The time series evolution of credit scores provides a great way to see the effects of removing or adding certain credit characteristics. These credit characteristics can have a significant impact on a person's credit score. This article discusses the effects of dropping certain credit attributes and the impact of high-cost credit scores on credit scores.
Credit scores over time
A critical component of many credit decisioning systems is time series data. This data allows lenders to assess the risk of a borrower by tracking how much a consumer has paid over time. Lenders can gain a greater understanding of borrowers' late payments history by looking at time series data on their credit card balances.
This data is generally good, but it can also show a downward tendency. This is particularly true for consumers who are at lower risk or have lower scores. This may be due to consumers' renewed focus on reducing their spending and paying down debt.
Dropping credit characteristics in groups that are closely related has an impact
One study looked at how removing a set of credit characteristics could affect a credit score. The mean credit score rose by 2.5 points (or about one-fifth) when this group of credit attributes was removed. These changes were greater for those with lower credit scores than for those with higher credit scores.
A drop in one attribute from a credit rating had little impact on the average score for blacks. The average change in black credit scores was 0.1 points. This is due to the high correlation of these attributes in the scoring system. These differences held across the three scorecards.
Addition of other characteristics has an impact
The effects of age on credit scores has been the focus of credit score analysis. Although it is not known how adding additional characteristics to a model can affect its effectiveness, it may be significant. The model for each scorecard was reevaluated with the additional characteristic. It was then compared to the FRB base modeling.
Although the average score did not change, adding race or ethnicity would affect the predictive value. However, dropping these attributes would result in a significant decrease in model predictiveness for other people.
High-cost credit has negative effects
There are several reasons why taking on high-cost debt can negatively affect a credit score. The first is that it sends a signal to lenders about a borrower's poor credit score. Second, high-cost borrowing results in more defaults, which in turn can have negative consequences on the overall financial situation. Third, high-cost credit has a negative effect on the social reputation of the borrower.
High-cost loans can limit the availability of standard sources of financing, and reduce demand. Secondly, high-cost credit causes borrowers to self-select into high-cost credit, a riskier category. While this may alleviate short-term financial concerns, it reduces the availability standard sources for financing.