Reasons why banks and lenders are shifting to alternative data solutions
As more people are applying for loans from banks, digital lending platforms and other lending institutions, the loan application, credit underwriting process and loan approval procedure has become too time-taking. To process all the loan applications from their customers, these financial institutions are implementing automated and alternative data solutions that can complete everything more accurately and within a short timeframe.
Since the pandemic, most customers are applying for loans remotely from their homes. Thus, with the help of machine learning models and alternative data solutions, banks, digital lending platforms and other financial institutions can handle all these online loan applications more accurately and swiftly. Such a high speed and accuracy provides a good customer experience. Here are some other reasons that have made alternative data and other solutions so popular.
Checking the creditworthiness of individuals is time-consuming
The criteria of calculating assets and financial capability of the individual has changed a lot. While real estate and land property are still seen as a crucial investment, in the present scenario people are also diversifying their finances through different types of investments, multiple sources of income, and various portfolio choices. Thus, the traditional parameters are not enough in the credit underwriting process.
The implementation of new solutions like alternative data, machine learning models, and automated algorithms have become necessary to determine the creditworthiness of an individual quickly. These automated methods are more accurate and faster in credit risk assessment.
Alternative data helps banks to give loans to people who lack credit history
As the internet has become more accessible to a larger population of our country, more people have started to apply for loans remotely through online methods. Many still lack a positive credit history or a good credit score, which can help them in credit risk assessment. To provide credit to these individuals, banks and other online lending platforms have started using alternative data solutions. This process helps them in the loan approval process as applicants just need to provide various data sets to satisfy the requirements of the alternative data method.
Depending upon the type of loan and lending institution, the alternative data that must be produced by the applicant may vary. Moreover, with the help of alternative data, many people can start their credit history with a good transaction. This will help them in their future loan underwriting processes.
Manual credit underwriting process is not sufficient for the large number of customers
Previously, limited people from semi-urban and rural areas of our country used to apply for loans from banks. It was because most of the local population lacked financial understanding and knowledge regarding banks and loans.
Nowadays, banks have become more transparent and a lot of digital lending platforms have also come up because an increasing number of people have started to apply for credit from these institutions. Processing so many applications, reading such a large amount of data, and providing accurate credit risk assessment reports is no longer possible through only manual work. Thus banks and digital lending platforms use alternative data, automated algorithms, and machine learning models that can handle such large data and then check for the creditworthiness of any individual. These solutions can help them with their workload and increase their efficiency.
From these points, we can see that it is a good choice to implement modern financial solutions like alternative data and machine learning models as it has been beneficial for both lending institutions and loan applicants. Both parties benefit from the faster and more accurate credit underwriting and loan approval process.
