use Alternative Credit Scoring Models?

A silent transformation is taking place in India in the lending arena. CIBIL scores have been a major criterion used to evaluate the creditworthiness of a borrower by traditional banks and non-banking financial companies. However, to millions of Indians, particularly gig workers, freelancers, students, and those with no credit history (retired individuals, wage earners), having a poor or zero CIBIL score has been a stumbling block to getting financial aid.

In coming digital lending platforms. These platforms are driven by fintech innovation, AI and big data, rather more like the traditional age-old credit assessment technique. They are launching alternative credit scoring models – which provide a more inclusive and accurate view of the financial behavior of an individual even without a good credit history.

So now, let us see how the new-age platforms are providing borrowing options to the audience that was otherwise locked out.

• What Are Alternative Credit Scoring Models? 

Another such credit scoring model refers to any system that takes into consideration the creditworthiness of a borrower on something other than their past loans or repayments alone. With the new DSA agent, the borrowers can now get in touch with agents who can show multiple options to the clients. 

It looks past traditional credit scores such as CIBIL, Experian, or Equifax and instead uses a wider list of factors that represent financial behavior, online behavior, and social signalizing.

These types of models are of great use in the country of India, which has well above 300 million adults who are both underbanked or new-to-credit. Traditional scores are low or unavailable to them, hence, these people find it harder to obtain loan approval via the conventional ways.

Other models seek to bridge this gap and provide statistically based insights by which lenders can analyze risk more comprehensively.

• Types of Data Used in Alternative Credit Assessment 

Digital lenders will take all possible types of data to create a borrower profile. These are some of the commonly used data types:

• History of transactions at the bank: Payments on Weekly/monthly payments, withholdings, savings behavior, bounced transactions
• Mobile call data: The pattern of calls, mobile bill payment, recharge behavior data
• Utility bills: Payments on electric, gas, and phone bills on time
• E-commerce behavior: History of purchase, use of digital wallet, payments through EMI
• Working conditions: Reliability of employment, predictability of salary, employer record
• Social media activity: LinkedIn, Facebook (only with the agreement)

Others even take into account location, metadata of smartphones, and browsing history (anon. with consent) in an attempt to gauge danger.

The indicators are run on AI/ML algorithms, and make decisions regarding the eligibility of loans in near real-time, and even in the case of borrowers that have no credit bureau presence.

• How Fintech Platforms Evaluate Borrowers Using These Models 

Products that have started using such credit scores early include products like CASHe, KreditBee, Slice, LazyPay, and PaySense. Even the personal loan agent are there who can help the clients with the alternative credit rating process. This is a simple outline of their mode of operation:

• Digital KYC & onboarding: the borrower uploads the basic documentation of identity and income through the application.
• Consent-based data collection at the data level (app level): A phone metadata, SMS information, or transaction alert would be collected by the platform to estimate the trends of spending and income.
• Machine Learning Risk Assessment: AI-powered algorithms search data to detect such indicators as the regularity of payment of salary, UPI payments, paying habits (e.g., utility bills), etc.
• Instant scoring: A stream of digital scores is produced, sometimes referred to as a behavioral score or AI credit rank.
• The generation of offer of loans: Depending on this rating, the loan amount, tenure and the interest rate are determined.

The entire procedure can take as short as 10 minutes, which revolutionizes the process of lending among borrowers.

• Advantages Over Traditional Credit Scoring Systems

Inclusivity:

Alternative lenders give non-credit borrowers an opportunity to take a short-term loan and start their credit record.

Speed and convenience:

It is a lot quicker than the usual banking approvals since verifications and scores are automated. Payments tend to be done in hours.

Real-Time Evaluation:

Rather than basing their credit decisions on the 6 12-month-old report, online lenders will evaluate data in real-time, such as monthly salary credit or spending spent in e-commerce.

Behaviour-Focused:

Unlike other scores that charge the borrower with previous mistakes these alternative scores look at the current financial activities and provide second chances to the ones who want to rectify.

Alternative credit scoring does not mainly act as a backup; it is a recreation of risk scoring- enabled by data, transparency, and real-time intelligence. This can be seen as the hope, access, and opportunity to millions of Indian borrowers outside the formal system.