Matthew Hinkley,
Sales Engineer & Systems Implementation Specialist,
TAO Solutions

Creating compliant, scalable automation within any industry is a challenge. However, three emerging technologies on a path of rapid growth in the digital era could soon be the solution, especially within equipment finance.

The equipment finance sector in North America is at a crossroads. As businesses and economies strive for greater efficiency and agility, the integration of cutting-edge technologies such as the Internet of Things (IoT), blockchain and artificial intelligence (AI) offers an unprecedented opportunity to transform the way equipment is financed, managed and maintained. These technologies, while still evolving, promise to affect every aspect of equipment finance, from the speed of transactions to the accuracy of asset valuations.

LOST IN THE MACHINE
Currently, the equipment finance industry faces several key challenges. One of the most significant is inefficiency around collateral valuation. Traditional methods rely on outdated data, often leading to inaccurate valuations and suboptimal lending decisions. Moreover, maintenance practices are largely reactive rather than proactive, resulting in higher operational costs and unexpected equipment downtime. The process of transferring ownership of financed equipment remains cumbersome, often requiring extensive documentation and multiple levels of manual verification, which slows down the transaction process. Payment processing is another area that suffers from inefficiency, with transactions often taking days or weeks to clear due to legacy financial systems and manual reconciliation methods.

Compliance and regulatory challenges further compound these issues, as adherence to constantly evolving standards requires significant time and resources. The industry’s current approach to risk assessment is predominantly reactive once again, relying on historical data that may not accurately predict future market conditions or borrower behavior. Estimating the depreciation of assets is
similarly complex and prone to inaccuracies, affecting both the pricing of finance products and the overall profitability of lending portfolios.

Let’s explore how the “golden trifecta” of IoT, blockchain and AI might solve these problems and drive the next wave of growth and innovation for equipment finance.

THE GOLDEN TRIFECTA
Over the last decade, the rapid rise of IoT, blockchain and AI has set the stage for a technological revolution across various industries. IoT has emerged as a game-changer, with a market size valued at $1.18 billion in 2023.¹

Ninety percent of all data ever captured has been amassed in the last two years.² Clearly, there has been a rapid growth in IoT devices and the volume of data generated to monitor certain assets or individuals and provide defined analysis and predictions. In the context of equipment finance, IoT’s ability to provide real-time data on asset performance and utilization can radically improve decision-making and operational efficiency.

Meanwhile, blockchain technology has gained momentum, with global investments reaching $12.4 billion in 2023.³ Despite early associations with cryptocurrencies, blockchain’s potential for creating secure, immutable records has started to gain recognition in areas like supply chain management and healthcare, though its adoption in finance remains slower.

Artificial intelligence has also experienced exponential growth, becoming a central focus for businesses seeking to optimize processes and enhance predictive capabilities. For the equipment finance sector, AI’s capacity to analyze vast datasets and predict risk scenarios offers a path to more accurate credit assessments, improved asset management and greater overall efficiency.

THESE TECHNOLOGIES AREN’T PERFECT — YET
Despite this growth, challenges persist that limit the industry’s full potential. Inefficiencies in asset valuation, slow payment processing, reactive maintenance and cumbersome compliance procedures continue to weigh heavily on the sector.

While the promise of IoT, blockchain and AI is evident, each technology also faces unique challenges. IoT, for instance, encounters trust issues around the accuracy and security of data captured by sensors. With millions of devices generating data, ensuring the validity and reliability of that information becomes a formidable task. Blockchain, despite its potential to provide a single source of truth,
has faced hurdles due to its association with cryptocurrencies, which has led to a slower uptake in the financial services sector. Furthermore, blockchain networks must overcome scalability issues and meet stringent regulatory requirements to achieve broader adoption. AI, on the other hand, grapples with challenges around data integrity and the potential biases inherent in its algorithms. The effectiveness of AI models hinges on the quality and diversity of the data they are trained on, making data management a critical concern.

Yet, when combined, these technologies can mitigate each other’s limitations and offer a cohesive solution. For example, IoT devices can feed real-time data into blockchain networks, ensuring data integrity and enhancing transparency, while AI can analyze this data to provide actionable insights. Together, these technologies hold the potential to address many of the industry’s current inefficiencies
and pave the way for a more streamlined, data-driven future.

THE TROJAN HORSE OF AUTOMATION
Looking ahead to the next couple of decades, the equipment finance industry stands on the brink of a transformative era. As IoT devices proliferate, the ability to capture real-time data on assets will enable more accurate and timely assessments of equipment value and condition. This real-time data will empower proactive maintenance strategies, reducing downtime and operational costs. Coupled
with AI-powered predictive analytics, lenders will be better equipped to anticipate market trends, assess risk more accurately and make more informed lending decisions.

The integration of AI and blockchain technologies will enable a new level of automation and transparency in compliance and risk management. AI will be able to use enhanced data points to predict defaults or fraudulent activity, while blockchain will provide an immutable ledger that ensures the integrity and security of that data. This combination will significantly reduce the time and cost associated with regulatory compliance, making the process more efficient and reliable. If it became an industry standard for each stakeholder — from lenders to vendors — to have some kind of node that reports data anonymously, securely and cryptographically, but also allows each stakeholder to pull information in real time, this would offer a new level of compliance, credit scoring and collateral evaluation.

In the future, AI will analyze vast datasets, including real-time data from IoT devices, to create more comprehensive and dynamic credit profiles for individuals, businesses and assets. This will allow lenders to make faster, more accurate assessments of creditworthiness, improving both the speed and quality of lending decisions.

The application of blockchain in equipment finance could streamline ownership transfer and payment processes, cutting transaction times from days to mere seconds. This technology will eliminate the need for multiple levels of verification and approval, providing a secure, transparent and efficient mechanism for transactions.

Additionally, AI and IoT will enable more advanced asset utilization management, allowing lenders to monitor real-time utilization and adjust lending terms accordingly. This will lead to more accurate asset valuations, better pricing of finance products and reduced idle time for financed equipment. Imagine, for example, a smart contract designed around credit conditions and risk policies that is overseen by IoT devices and the data that is offset by them. Punishments or rewards in interest rates and fees could be given automatically based on the performance of the borrower.

In many ways, the future state of equipment finance could resemble the evolution of transportation from traditional taxis to autonomous ride sharing services like Uber. Just as Uber uses GPS, mobile payments and AI to provide a seamless transportation experience, the equipment finance industry could use IoT, blockchain and AI to create a seamless, automated financing experience where transactions are instantaneous, data is reliable and decision-making is highly predictive.

RIDE THE WAVE OF DIGITAL TRANSFORMATION OR BE LEFT BEHIND
The equipment finance industry is poised for significant evolution over the next two decades. As the demand for capital equipment continues to grow — driven by the need for more efficient, productive machinery in sectors such as construction, agriculture and mining — the industry will need to adopt more advanced technological solutions to keep pace. By leveraging IoT, blockchain and AI, equipment finance can become more efficient, transparent and scalable, ensuring continued growth and relevance in an increasingly digital world. The total volume of deals and financing is set to increase, but only if the industry embraces these technological advancements to overcome its current challenges. •

¹ “Internet of Things (IoT) Market Size & Trends,” Grand View Research.
² Bartley, Kevin, “Big Data Statistics: How Much Data is There in the World?” Rivery, Aug. 27, 2023.
³ “Blockchain Market Trends and Analysis by Application, Vertical, Region, and Segment Forecast to 2030,” Research and Markets, May 2024.

Matthew Hinkley started his career in fintech in Europe mapping both debt and equity lenders into Europe’s largest online brokerage. He has been consistently trying to improve the relationship between lender and borrower within the finance space using technology throughout his career. In 2017, Hinkley moved to Canada, where he became a technology analyst at PwC with a large focus around emerging technologies such as AI and blockchain. Following two years at PwC, Hinkley moved on to build his own company, providing a compliant onboarding tool for banks and other financial institutions in the Caribbean. Most recently, Hinkley joined LeaseSpark, a TAO Solutions asset-finance software application solution, where he helps manage and onboard new client accounts while
aiding product solution design