The flourishing digital lending segment in India is giving rise to a new kind of challenge on sourcing credit score data.

In order to solve this problem, Fintech companies are now using Artificial Intelligence (AI) and Machine Learning (ML) to create alternate lending data score for more than 80 per cent of the Indian population who have no credit scores. ML captures the relevant information of the customer ranging from where the person lives, whether he is an iPhone user or Android user, restaurants they visit, their social media interactions etc. in order to assess their credit score.

Most of the Fintech tech companies are also relying on live data. For example, if the person says he is working in a particular company in a particular location but his phone location details decipher otherwise, then the application gets rejected immediately. AI and ML can also tell if the person is lying or has a genuine requirement and what his repayment capacity is. Fintech companies have started using the term –“Social Loan Quotient” for every customer and this quotient can help customers upgrade to bigger loans in the future. For example, a Mumbai based Fintech Company called Cashe heavily relies on Social Loan Quotient for disbursing loans.

This credit data could help the credit officers at banks who make lending decisions, to make more accurate predictions about loan performance. This could, in turn, help improve collection rates and profitability for institutions and make credit more affordable for lower-risk customers.

Another aspect to credit assessment in digital lending is the usage of alternate data-based programs to disburse loans to customers. Many start-ups are using these analytics programs in cases where there is lack of credit details availability.  These start-ups tie up with larger NBFCs to provide them with the required data that NBFCs and banks are not collecting currently.

Recently, Shriram City Union Finance has tied up with CreditMantri, (a credit marketplace to know a customer’s credit quotient), to build a digital program called Score Builder. The score-builder program has helped see seven times growth in the last 12 months, and has enabled more than 95 per cent of borrowers with no prior credit score to build a solid credit profile. Using this program, Shriram City Union disburses loans to its customers and based on their loan repayment pattern, increases their credit score for future. Hence, through Artificial Intelligence, a no/low credit score customer can be eligible for a loan without having to face any rejection.

Lastly, to put some numbers in perspective, research done by Boston Consultancy Group suggests that using AI to assess credit score, digital lending would grow 10-15 times to Rupees more than 10 lakh crore by 2023.

AI will be the way forward to credit scoring and boon to millions who today don’t have a formal score.

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