Digital finance companies such as online lenders also use alternative data sources to calculate the creditworthiness of borrowers.
[5] Application scores tend to be dominated by credit bureau data which typically amounts to over 80% of the predictive power compared to 60% in the late 1980s[5] for UK scorecards.
Indeed, there has been an increasing trend to minimize applicant or non-verifiable variables from scorecards, resulting in the reliance on credit bureau data.
A customer with a high credit score shows that they are creditworthy and banks will have no problem giving them a loan.
If a customer has a low credit score then banks would be hesitant to give out a loan and if they do it might be with a higher interest rate.
This model can be used to predict the probability of default for new clients using the same observation characteristics (e.g. age, income, house owner).
The primary differences involve the assumptions required about the explanatory variables and the ability to model continuous versus binary outcomes.
Despite much research from academics and industry, no single technique has been proven superior for predicting default in all circumstances.
A typical mistaken belief about credit scoring is that the only trait that matters is whether you have actually made payments on time as well as satisfied your monetary obligations in a prompt way.
This is where credit scorecards come into play which helps banks and financial situations minimize risk and less the delinquency rate.
Many banks prefer this category because if a customer is denied a loan then a reason for denial needs to be given and that can be easily interpreted from these models.
This type of scorecard helps the business to make automated, accurate, and consistent decisions on whether to approve, review or decline an applicant.
Here it is important to consider that customers' circumstances may also change over time and to maintain a good relationship with their clients, the bank would need to offer appropriate support.
It is important for the organization to identify and prioritize the accounts that need collections because it plays a vital role in controlling bad debt.
These days all the file sourcing or paperwork required needs to be submitted online on the bank's web portal.