Overview of Alternative Credit Scoring Models

Ashish M. Shaji

16 Jul, 2020

You may have heard cases of loan applicants being rejected due to a lack of credit history data. This is a common sight for loan applicants who get rejected because of low or no credit scores. So what is the alternative to it? Well, they can look at alternative credit scoring models as a solution to it.

What is Alternative Credit Scoring?

Alternative credit scoring is a broad-based credit scoring mechanism. It functions well beyond the parameters used by traditional agencies. For someone who is new to the credit and financing ecosystem, it is of great help. As there is no sufficient centralized data available for new consumers, getting a loan may be a tough task, but new-age alternate credit scoring companies use tangible factors such as digital footprint to determine the creditworthiness of a borrower.  

Why is alternative credit scoring needed?

A sizeable portion of India’s population, along with SMEs (Small and Medium Enterprises), doesn’t have access to formal financing or other such services. For them, there is no centralized data, or the data is insufficient; therefore, alternate credit scoring helps the companies to fulfill the needs of the people in terms of the loan.

The creditors under this method use a variety of ways, such as scanning the mobile phone logs, assessing social behavior, etc. to make lending decisions. The fact that it provides benefits to both lenders, as well as borrowers, is the reason why it is primarily needed.

How does the alternate credit scoring work?

The credit scoring agencies work to assist individuals and small enterprises in getting different forms of credit, such as personal loans, working capital loans, and vehicle loans.

It uses technology to assess factors such as payment history, bank balance, travel size, e-commerce shopping, and spending patterns of the borrower. It uses technology to its full extent and digital footprints such as social media and internet usage, to know whether the applicant should be given the loan. Such a broad perspective regarding the customer profile increases the chances of loan disbursements.

Examples of Alternative Credit Scoring Models

The alternate form of credit scoring models has a unique approach in leveraging their data sources and technology to disrupt the industry system. Its basic objective is to reach out to people who are creditworthy but are rejected from getting a loan.

Some of the Alternate Credit scoring models include the following:

• FICO

FICO has been one of the predominant credit scoring models for many years. FICO’s new alternative model FICO XD was tested in 2015 and was gradually introduced to the lenders with a view to providing loans to individuals with no credit scores. It uses alternative data sources like internet and phone bills to provide users with a score who have not attained any.

• Vantage Score

Vantage score is a major competitor to FICO, and it has been in this business for quite some time now. It was founded in 2006. It may be noted that it can be faster and easier to produce a vantage score than a FICO score. The traditional FICO score calls for six months record (credit history), whereas Vantage Score only requires one or two months. It also uses utility and phone bill payments to determine the creditworthiness of a borrower.

This model has been upgraded, which means that instead of looking just at an individual’s most recent utilization rate, Vantage Score will look at patterns over a period of time to determine a full picture of credit behavior.

• Credit Vision Link

This is another scoring model developed by the credit reporting agency TransUnion with a view to integrate alternative data and cater to the needs of those borrowers who do not have a credit score. It evaluates the present situation of the borrower and also the credit details for the last two years in order to get a comprehensive credit scoring. It has managed to score more than 60 million borrowers who were previously unscorable.

• Cignifi

Cignifi is another alternative credit scoring model. It provides a platform for offering credit and marketing scores for consumers through mobile phone behavior data. Its big data engine enables the mobile network operators and insurance partners to find out costumers eligible for credit cards, loans, insurance, and other banking services. 

The main focus of Cignifi is financial inclusion that employs risk scoring technology to cater to the unbanked population who lack any credit score.

• Credit Vidya

Credit Vidya is an India based fintech start-up that offers alternate data-based credit scores for underwriting borrowers who borrow for the first time using machine learning and big data analytics. It has managed to raise 7 million dollars in funding and employs more than 10000 digital footprints through in house designed APIs. 

This model has helped the lenders to attract first-time borrowers and has reduced the processing time significantly from a few days to a few minutes.

India has more than 800 million unscored persons; hence the market size is vast, and lenders are in need of a service that can help them tap into such a massive proportion of the population. 

What are the advantages of the Alternative Credit Scoring Models?

The advantages of these models are as follows:

• Accessibility to a large customer base

It helps in accessing a large customer base, which is essential to fintech lenders as it may not be easy to compete with big banks. Their ability to use new credit models and providing borrowers will lead to the expansion of the entire market.

• Customer Experience

With these models, the process of credit decision making is automated and allows for a more trouble-free digitally enhanced experience for customers. It raises the utility to numerous borrowers who were earlier required to visit their bank branches for applying and processing their loan applications.

• Improved underwriting process

The alternative data adds a layer of analytics to the existing data, thus gives an understanding to the underwriters. It aids in developing a better credit scoring model.

Conclusion