The world we live in is no longer the same, we have stepped into the age of digitization, which is marked by growing reliance on technology to solve issues and find new directions that aim at an overall improvement of life. However, some areas are there which desperately need the digital solutions keep pace with the progress being made. There are people who fall under the category of unbanked and, under-banked and these people end up failing to get any access to credit, because of lack of traditional data which is required for credit risk assessment. However, if this situation is allowed to continue in this manner then it would lead to inequity.
But, the risk factor also remains due to the lack of data regarding their credit history. So, how to achieve a balance in such a situation? The alternative data holds the key here. The willingness to repay the loan is a crucial factor that the traditional data points at, but, in the absence of traditional data sources alternate data takes over and takes a thorough approach in indicating not only the willingness of the borrower but also the ability of that person concerning loan repayment.
More often than not the alternative data sources rely on the AI, ML based systems for dealing with extracted information from various sources. Usually the sources of information for alternate data could be varied and range from mobile transactions to bill payment. These sources allow the digital lenders to get a more holistic view of the borrower’s capability of repaying the amount and hence in doing so, it keeps the risk factor at a minimal level.
The alternate data is the need of the hour as it helps bringing those customers who are new to the field and who do not have any report to back them up and in the process they end up being denied a loan, or, paying penalties. The financial institutes must take advantage of the alternate data sources so, that they can grant credit to this group of people, otherwise it would not be easier for the financial institutes to grow and flourish as an organization, if they only continue to rely on traditional data. The alternate data allows them to open doors to new customers without getting entangled in financial risks.
This has another big advantage as alternative data open doors to the under-banked and unbanked people and thereby helping in financial inclusion. If these sections are able to access loans for personal or, other reasons, it would empower them.
The bureaus need to consider the power of alternate data and while assessing credit risk they must take into account both traditional data as well as alternate data in order to get a more comprehensive view of the potential borrower.
