Where AI & ChatGPT Are Offering Equipment Asset Management Opportunities and Challenges for Equipment Finance Professionals

by Hadley Benton

Hadley Benton is Executive Vice President of Business Development at Fleet Advantage, a leading innovator in truck fleet business analytics, equipment financing and lifecycle cost management. 

AI has dominated recent headlines, with the introduction of ChatGPT and other platforms capable of an amazing and ever-growing list of feats. In its continuous search for new and exciting technology to employ, the financial sector could be changed by AI forever. Hadley Benton, executive vice president of business development at Fleet Advantage, puts things into perspective.

The highly developed and evolving artificial intelligence (AI)-driven tools and resources, including those that employ natural language processing like ChatGPT and Google’s recent AI offering Bard, are providing many new opportunities for today’s finance professionals. And while experts in the industry are becoming more aware of these resources, it is still unclear to what extent these advanced resources will be used in financing assets and asset management.

Like many other leading-edge technology resources today, these advanced AI tools possess incredible promise. Still, finance executives need to understand the pros and cons of how far they can rely on such tools for their day-to-day decision making, and for their clients.

How do finance organizations view AI & ChatGPT?

These advanced resources are increasingly being discussed because the finance industry has been looking at new-age tools like Open AI ChatGPT since it was initially released in November 2022. While the Chat Generative Pre-Trained Transformer (ChatGPT) is still new, there is a lot of buzz surrounding the technology because of its ability to create immediate responses on virtually every topic. What’s more, because AI drives the tools, they leverage human-like language during the interaction.

ChatGPT promises to dramatically increase organizational visibility, build a baseline for strategies and plans, streamline internal and external communication, and optimize end-to-end operations.

AI and ChatGPT are being used across all industries today, but finance professionals are highly interested in the opportunities it creates for asset management strategies and financing.

As an example, when you ask ChatGPT why asset management is vital for equipment finance it offers the following excerpts:

‘Asset management helps to maximize the value of equipment over its lifespan by ensuring that it is properly maintained and used efficiently. This can lead to reduced downtime, increased productivity, and extended equipment life, ultimately increasing the equipment’s overall value. Asset management enables finance companies to effectively plan for equipment replacement or upgrades, ensuring that they can provide clients with the most up-to-date and efficient equipment possible. This can also help finance companies to manage cash flow and budget more effectively.’

While it’s understandable to view this as a thorough overview of the role of asset management, some inconsistencies are too inaccurate to ignore. For example, traditional finance companies and banks play no part in planning equipment replacement or upgrades.

When you ask ChatGPT to build an asset management plan for a Class-8 heavy-duty truck fleet, it will generate a high-level overview covering topics such as equipment inventory, preventative maintenance, telematics and IoT solutions, driver training and safety programs, replacement and upgrade planning, budget and cash flow management, and reporting. These are all baseline topics that need to be considered for asset management.

But it’s important to keep in mind that ChatGPT will not answer financial/mathematical questions, but it will defer to pros and cons of a business transaction like buying or leasing. It also tends to give wrong answers because it pings millions of web references to what you ask and then tries to compile the most frequently mentioned text. Without the proper knowledge and expertise, you could make wrong decisions that could negatively impact your operation.

Therefore, it is crucial to understand that any inaccuracies produced by an AI tool may have consequences in financial loss outcomes, legal or even defamation toward an organization. This also includes defining the trustworthy source of who produces any material developed entirely or in part by an AI tool such as ChatGPT. While no laws currently determine the responsibility for any inaccuracies, it is widely speculated that regulation could soon be forthcoming as a set of guidelines1.

Why it’s a cause for concern among finance professionals

However, ChatGPT won’t serve as a solution to help build a custom financing and asset management strategy. Aside from the general considerations, ChatGPT is not built to analyze asset operating data, such as miles driven per year by a transportation fleet, to create an effective procurement strategy based on a life cycle that best suits that organization. And while it’s hard to fathom organizations will actually rely on ChatGPT to create their entire plan, some may confuse it with analytic or SAAS tools in the market. Depending too much on a standardized approach during the procurement planning phase without incorporating actual vehicle operating data, for example, can be problematic.

When building a proper procurement modernization plan for vehicle asset management, it is critical to arrive at a strategy that produces optimum flexibility and agility within the financial and operational business model. While ChatGPT on its own can’t produce a plan with this level of detail, organizations can utilize those existing analytic tools that provide AI-driven analytics to help closely monitor key metrics such as:

  • Lease versus purchase analysis
  • Life cycle cost analysis
  • Sales Tax analysis
  • Unbundled vs. Full-Service Lease Analysis
  • Comparative Cost Analysis to determine the optimal time to upgrade equipment, etc.
  • Per unit P&L
  • Predictive Life Cycle Modeling

Identifying where AI can be beneficial

Aside from finance, asset management and procurement, AI tools are impacting operations for organizations in various industries.

Several recent studies illustrate the significant benefits that AI tools have over traditional spreadsheet analytics. A recent study by McKinsey & Company estimated that AI-powered technologies can reduce errors between 20% – 50% for organizations focused on supply chain management2.

Furthermore, the Boston Consulting Group (BCG) offers a report that shows how AI may help organizations achieve $1.5 trillion in additional value3 from increased productivity and reduced downtime in the global industrial sector by 2030. For M&R operations within the manufacturing sector, a separate McKinsey report found that AI-enhanced predictive maintenance of industrial equipment will generate a 10% reduction in annual maintenance costs, up to a 20% downtime reduction and 25% reduction in inspection costs4.

Total Cost of Ownership (TCO) analytic tools that provide life cycle cost management with billions of miles of data and understand the full scope of TCO are continuously monitoring economic factors, used truck values, depreciation, emissions, performance data, and equipment costs to determine the optimum procurement and asset management strategy.

This is important because TCO analytic tools that leverage predictive modeling allow equipment finance professionals to help organizations with transportation fleets create future business insights with significant accuracy. With sophisticated data analytic tools and modeling, these companies can use historical and current operating data to accurately forecast budget trends in milliseconds, days, or years into the future. As more AI-powered resources are available, companies must work closely with their finance and asset management partners to ensure these tools are used effectively to boost operations and their bottom lines. Understanding the company’s specific challenges, finance and asset management partners can also help identify which AI-powered tools are best suited to address those challenges and how to integrate them into their operations properly.





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