by Thomas Galbraith, Co-Founder, Barker
The asset-backed lending (ABL) landscape is undergoing a major transformation. With short-term yields still elevated and the cost of capital at its highest point in more than a decade, both lenders and borrowers are facing new challenges that require sharper decision-making and more precise tools. Much like traditional banks, credit unions are working to strike the right balance between offering competitive terms while also protecting their margins in an environment where capital is expensive and investor expectations are rising.
Investors evaluating ABLs today are more discerning and more attuned to how lenders assess risk and structure deals. Borrowers are finding that higher interest rates can dramatically change the feasibility of financing strategies that once felt straightforward. Against this backdrop, one question is becoming central to both sides of the table: How do we make ABLs efficient, fair, and sustainable when borrowing costs are higher than ever?
It’s no surprise that in 2026 and beyond, the answer increasingly lies in embracing advanced technology, particularly AI. I’ve found that the ability to offer accurate pricing to clients helps them dynamically reduce risk and respond quickly to market shifts; it’s becoming essential infrastructure for lenders that want to stay competitive and resilient.
High Short-Term Yields Are Reshaping ABL Expectations
One of the biggest forces reshaping the ABL market is the persistently high yield on short-term instruments. Treasury bills and other short-duration assets continue to offer unusually strong returns, setting a new baseline for investors and raising the opportunity cost of deploying capital elsewhere. For lenders, this means the underlying cost of funds is higher, which compresses margins and creates pressure to justify every pricing decision. Borrowers feel this pressure too, as higher carrying costs make it more difficult to pursue refinancing strategies or secure additional liquidity.
Investors now expect stronger returns from ABLs because they have safer alternatives that deliver attractive yields. As a result, deal terms are tightening, negotiations are lengthening, and competitive differentiation is becoming more important across the lending landscape. In this environment, credit unions that rely on manual, static, or purely experience-based pricing models may struggle to respond quickly enough to shifting conditions. What once worked in a low-rate world now risks leaving value on the table or losing borrowers altogether.
Why Traditional Pricing Models Fall Short in Today’s Market
Many credit unions still rely on familiar but dated methods such as spreadsheets, manual reviews, or valuations that function more like opinions than data-backed, enforceable instruments. These tools limit a lender’s ability to produce consistent, transparent, market-responsive pricing. In a low-rate environment, these imperfections were inconvenient but generally survivable, but in today’s higher-yield environment, they introduce real financial and competitive risks.
Traditional pricing workflows often lead to overpricing, which pushes otherwise strong borrowers toward more aggressive competitors. They can also lead to underpricing, which erodes profitability and increases financial exposure at a time when margins are already tight. These workflows are also slow, which puts lenders at a disadvantage in a market where borrowers expect decisions in hours, not days. Since traditional pricing relies on static inputs, it rarely adapts quickly when yield curves shift or liquidity tightens.
This is one place where technology can play a transformative role. Pricing should empower lending, not constrain it. By utilizing AI-powered technology to turn valuations into more standardized, data-backed tools, lenders can operate with far greater clarity and confidence.
How AI-Powered Pricing Can Offset Higher Borrowing Costs
AI-driven pricing engines can provide credit unions and commercial lenders with a more precise, efficient, and reliable method for pricing loan collateral, particularly in markets where capital is scarce. The goal is not to replace human expertise, but to augment it with faster analysis, stronger protections, and more consistent pricing recommendations.
One of the clearest benefits of AI-powered pricing is its ability to deliver more accurate and defensible valuations. AI models can analyze thousands of variables (like asset history, asset-specific market trends, and real-time supply and demand dynamics) to arrive at a price that reflects true, measurable risk. This precision helps avoid the unnecessary “risk padding” that often gets added to pricing when lenders feel uncertain about the underlying valuation. In today’s market, where every basis point matters, reducing that uncertainty can make loans more attractive to borrowers while still protecting credit union profitability.
AI also dramatically accelerates the pricing and approval process. Borrowers operating under higher interest rates tend to move quickly, and they expect lenders to keep pace. AI-driven pricing enables faster internal decision-making, fewer points of friction between underwriting and pricing teams, and a more streamlined overall experience. Speed becomes a strategic advantage, and in many cases, the factor that determines whether a credit union wins or loses a deal.
Another important advantage is the ability for AI models to adjust continuously as market conditions change. Traditional pricing tools often update monthly or quarterly, but AI-driven systems can reflect market movements in real time. By incorporating data feeds that help lenders align pricing decisions with current market conditions, both precision and consistency are enhanced. Asset valuations should not merely be opinions, but enforceable instruments that empower action. This philosophy enables lenders to feel confident in their decisions, even in volatile market conditions.
Finally, AI offers deeper and more dynamic insight into loan collateral and portfolio risk. High-rate environments often lead borrowers to explore more complex or creative financing options. AI helps lenders evaluate those scenarios more accurately, assessing factors like asset volatility, borrower behavior patterns, and concentration risk. This leads to higher-quality portfolios and stronger long-term performance, which are outcomes that both lenders and investors value highly.
The Bottom Line: AI Is Now a Core Competitive Advantage
As the ABL landscape continues to evolve, credit unions will need to navigate rising investor expectations, a higher cost of capital, and a more competitive market for borrowers. Technology, particularly AI-driven pricing, offers a strategic advantage. It enables lenders to deliver more competitive terms, operate with greater efficiency, and strengthen their risk management practices, all while maintaining the trust and transparency that credit unions are known for.
At Barker, our mission is to bring greater transparency and trust to asset valuations by using AI to deliver more accurate, reliable, and actionable pricing. To learn more about Barker, or to access our pricing portal, visit www.thebarkerprice.com.