Asset-backed lending (ABL) has long been a crucial but underappreciated part of the global financial system. It allows unlocking of capital by leveraging assets, without diluting ownership or relying on expensive unsecured loans. However, the traditional model has struggled with one persistent challenge: how to accurately and efficiently value collateral at scale.
Today, artificial intelligence, machine learning, and advanced analytics are transforming that process. ABL is no longer a niche financing option. It is rapidly becoming one of the most data-driven and technology-enabled segments in modern finance. According to the recently published Global Strategic Business Report, the global asset-based lending market is conservatively projected to grow from $701 billion USD in 2024 to more than $1.3 trillion by 2030, representing a compound annual growth rate in the double digits.
This surge is being fueled by tightening credit conditions, the rise of alternative credit structures, and increasing demand from small and mid-sized enterprises (SMEs) seeking liquidity. Across the industry, AI in finance is reshaping how risk is assessed, how assets are valued, and how capital becomes accessible, and it’s only accelerating from here.
The Problem with Traditional Collateral Valuation
For decades, asset-backed lending was limited by the manual nature of asset valuation. Appraisers relied on limited data and largely subjective assessments. For highly liquid assets, such as real estate or vehicles, this was workable. But when it came to nontraditional assets—collectibles, private jets, or intellectual property—it became a roadblock.
These assets are valuable but notoriously difficult to appraise. Without reliable, scalable methods to determine their worth, lenders have been forced to discount them, offer bad terms or exclude them entirely. The result: asset-rich but cash-poor individuals or businesses unable to harness the benefits of traditional financing.
That’s where AI-powered valuation steps in.
By training machine learning models on millions of data points—from historical transactions and auction results to market sentiment and physical condition—AI can now generate instant, data-backed valuations. These are consistent, accurate, and continuously updated as new data flows in.
Turning Data into Dynamic Collateral
The next frontier for ABL goes beyond stronger valuation and into real-time collateral monitoring.
Traditionally, once a loan was approved, lenders had limited visibility into how the value of the collateral changed over time. A piece of equipment might depreciate faster than expected, or a luxury watch might appreciate in value due to scarcity. Until recently, lenders could only reappraise periodically, introducing inefficiency, cost and risk.
AI-driven asset monitoring systems are changing that. By combining predictive analytics, computer vision, and external data feeds, lenders can now track the health and value of collateral continuously. These “living valuations” are dynamic assessments that evolve as the market does.
These systems integrate auction data, sensor inputs, economic indicators, and environmental conditions to update valuations in real-time. The result is a more accurate view of exposure, allowing lenders to make proactive decisions before risks materialize.
While challenges remain (such as data quality, model drift, and outlier events), AI’s predictive capabilities are turning static lending into a dynamic, insight-driven discipline.
Expanding the Definition of Collateral
One of the most transformative impacts of AI in finance is its ability to expand what counts as collateral.
Historically, asset-backed lending focused on hard assets like property, inventory, and equipment. But thanks to AI and machine learning-based valuation, lenders can now confidently appraise nontraditional assets like art, intellectual property, and even GPUs.
This evolution has major implications for mid-market and entrepreneurial borrowers. Many of these businesses hold valuable but illiquid assets that were previously unusable for credit. AI-driven valuation models are turning those assets into bankable collateral, creating new pathways to capital for innovators and business owners.
In other words, AI isn’t just improving lending efficiency. It’s democratizing access to financing. By making alternative collateral types viable, technology is leveling the playing field for smaller players in need of liquidity.
The Human-AI Partnership in Modern Lending
Despite the automation revolution, AI in lending doesn’t eliminate human expertise. Rather, it amplifies it.
AI excels at pattern recognition, trend analysis, and anomaly detection. But lending still requires context, experience, and judgment, which are qualities that only people can bring. The most effective lenders are those who use AI as a co-pilot, not a replacement.
Machine learning can surface insights or highlight risk factors that humans might overlook, while human analysts can interpret those insights through the lens of market realities and relationships. This synergy accelerates decision-making and improves both speed and quality of underwriting.
Ultimately, the future of lending technology lies in the combination of human expertise and AI.
What Comes Next for AI-Driven Lending
The next decade will redefine how financial institutions think about collateral, credit, and risk.
The fundamentals of lending remain the same. What’s changing is the data infrastructure that supports them. With AI-powered lending systems, lenders can operate with far greater agility and insight. Borrowers, meanwhile, can tap into capital that’s aligned with the real value of their assets, without the limits of outdated valuation models.
As AI continues to mature, we’ll see more personalized lending offers, better fraud detection, and more intelligent risk forecasting. For asset-backed lending, this means a more inclusive, data-driven, and transparent marketplace, and capital will flow more efficiently to where it’s needed most.
At Barker, our mission is to make that transformation real: combining the precision of our AI with the protection of our warranty to build a more innovative, fairer lending ecosystem.
About Barker
Barker is a financial technology company that uses proprietary AI models to deliver highly accurate, real-time valuations of hard-to-price collateral. Barker combines advanced pricing and insurance-backed protection to help lenders unlock new opportunities, de-risk complex collateral, and boost profitability. Learn more at: thebarkerprice.com
Thomas Galbraith, Co-Founder at Barker
