Emmaline Aliff sits down with Cox Automotive Chief Economist Jeremy Robb to unpack the forces reshaping today’s auto market—from affordability pressures and credit expansion to the growing wave of used EVs. As consumers navigate rising costs and lenders adapt to shifting risk, the conversation explores what’s really driving demand—and what dealers and lenders should watch next.

In this episode:

What is driving the current auto market in 2026?

The auto market is being shaped by a mix of macroeconomic forces, including inflation, interest rates, tariffs, and consumer affordability challenges. At the same time, credit availability is expanding, creating a complex environment where demand persists despite financial pressure.

What is a K-shaped economy and how does it impact auto buyers?

A K-shaped economy means higher-income consumers are thriving while lower-income consumers face increasing financial strain. In the auto market, this results in strong demand for high-end vehicles while affordability challenges push many buyers toward used cars—or out of the market entirely.

Why is affordability such a major issue in the auto industry right now?

Affordability is being impacted by rising vehicle prices, higher interest rates, increased insurance costs, and ongoing inflation. These combined factors are making it harder for many consumers to purchase or finance a vehicle.

How is credit availability increasing despite consumer financial pressure?

Lenders are expanding access by offering longer loan terms, financing lower down payments, and taking on more subprime risk. While this increases access to credit, it can also introduce additional long-term financial strain for consumers.

What should dealers and lenders watch for in the second half of the year?

Key indicators include interest rate changes, inflation trends, mortgage activity, and continued consumer demand. Lower rates and improved economic conditions could unlock stronger sales.

The mortgage industry is debating whether to move away from the long-standing TriMerge credit reporting standard. Wendy Hannah-Olson of Equifax speaks with mathematician and behavioral modeling researcher Joni Baker at Andrew Davidson & Company about new research analyzing credit score differences across the three credit bureaus. Their discussion reveals how shifting to single or bi-merge credit reports could affect loan qualification, mortgage pricing, and risk—potentially costing consumers thousands of dollars and reshaping how lenders evaluate credit.

In this episode:

Why are lenders debating moving away from the TriMerge credit report?

Some policymakers and industry groups are exploring whether using a single credit report or a bi-merge report could reduce costs and streamline the mortgage process. However, new research suggests that using fewer credit reports may introduce pricing uncertainty, increase risk, and lead to inconsistent loan qualification outcomes.

How different can credit scores be between the three credit bureaus?

According to a recent study from Andrew Davidson & Company, credit scores across bureaus can differ significantly. In the data analyzed, 27% of consumers had score differences of at least 10 points between bureaus, 14% had differences of 20 points or more, and nearly 1 in 10 had differences of 30 points or more.

How could moving away from TriMerge affect mortgage pricing?

If lenders rely on a single credit score instead of the TriMerge median, borrowers could move between pricing tiers more frequently. In some scenarios, a change of just 10–20 credit score points could alter loan pricing, potentially affecting mortgage costs by $3,000 to $5,000 or more over the life of a loan.

Ashley Sellers of Equifax sits down with Jordan Sullivan, Director of Retail Lending at CSL Financial, to explore how modern credit scoring is reshaping mortgage lending. As one of the first lenders to adopt VantageScore for underwriting, CSL shares real-world results, from higher approval rates and lower costs to stronger portfolio performance. The conversation dives into affordability, trended credit data, thin-file borrowers, and why delaying adoption of new credit models may be a competitive disadvantage for lenders navigating today’s evolving credit ecosystem.

Economist Justin Begley of Moody’s Analytics provides our economic update.

In this episode:

Why did CSL Financial adopt VantageScore for underwriting?

CSL Financial adopted VantageScore after internal testing showed it was a stronger predictor of credit risk than legacy models. The lender found it better aligned with borrower behavior and more effective for evaluating thin and non-traditional credit files.

How does VantageScore help lenders approve more borrowers?

VantageScore uses trended credit data to evaluate whether a borrower’s financial behavior is improving or declining over time. This allows lenders to make more informed decisions than snapshot-based models, helping qualified borrowers who may have been overlooked receive approval.

What results has CSL Financial seen using VantageScore?

Since adopting VantageScore, CSL Financial has increased loan pull-through rates from approximately 8% to nearly 20%, while maintaining stable delinquency levels. The lender has also reduced credit-related costs and improved portfolio performance.

 Who benefits most from VantageScore-based underwriting?

Borrowers with thin credit files, limited credit history, or past credit challenges benefit most. This includes younger borrowers building credit and older consumers who have paid off debt and have limited active tradelines.

Why is delaying VantageScore adoption a competitive disadvantage?

Lenders who delay adoption risk higher costs, lower approval rates, and less accurate risk pricing. Early adopters like CSL Financial report both operational savings and stronger credit outcomes, making modern scoring models a competitive advantage.

Jennifer Henry of Equifax sits down with Christina Randolph of Freddie Mac to discuss how lenders can drive efficiency, improve data quality, and build resilience through digitization and automation. From reducing origination costs to leveraging tools like Loan Product Advisor, AIM, and verified income data, the conversation offers practical insights to help lenders prepare for the next market cycle while delivering a better borrower experience.

In this episode:

How are lenders improving efficiency in today’s housing finance market?
Lenders are improving efficiency by digitizing and automating key steps in the mortgage process, including underwriting, income and employment verification, and data validation. Tools that reduce manual documentation help lower origination costs, shorten cycle times, and improve consistency across fluctuating market conditions.

What does resilience mean in the mortgage and housing finance ecosystem?
Resilience means a lender’s ability to perform consistently across economic cycles by managing risk, maintaining data quality, and using technology that scales with volume changes. A resilient mortgage operation is prepared for both market slowdowns and rapid growth without sacrificing loan quality or borrower experience.

Why is loan data quality critical for mortgage lenders and investors?
Loan data quality is critical because inaccurate or incomplete data increases defects, repurchase risk, and operational costs. Verifying income, employment, and assets earlier in the loan lifecycle helps lenders deliver cleaner loans, meet investor requirements, and reduce downstream risk.

How can digital income and employment verification reduce mortgage costs?
Digital income and employment verification reduce costs by eliminating manual document collection and repeated reviews. Lenders using automated, source-verified data can save hundreds to thousands of dollars per loan, reduce cycle times by several days, and significantly lower the likelihood of income-related defects.

Emmaline Aliff of Equifax sits down with Matt Orlando, Chief Experience Officer at Informative Research, to unpack one of the most talked-about developments in mortgage lending: FICO’s new Mortgage Direct Licensing program and what it could mean for lenders, credit providers, and borrowers.

In this episode:

What is FICO’s Mortgage Direct Licensing program?

FICO’s Mortgage Direct Licensing program allows lenders and technology providers to license FICO scores directly, rather than receiving them solely through traditional credit reporting agencies. The program is still new, and its full impact on the mortgage ecosystem has yet to be determined.

How could FICO Direct Licensing impact mortgage lenders?

Lenders are still evaluating how the program will affect their overall cost of credit each month and whether it will increase expenses across the loan lifecycle.

What risks does Direct Licensing introduce into the mortgage market?

The program introduces risk across multiple layers of the ecosystem. Credit reporting agencies may now be asked to generate scores—something they have not historically done. Lenders must assess the reliability of these scores, while the broader mortgage market and borrowers face uncertainty as scoring responsibility shifts to a more fragmented landscape.

How might borrowers be affected by these changes?

Borrowers could ultimately bear higher costs if credit expenses rise for lenders. There is also risk tied to accuracy and consistency as new parties begin generating credit scores. The long-term borrower impact remains unclear.

Bobby Deery sits down with Praveen Chandrahomhan, SVP of Origination Growth at Cotality, to explore how AI is reshaping mortgage lending. They discuss the rise of “micro AI” in origination, the balance between speed and empathy in the borrower journey, and why personalization and retention are becoming critical in a purchase-driven market. 

In this episode:

How is AI changing mortgage lending?

AI is improving customer service, underwriting, document processing, and workflow automation while keeping humans in the loop. AI helps lenders increase speed, accuracy, and empathy throughout the borrower journey.

What mortgage challenges does AI help solve?

The conversation highlights how AI reduces friction, improves clarity for borrowers, lowers operational costs, and supports more personalized experiences—especially in a highly regulated, purchase-driven market.

Why are personalization and retention so important right now?

With fewer refinance opportunities and evolving trigger legislation, lenders are prioritizing retention and relationship-based lending. AI-powered data and automation help lenders stay connected to borrowers across the full lifecycle of homeownership.

Recorded live at MBA Annual25 in Las Vegas, this special edition of the Equifax Market Pulse explores how data, workflow automation, and AI are reshaping mortgage lending. Tanja Cleve, SVP of Solution Sales at Equifax sits down with Craig Rebmann, Product Evangelist at Dark Matter Technologies, to discuss capturing data earlier in the process, automating complex borrower scenarios, managing costs in tight margin environments, and preparing lenders for the next market turn through smarter technology investments.

In this episode:

What is the biggest operational challenge mortgage lenders are facing right now?
Beyond rates and affordability, lenders are grappling with process inefficiencies, higher fallout rates, and rising costs. This makes automation and better data workflows essential.

How does capturing data earlier in the loan process help lenders?
Early data capture allows lenders to assess risk sooner, automate pre-approvals, reduce downstream surprises, and create more productive borrower conversations upfront.

How can automation support complex borrower profiles like self-employed income?
Automation helps identify complexity early and uses tax and income data to streamline calculations, reducing manual review and improving underwriting readiness.

How are lenders balancing innovation with cost control in a tight market?
Many are focusing on capacity management, which used technology to increase efficiency with existing staff while remaining scalable as volumes return.

What role does AI play in today’s mortgage technology stack?
AI is increasingly used to gather and prepare information, while humans remain essential for judgment, decision-making, and borrower communication.

What is “agentic AI” and why does it matter for lenders?
Agentic AI refers to systems that can take action—not just provide insights—while still operating within defined workflows and human oversight.

How do integrations and APIs improve borrower experience?
Connected systems allow data to flow in real time, trigger automations instantly, reduce back-and-forth, and give borrowers greater transparency throughout the process.

Recorded live at the 2025 MBA Annual in Las Vegas, this special episode of Market Pulse explores how down payment assistance programs can help unlock homeownership amid today’s affordability challenges. Joel Rickman of Equifax sits down with Rob Chrane, Founder and CEO of Down Payment Resource, to discuss how lenders, real estate professionals, and technology can better connect buyers to thousands of available programs—and why awareness, education, and alignment are key to getting more families into homes.

In this episode:

What is down payment assistance, and how does it help homebuyers?

Down payment assistance (DPA) includes grants, forgivable loans, and other programs that help cover down payments and closing costs. These programs can significantly reduce upfront cash requirements and make homeownership more accessible—especially for first-time buyers and middle-income households.

How many down payment assistance programs exist today?

According to Down Payment Resource’s latest Homeownership Program Index, there are more than 2,600 active homeownership assistance programs nationwide, administered by over 1,300 state, local, and nonprofit organizations.

Who qualifies for down payment assistance programs?

Eligibility varies by program, but many programs serve more than just low-income buyers. Some programs:

• Have no household income limits
• Support middle-income and “missing middle” buyers
• Apply to manufactured homes and multifamily (2–4 unit) properties
• Are available nationally or in high-cost housing markets

Why don’t more buyers use down payment assistance?

The biggest barrier isn’t funding—it’s awareness. Many buyers (and even industry professionals) don’t know these programs exist. Fragmentation, lack of standardization, and fear of complexity have historically limited adoption.

How do lenders and loan officers use Down Payment Resource?

Down Payment Resource provides tools that:

• Match borrowers and properties with eligible assistance programs
• Integrate with loan origination systems (LOS)
• Surface vetted programs automatically during the lending process
• Help lenders educate borrowers without adding operational burden

In this special holiday edition, Emmaline Aliff is joined by Equifax Advisors Tom O’Neill, Dave Sojka, Jesse Hardin, and Maria Urtubey for a “Santa Scorecard” look back at what was naughty or nice in the 2025 economy, and what may change in 2026. The group unpacks AI adoption, rate cuts, equity market resiliency, and rising consumer stress signals—from student loans to auto and mortgage delinquencies. They close with 2026 resolutions, including what they’re watching most closely.

Economist Shandor Whitcher from Moody’s Analytics provides this episode’s macroeconomic update.

What are the key economic themes discussed?

·       AI adoption at the personal and industry level—and its economic impact

·       The state of inflation, growth, and consumer sentiment

·       Federal Reserve rate cuts and what they mean for credit, housing, and auto loans

·       Equity market resiliency and the role of higher-income households

·       Rising delinquencies in student loans, auto, and mortgages

·       Government shutdowns and gaps in economic data

·       The persistence—and possible evolution—of the K-shaped economy

What are the biggest risks heading into 2026?
The panel highlights labor market softening, affordability pressures, consumer reliance on credit, and uncertainty around policy, tariffs, and inflation.

What are the key takeaways for businesses and lenders?

·       Consumer financial health is increasingly uneven across income tiers

·       Credit performance signals require closer monitoring in 2026

·       AI and alternative data sources are becoming essential for economic insight

·       Adaptability and resilience will be critical as uncertainty continues

Have feedback or want to be a guest?
Contact the Equifax Advisors team at [email protected].

Jennifer Henry of Equifax sits down with Andrew Davidson, president of Andrew Davidson & Co. and a leading voice in mortgage analytics, to unpack one of the most misunderstood elements of housing finance: credit scores. They explore what a credit score actually measures, why different models and bureaus produce different results, how VantageScore’s adoption could reshape risk evaluation, and what investors, lenders, and consumers need to know as the industry shifts toward new data sources and scoring frameworks.

What is a credit score and what does it measure?

A credit score is a model applied to a specific credit file to predict the likelihood that a borrower will become delinquent. It is based only on the data included in that credit file, not the consumer’s entire financial life.

Why do credit scores differ between bureaus or scoring companies?

Scores vary because:

• Each bureau holds different underlying data.
• Scoring companies group data differently based on their models.
• The same borrower may fall into different “risk buckets” depending on how the model evaluates attributes (e.g., payment history, utilization, depth of file).

Different models may both predict risk effectively yet categorize borrowers differently.

How does adopting multiple scores (e.g., VantageScore + FICO) affect the industry?

Having multiple accepted scores encourages deeper analysis of:

• How risk is grouped and measured
• Which score is most predictive for different loan types
• How investors calibrate pricing and performance expectations

This shift pushes the industry to understand why scores differ, not just rely on a single number.

How could alternatives to tri-merge (bi-merge or single file) impact lending decisions?

Using fewer files may lower cost and streamline operations, but may reduce visibility into borrower behavior—especially for thin-file or non-traditional applicants. More data generally improves risk grouping.

How does alternative data (e.g., utilities, telco, rental history) influence credit scoring?

Alternative data helps:

• Create a more complete financial picture
• Surface strong repayment behavior not shown on traditional trade lines
• Improve risk assessments for people with non-traditional income patterns or limited credit history

However, adding new data is not enough. Lenders and investors must also understand how that data influences models.

Where can listeners learn more?

Andrew Davidson & Co: ad-co.com
Financial Lifecycle Education (FiCycle): ficycle.org