Credit-score cutoffs are changing in today's mortgage lending market. This article explains why credit scores don't remain static and need to be revisited against changing market backdrops.
Today, credit scores are often used synonymously as an absolute statement of consumer credit risk. Or credit scores are viewed as measurement of borrowing strength and mistakenly thought to include assets, income and/or net worth in the calculation. [paragraph] Consumers are regularly advised that their three-digit credit score is important to their financial well being. It is not uncommon to hear people boast of excellent credit scores--or anxiously ask for help when their scores are low. [paragraph] With the complexity and variety of scoring models in the market, an opportunity exists to further educate consumers on credit scores as well as better inform the entire spectrum of credit-score users. [paragraph] Indeed, one common miscalculation is attempting to describe whether a particular credit-score value is good or bad without the context of how to interpret the number. This can be confusing at best--and at worst can create either unexpected and increased risk exposure, or lost opportunities for both lenders and consumers. H This article discusses how credit scoring works, and redefines both a new way to measure risk and how risk shifts over time.
All users of credit scores--mortgage lenders, servicers and investors in mortgage-backed securities (MBS)--must be hyper-aware of these trends in order to fully optimize their portfolios and prevent risk from unknowingly impacting loss ratios.
The relationship between scores and consumer credit risk
In the simplest of terms, lenders use credit scores in three primary areas of their businesses: 1) as part of the process for evaluating credit applications; 2) identifying potential new customers who meet their approval profiles, thereby creating a list of consumers to receive credit offers (often called account acquisition strategies); and 3) monitoring credit health among current credit customers (often called account management).
The common bond for all three scenarios is the overarching business strategy employed by the lender or servicer.
Some lenders choose to extend credit only to those with the best credit record. Other lenders or servicers may exclusively target so-called subprime consumers, while others offer credit to the vast majority of consumers between those two extremes. Institutional investors use credit scores in their risk and pricing models as part of the loan-level data used to evaluate residential mortgage-backed securities (RMBS).
The credit score is a numeric interpretation of a consumer's risk level relative to the risk of other consumers in the same population. In other words, it is the likelihood that the consumer will allow one debt to become 90 days or more delinquent, also known as probability of default (PD).
For example, if a credit score of 700 represents a PD of 5 percent, then the consumer has a 5 percent chance of becoming 90 days or more late on an account over a given time period (typically two years).
The relationship between any given score and PD is determined by apportioning the total risk for the entire population among each consumer in the population according to his or her credit-management behavior. Consumers with good credit-management behavior have a low probability of default and a high credit score, and vice versa.
It's important to note that the actual PD value at a specific score can vary based on a number of factors:
* the population being evaluated;
* the product and lender mix;
* the type of decision being made (acquisition versus account management) and
* the time period when the consumer's score was calculated.
For example, assume a population of just two consumers. One consumer has extremely strong credit-management skills and is therefore high credit quality. The other consumer has very poor credit-management skills and is of low credit quality.