Harnessing data-driven strategies for a deeper understanding of … – BAI Banking Strategies

Today’s dynamic economic climate is characterized by rising inflation, elevated interest rates and shifting employment patterns, and bank lenders are challenged to expand their lending portfolios while mitigating risks associated with loan affordability.  

As interest rates continue to rise, every dollar of income becomes crucial in calculating loan affordability. For instance, a borrower who purchased a $300,000 home in 2021 at a 3.75% interest rate would pay roughly $1,400 monthly. Fast forward to 2023, and the same house, financed at a 7% interest rate, would require a monthly payment of approximately $2,000. This scenario doesn’t account for the likelihood of higher home prices in 2023, which can also increase borrowers’ down payment requirements. 

Navigating the complex landscape of loan affordability

Loan affordability has become vital to preserving homeownership and promoting financial well-being. Successfully assessing loan affordability requires the debt-to-income (DTI) ratio, a metric that compares a borrower’s total debt to their gross income (pre-tax). While the maximum DTI ratio for mortgage qualification can be up to 50%, depending on qualifying factors, many financial institutions opt for a more conservative range, typically between 35% and 43%.  

Bankers must embrace a data-driven approach to income and employment verification to determine loan affordability. They will have a clearer understanding of borrowers’ financial health and enhance their risk assessment capabilities. 

Shifting sands of debt-to-income ratio 

Amidst shifts in inflation, the job market, and the overall economic landscape, calculating the DTI ratio has become less straightforward. Wage and inflation trends fluctuate, and it can be difficult to predict if a borrower’s DTI will remain the same from the start of the application process to closing. 

A study from the CFPB indicates that close to 37% of households lack the financial cushion to cover expenses for more than a month, even when tapping into savings, loans or assets. These circumstances can further complicate the DTI ratio calculation for lenders. 

Despite a 1% increase in wages and salaries from April to June of this year, the Federal Reserve’s multiple interest rate hikes aimed at stabilizing the economy have created additional challenges for consumers regarding affordability.  

Data from the Bureau of Economic Analysis reveals that 2023 began with fluctuations in consumer spending. Americans saved their income in May at the same rate as in January 2022, signaling consumers’ growing sense of caution. 

These data points further depict how consumer spending habits are unpredictable, which may impact loan affordability. 

Income as the driving force behind affordability 

Income data is the foundation for calculating the DTI ratio for loan applicants. Financial institutions use a variety of strategies to assess an applicant’s financial capacity, ranging from traditional methods like credit score to alternative sources like bank transaction data or consumer-permissioned data from third-party platforms and aggregators, or documents provided by consumers (e.g., pay stubs or W-2s). 

While these approaches are diverse, they also come with risks. When linked to bank transaction data, many third-party aggregators continue to access consumer data until the consumer manually disconnects the third party from their account. The storage and security of financial data could represent potential risks for lenders. Lenders should consider utilizing automated income and employment verification data from trusted sources to help determine loan terms while minimizing risk. 

In the past, lenders may have relied solely on base pay to qualify borrowers. However, affordability concerns have led some individuals to use additional income sources, such as bonuses and commissions, to qualify for loans. This underscores the importance of verifying all sources of a borrower’s income to avoid surprises during the underwriting process. 

Trusted data means better opportunities for consumers 

Lenders who embrace a data-driven approach to assess DTI ratios may discover more favorable credit and loan outcomes for borrowers. Homebuyer assistance programs, for example, have emerged as a promising path to homeownership for many aspiring homeowners. According to research from Down Payment Resource, 33% of declined mortgage applications were eligible for homebuyer assistance but were rejected due to insufficient funds or disqualifying DTI ratios. 

These potential customers highlight an opportunity for lenders to increase their loan volumes while supporting more borrowers on their path to homeownership. Access to readily available income data streamlines the identification of these prospects. 

Paving the way for the next generation of homebuyers 

A timely example of an often-overlooked segment of potential borrowers is Gen Z as the next generation of homebuyers. Their financial behaviors and unique attributes demand lenders’ understanding. According to Rocket Homes, 86.2% of 18-to-24-year-olds aspire to homeownership, with 45% aiming to own a home within the next five years. Challenges for this group include inadequate down payment funds, house price affordability, credit sufficiency and student loan debt. Automated income and employment verifications can help lenders better assess a Gen Z applicant’s ability to pay. 

In the ever-evolving economic environment of 2023, lenders require robust tools to expand their lending opportunities responsibly. Income-driven loan affordability determinations, underpinned by a nuanced understanding of the DTI ratio, empower lenders to navigate challenges and guide borrowers toward brighter financial futures. By embracing data-driven strategies, lenders can thrive in a volatile market and ensure that loan affordability remains at the forefront of their lending decisions. 

Tracy Huber is director of product management, mortgage service at Equifax Workforce Solutions.  

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