Have you ever noticed how defensive some people can be when it comes to their favorite or family recipes? Depending on the food and the people involved, certain debates can get pretty passionate in a moment’s notice. Some swear their recipes are the gold standard for things such as chili, barbecue ribs, pies, cakes or any other food where contests are held to crown the best reign supreme. It even goes beyond individuals and spreads to different regions or communities for how things are done best.
Duels between award-worthy recipes are one thing, but what about the person who’s convinced blueberries belong in lasagna?
Financial institutions can sometimes find themselves in a similar position when it comes to statistics and analytics used to fuel their strategies and operations. How much data as well as the types of data used for ratios or calculations can sometimes vary depending on the institution, market, goals or other parameters of certain situations. Some institutions might have slightly different ways of using data effectively, whereas others might miss the boat completely. This can be especially true regarding ratios and other factors involved with decisioning or risk.
Debt-to-income (DTI) is one of the most critical ratios that financial institutions consider when determining the approval or rejection of applicants. DTI is generally part of an institution’s approval policy, and there are limits included as part of the underwriting guidelines when it is not part of the policy.
DTI is the ratio between debt and income. The denominator is usually straightforward, being the monthly or annual income. However, it is very important to have procedures in place to avoid collecting misleading data (for example, gross values vs. net values). The numerator, from a theoretical standpoint, should consider each form of borrower debt. This would include the debt reported in the credit bureau file, such as credit card, mortgage, vehicle and personal loans. Additionally, the theoretical DTI would also consider other recurring expenses that are typically not included in the credit file data. These expenses may include rental obligations, monthly expenses (utilities and telecommunications) and loans that are not captured by the credit file (subprime loans and payday loans).
However, from a practical standpoint, financial institutions typically consider DTI that includes debt obligations reported in the credit bureau file and some application data, which typically only includes data such as rental obligations. The other recurring expenses are generally not captured.
Maximum thresholds for DTI are usually set between 40-50 percent depending on product type and the institution’s policies. A typical threshold for mortgages is usually set to approximately 43 percent to account for qualified mortgage requirements), and a vehicle loan might be set in the neighborhood of 45 percent. In some cases, a maximum DTI of 60 percent can be allowed for applications containing strong compensation factors. Applications that go beyond these values are often declined.
Given the importance for financial institutions to develop effective risk policies and sound risk management strategies, our Achieve team recently released an eBook focusing on finding DTI's optimal definition. It is written based on our industry experience. In the eBook, our team summarizes the main characteristics of the three most common versions of DTI calculations used in the industry. It also goes one step further by testing the actual performance of those different versions in predicting risk. In doing this, indirect lending portfolio data was used.
To learn more about this analysis and its findings, please click the button below to request a copy our complimentary "Identifying an Optimal DTI Definition Through Analytics" eBook.
Photo Credit: liz west