From Willingness to Ability: Why Consumer Affordability Is the New Pillar of Responsible Lending

Highlights: 

• Relying solely on traditional credit scores can mask significant differences in a consumer's financial capacity, potentially leading to missed lending opportunities or exposing a portfolio to hidden risk.
• Equifax's Consumer Affordability View leverages AI to combine traditional and trended credit data, providing a forward-looking estimate of how much additional debt a consumer can responsibly manage, which could offer a KS lift of up to 4.5% in delinquency prediction.

For decades, the traditional credit score has been the North Star of the lending industry. It is a reliable, time-tested measure of historic payment behaviors. But as the financial landscape becomes increasingly complex, lenders are realizing that historic payment behaviors and income are  only half of the equation. The other half—and arguably the more critical one in today’s economy—is their ability and capacity to pay.

To truly practice responsible lending, institutions must add greater dimension to their practices in assessing  consumer's past behavior and gain a clearer view of their predicted future financial capacity.

However, determining a consumer's forecasted ability to manage new debt can be a complex task that traditional credit modeling solutions alone may not solve. Every lender aims to empower qualified borrowers while ensuring they do not extend more credit than a consumer can responsibly manage to repay.

The Limitations of Traditional Credit Data Alone: Bridging the Information Gap

Every lender shares a common goal: extending enough credit to help consumers reach their financial milestones without overextending them, creating damage to both the consumer and the lender portfolio. But, looking at traditional credit scores by themselves may mask significant differences in a consumer’s financial reality, leaving lenders exposing their portfolio to more risk than might be visible via a single data point.

Relying solely on retrospective, “point-in-time” debt-to-income data or traditional credit scores could lead to missed opportunities and hidden risk. When two consumers present identical traditional credit scores, they may appear to have the same risk profile at first glance. However, their actual financial capacity can be drastically different.

Lenders may inadvertently decline a qualified borrower or, conversely, approve a loan that puts a consumer at risk of delinquency.

To bridge this gap, Equifax has introduced Consumer Affordability View, a unique solution designed to estimate how much additional debt a consumer can responsibly manage over the next 24 months.

The difference lies in the synthesis of data. By combining traditional credit data with trended credit data with the Equifax Amplify AI™ engine, lenders can now access estimated additional debt a consumer can manage for the next 24 months.

Imagine two auto loan applicants, Jack and Jill. Both present a credit score of 660, so one may think they carry the same risk profile. However, when a lender layers on the Consumer Affordability Score, the "mirror image" shatters:

• Jill shows a monthly predicted capacity of $1,550, signaling that a $750 auto loan is highly sustainable.

• Jack shows a monthly predicted capacity of only $225, signaling that the same $750 payment could lead to financial strain.

By integrating an AI-driven capacity and affordability model, organizations can move beyond single dimension data points to more robust, responsible consumer payment estimates. This approach allows for:

• More Precise Prospecting: Laser-focus pre-screen campaigns on candidates with the highest estimated capacity for compelling offers.

• Right-Sized Origination: Level up decisioning by automating the review of files that previously required manual oversight.

• Proactive Account Management: Segment portfolios to uncover hidden pockets of risk and opportunity while expanding access to credit.

This isn't just about avoiding "bad" loans; it’s about lending responsibly.

Measuring The Impact: Quantifying the Influence on Decisioning

Integrating affordability metrics into existing models provides a measurable "Information Gain" for AI-driven underwriting:

• Predictive Power: Adding Consumer Affordability View to traditional risk scores can offer a KS lift of up to 4.5% when predicting delinquency.

• Versatility: The tool provides distinct values for installment trades (monthly capacity) and revolving trades (maximum sustainable balance), making it adverse-actionable and FCRA-compliant.

The Path Forward

In an era where "responsible lending" is more than just a buzzword, the data is clear: having a multidimensional view of the consumer is essential. By layering predictive capacity on to traditional risk models, lenders can move closer to a future where every financial decision is backed by a clear understanding of what is truly sustainable. 

Source: 

Equifax, Consumer Affordability View Infographic