Despite the evolution and dispersion of the digital technology in India, yet a large section of people are either underbanked or have meager access to the credit system. Though a large number of people have access to the internet and mobile phones but not even half of them have access to formal credit sources. Traditional models of credit scoring have a limited scope in developing economies like India where the person’s having low income and borrowers not having a history of borrowing are not considered by formal credit providers. However, an increase in the digital operations has provided an opportunity to the persons having no credit history or having low income by way of alternative credit scoring.
Alternate Credit Scoring means the use of data from digital platforms and such applications for determining consumer behavior for assessing credit risk. Earlier only the credit bureaus were the only source for the consumer credit information that was used by the lending institutions like banks to lower market risk and bad debts. Alternative form of Credit Scoring indicates the strength of mixing the data from sources like bill payment history, social media usage, etc.
More than 30% of the world’s population and a sizeable portion of the Indian population along with Small and Medium Enterprises (SME) don’t have access to formal financing or other banking services. For such a group of people, centralized credit data is insufficient or unavailable therefore alternative criteria apart from the traditional credit scoring helps the companies to serve the needs of the customers thus providing a way for these people to be introduced to the credit landscape.
From scanning the mobile phone logs to assessing the social behavior, the creditors are using these novel ways to make lending decisions.
The alternative credit scores are not calculated in the way that the traditional credit bureaus calculate. They calculate on the basis of payment for utilities, rent, etc. They are invaluable for several reasons. These include:
The lenders should supplement the traditional scores with alternative credit data as it reduces risk. There is information that you may not find with a traditional hard credit inquiry.
It provides the lenders with a way to evaluate any kind of applicants fairly because in case of the traditional credit scoring applicants having very high scores or very low scores can be assessed easily but applicants who fall somewhere in the middle of the two, traditional scores may not be enough.
It provides you a great way of assessing persons not owning credit cards. If a person having limited credit histories applies for a personal loan the traditional scores may not reflect their creditworthiness accurately.
This method of credit scoring allows more and more borrowers to apply for the loan whether it is a young individual with no credit history or an adult with low traditional credit scores.
The real-time credit assessment aspect of an alternative form of credit scoring helps the creditors not miss out on potential business and it will provide accurate information where the credit score would be based on the current creditworthiness of an applicant instead of his or her past score.
Read, Also: Credit rating bureaus in India: CIBIL and Equifax.
The alternate form of credit scoring models has a unique approach leveraging their data sources and technology to disrupt the industry system. The basic thinking behind it is to reach out to people who are creditworthy but are excluded from the traditional model. Some of the Alternative Credit Scoring models are specified below.
FICO Score XD is FICO’s new alternative model. It considers alternative data sources like the internet and mobile phone bills to allow the borrowers to gain scores who don’t have credit data.
It is a credit scoring model formed by the credit reporting TransUnion with a view to integrate alternative data and help the individuals not having any credit score.
It is an Indian based fintech start-up offering alternative data-based credit scores for borrowers, borrowing for the first time using machine learning and big data analytics. It has helped several lenders to attract borrowers borrowing for the first time. It has further reduced the time of processing loans from few days to a few minutes (30 minutes).
India has 800 million unscored individuals which tell us the fact regarding the enormity of the market size and the lenders are in continuous pursuit to tap such a huge portion of the population.
The main motive of these alternative credit scoring models is to provide access to banking to the unbanked. The lenders are also empowered now to reach out to people who were excluded from the traditional scoring due to low or no credit scores.
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