How are Alternative Data Being Applied by Banks and Digital Lenders?

For a long time, an individual’s credit score was considered as the main key factor that influenced their loan underwriting process. This regulation adversely affected a large population of people who belonged to rural communities or did not have a fixed income source. These people lacked a proper credit history and thus were ineligible to get any credit or loans from financial institutions like banks. The implementation of alternative data for the loan underwriting process helps banks and lenders to provide credit access to these people and helps them to build up a proper credit report.

The introduction of alternative data solutions in the financial sector, especially the lending market, can help banks and other financial institutions to reach out to these people and help them get credit loans easily during an emergency. Thus, governmental agencies, credit bureaus, and financial institutions are monitoring the implementation of new digital technologies like alternative data solutions that help more people to become a part of the growing economy of the country.

Alternative data can help in improving the accuracy of the loan underwriting process

Previously, a person had to provide their credit score, proof of mortgage, and other relevant documents to the bank while applying for a loan. The bank then used to verify the details manually in the loan underwriting process and determines the creditworthiness of the individual. This took a lot of time and often led to the rejection of the loan application if the individual failed to meet the criteria set by the bank.

Nowadays, banks are looking to reach out to a large group of people who lack a proper credit history due to their lack of fixed income sources. As these people do not comply with the traditional parameters set by financial institutions, they can still apply for digital loans. By gaining consent from the customer, the following alternative data is collected by the banks and lenders as alternative data.

● The payment details of utility bills like electricity, gas, water, internet, mobile, etc.

● Your social media activity across various platforms.

● Your e-commerce history and orders.

● And various other data about your online activities.

This collected data is used by the banks and lenders to determine the financial behavior of the individual. For example, if a person pays his bills on time while also purchasing items online at e-commerce platforms, it means that the individual is financially active, although he may not have a long credit history. The data is analyzed by machine learning models and artificial intelligence algorithms to determine the possible financial behavior of the person. If this information is combined with the current credit score of the individual, banks and lenders can determine whether the customer will be a credit risk or a credit-worthy individual shortly.

Challenges faced with the implementation of alternative data

While the usage of alternative data may look ground-breaking, one has to realize that this technology is still underdeveloped. As it is not perfect, banks and lenders can still make errors when determining the creditworthiness of an individual for the underwriting process of digital loans. Plus the individual must also be familiarized with the type of data that they are giving access to the banks and digital lenders during the loan underwriting process. As alternative data can contain the private information of an individual, he or she must be made aware of what and why their data is getting used for before asking for their consent.

These are the steps in which alternative is being implemented in the lending market of our financial sector.